From a5b1079e39bad052e6da3c5d3fba44d7a000993a Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 15 Mar 2024 11:57:53 +0100
Subject: [PATCH 001/188] work in progress

---
 supervision/annotators/core.py | 91 +++++++++++++++++++++++++++-------
 1 file changed, 74 insertions(+), 17 deletions(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 0c834fa86..1c63b2324 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1847,7 +1847,14 @@ class CropAnnotator(BaseAnnotator):
     A class for drawing scaled up crops of detections on the scene.
     """
 
-    def __init__(self, position: Position = Position.TOP_CENTER, scale_factor: int = 2):
+    def __init__(
+        self,
+        position: Position = Position.TOP_CENTER,
+        scale_factor: int = 2,
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
+        thickness: int = 2,
+        color_lookup: ColorLookup = ColorLookup.CLASS
+    ):
         """
         Args:
             position (Position): The anchor position for placing the cropped and scaled
@@ -1858,13 +1865,17 @@ def __init__(self, position: Position = Position.TOP_CENTER, scale_factor: int =
         """
         self.position: Position = position
         self.scale_factor: int = scale_factor
+        self.color: Union[Color, ColorPalette] = color
+        self.thickness: int = thickness
+        self.color_lookup: ColorLookup = color_lookup
 
     @scene_to_annotator_img_type
     def annotate(
         self,
-        scene: np.ndarray,
+        scene: ImageType,
         detections: Detections,
-    ) -> np.ndarray:
+        custom_color_lookup: Optional[np.ndarray] = None,
+    ) -> ImageType:
         """
         Annotates the provided scene with scaled and cropped parts of the image based
         on the provided detections. Each detection is cropped from the original scene
@@ -1873,8 +1884,12 @@ def annotate(
 
 
         Args:
-            scene (np.ndarray): The image where cropped detection will be placed.
+            scene (ImageType): The image where cropped detection will be placed.
+                `ImageType` is a flexible type, accepting either `numpy.ndarray`
+                or `PIL.Image.Image`.
             detections (Detections): Object detections to annotate.
+            custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
+                Allows to override the default color mapping strategy.
 
         Returns:
             The annotated image.
@@ -1901,37 +1916,79 @@ def annotate(
         ]
         anchors = detections.get_anchors_coordinates(anchor=self.position).astype(int)
 
-        for resized_crop, anchor in zip(resized_crops, anchors):
+        for idx, (resized_crop, anchor) in enumerate(zip(resized_crops, anchors)):
             crop_wh = resized_crop.shape[1], resized_crop.shape[0]
-            crop_anchor = self.calculate_crop_coordinates(
+            (x1, y1), (x2, y2) = self.calculate_crop_coordinates(
                 anchor=anchor, crop_wh=crop_wh, position=self.position
             )
-            scene = place_image(scene=scene, image=resized_crop, anchor=crop_anchor)
+            scene = place_image(scene=scene, image=resized_crop, anchor=(x1, y1))
+            color = resolve_color(
+                color=self.color,
+                detections=detections,
+                detection_idx=idx,
+                color_lookup=self.color_lookup
+                if custom_color_lookup is None
+                else custom_color_lookup,
+            )
+            cv2.rectangle(
+                img=scene,
+                pt1=(x1, y1),
+                pt2=(x2, y2),
+                color=color.as_bgr(),
+                thickness=self.thickness,
+            )
 
         return scene
 
     @staticmethod
     def calculate_crop_coordinates(
         anchor: Tuple[int, int], crop_wh: Tuple[int, int], position: Position
-    ) -> Tuple[int, int]:
+    ) -> Tuple[Tuple[int, int], Tuple[int, int]]:
         anchor_x, anchor_y = anchor
         width, height = crop_wh
 
         if position == Position.TOP_LEFT:
-            return anchor_x - width, anchor_y - height
+            return (
+                (anchor_x - width, anchor_y - height),
+                (anchor_x, anchor_y)
+            )
         elif position == Position.TOP_CENTER:
-            return anchor_x - width // 2, anchor_y - height
+            return (
+                (anchor_x - width // 2, anchor_y - height),
+                (anchor_x + width // 2, anchor_y)
+            )
         elif position == Position.TOP_RIGHT:
-            return anchor_x, anchor_y - height
+            return (
+                (anchor_x, anchor_y - height),
+                (anchor_x + width, anchor_y)
+            )
         elif position == Position.CENTER_LEFT:
-            return anchor_x - width, anchor_y - height // 2
+            return (
+                (anchor_x - width, anchor_y - height // 2),
+                (anchor_x, anchor_y + height // 2)
+            )
         elif position == Position.CENTER or position == Position.CENTER_OF_MASS:
-            return anchor_x - width // 2, anchor_y - height // 2
+            return (
+                (anchor_x - width // 2, anchor_y - height // 2),
+                (anchor_x + width // 2, anchor_y + height // 2)
+            )
         elif position == Position.CENTER_RIGHT:
-            return anchor_x, anchor_y - height // 2
+            return (
+                (anchor_x, anchor_y - height // 2),
+                (anchor_x + width, anchor_y + height // 2)
+            )
         elif position == Position.BOTTOM_LEFT:
-            return anchor_x - width, anchor_y
+            return (
+                (anchor_x - width, anchor_y),
+                (anchor_x, anchor_y + height)
+            )
         elif position == Position.BOTTOM_CENTER:
-            return anchor_x - width // 2, anchor_y
+            return (
+                (anchor_x - width // 2, anchor_y),
+                (anchor_x + width // 2, anchor_y + height)
+            )
         elif position == Position.BOTTOM_RIGHT:
-            return anchor_x, anchor_y
+            return (
+                (anchor_x, anchor_y),
+                (anchor_x + width, anchor_y + height)
+            )

From 9f5c63b32d88d5eed7dada3cebd37dce5623a7d7 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 15 Mar 2024 11:02:24 +0000
Subject: [PATCH 002/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/annotators/core.py | 32 ++++++++++----------------------
 1 file changed, 10 insertions(+), 22 deletions(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 1c63b2324..a96d91e1c 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1853,7 +1853,7 @@ def __init__(
         scale_factor: int = 2,
         color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
-        color_lookup: ColorLookup = ColorLookup.CLASS
+        color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
         """
         Args:
@@ -1948,47 +1948,35 @@ def calculate_crop_coordinates(
         width, height = crop_wh
 
         if position == Position.TOP_LEFT:
-            return (
-                (anchor_x - width, anchor_y - height),
-                (anchor_x, anchor_y)
-            )
+            return ((anchor_x - width, anchor_y - height), (anchor_x, anchor_y))
         elif position == Position.TOP_CENTER:
             return (
                 (anchor_x - width // 2, anchor_y - height),
-                (anchor_x + width // 2, anchor_y)
+                (anchor_x + width // 2, anchor_y),
             )
         elif position == Position.TOP_RIGHT:
-            return (
-                (anchor_x, anchor_y - height),
-                (anchor_x + width, anchor_y)
-            )
+            return ((anchor_x, anchor_y - height), (anchor_x + width, anchor_y))
         elif position == Position.CENTER_LEFT:
             return (
                 (anchor_x - width, anchor_y - height // 2),
-                (anchor_x, anchor_y + height // 2)
+                (anchor_x, anchor_y + height // 2),
             )
         elif position == Position.CENTER or position == Position.CENTER_OF_MASS:
             return (
                 (anchor_x - width // 2, anchor_y - height // 2),
-                (anchor_x + width // 2, anchor_y + height // 2)
+                (anchor_x + width // 2, anchor_y + height // 2),
             )
         elif position == Position.CENTER_RIGHT:
             return (
                 (anchor_x, anchor_y - height // 2),
-                (anchor_x + width, anchor_y + height // 2)
+                (anchor_x + width, anchor_y + height // 2),
             )
         elif position == Position.BOTTOM_LEFT:
-            return (
-                (anchor_x - width, anchor_y),
-                (anchor_x, anchor_y + height)
-            )
+            return ((anchor_x - width, anchor_y), (anchor_x, anchor_y + height))
         elif position == Position.BOTTOM_CENTER:
             return (
                 (anchor_x - width // 2, anchor_y),
-                (anchor_x + width // 2, anchor_y + height)
+                (anchor_x + width // 2, anchor_y + height),
             )
         elif position == Position.BOTTOM_RIGHT:
-            return (
-                (anchor_x, anchor_y),
-                (anchor_x + width, anchor_y + height)
-            )
+            return ((anchor_x, anchor_y), (anchor_x + width, anchor_y + height))

From 4f9e5a590f6a73d900fcd537420271190ba193bb Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Fri, 15 Mar 2024 22:20:02 +0300
Subject: [PATCH 003/188] =?UTF-8?q?ci:=20=F0=9F=91=B7=20develop=20doc=20co?=
 =?UTF-8?q?ncurrency=20added=20for=20single=20run=20and=20cancel=20old=20o?=
 =?UTF-8?q?nes?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 .github/workflows/docs.yml | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index fc59387f0..0661929e3 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -4,12 +4,18 @@ on:
   push:
     branches:
       - develop
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event_name == 'push' && github.ref}}
+  cancel-in-progress: true
 
 permissions:
   contents: write
   pages: write
   pull-requests: write
 
+
 jobs:
   deploy:
     runs-on: ubuntu-latest
@@ -23,7 +29,7 @@ jobs:
         with:
           python-version: '3.10'
       - name: 📦 Install mkdocs-material
-        run: pip install "mkdocs-material[all]"
+        run: pip install "mkdocs-material"
       - name: 📦 Install mkdocstrings[python]
         run: pip install "mkdocstrings[python]"
       - name: 📦 Install mkdocs-material[imaging]

From e8810fe8a20ccb68744beac4c578fed383ccf92f Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Sun, 17 Mar 2024 14:41:47 +0300
Subject: [PATCH 004/188] =?UTF-8?q?fix:=20=F0=9F=90=9E=20static=20type=20f?=
 =?UTF-8?q?ix=20for=20color=20constants=20to=20sv.Color?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 supervision/draw/color.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/supervision/draw/color.py b/supervision/draw/color.py
index 635ef47fd..149908d8c 100644
--- a/supervision/draw/color.py
+++ b/supervision/draw/color.py
@@ -176,31 +176,31 @@ def as_bgr(self) -> Tuple[int, int, int]:
         return self.b, self.g, self.r
 
     @classproperty
-    def WHITE(cls):
+    def WHITE(cls) -> Color:
         return Color.from_hex("#FFFFFF")
 
     @classproperty
-    def BLACK(cls):
+    def BLACK(cls) -> Color:
         return Color.from_hex("#000000")
 
     @classproperty
-    def RED(cls):
+    def RED(cls) -> Color:
         return Color.from_hex("#FF0000")
 
     @classproperty
-    def GREEN(cls):
+    def GREEN(cls) -> Color:
         return Color.from_hex("#00FF00")
 
     @classproperty
-    def BLUE(cls):
+    def BLUE(cls) -> Color:
         return Color.from_hex("#0000FF")
 
     @classproperty
-    def YELLOW(cls):
+    def YELLOW(cls) -> Color:
         return Color.from_hex("#FFFF00")
 
     @classproperty
-    def ROBOFLOW(cls):
+    def ROBOFLOW(cls) -> Color:
         return Color.from_hex("#A351FB")
 
     @classmethod

From 63b338751fffc6936b12e842a35f2cec86010407 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Sun, 17 Mar 2024 18:12:45 +0300
Subject: [PATCH 005/188] =?UTF-8?q?feat:=20=F0=9F=93=9D=20typing=20improve?=
 =?UTF-8?q?ment=20for=20polygone=20zone?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 supervision/detection/tools/polygon_zone.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index d7f228353..00b746aaa 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -3,6 +3,7 @@
 
 import cv2
 import numpy as np
+import numpy.typing as npt
 
 from supervision import Detections
 from supervision.detection.utils import clip_boxes, polygon_to_mask
@@ -39,7 +40,7 @@ class PolygonZone:
     )
     def __init__(
         self,
-        polygon: np.ndarray,
+        polygon: npt.NDArray[np.int64],
         frame_resolution_wh: Tuple[int, int],
         triggering_anchors: Iterable[Position] = (Position.BOTTOM_CENTER,),
     ):
@@ -54,7 +55,7 @@ def __init__(
             polygon=polygon, resolution_wh=(width + 1, height + 1)
         )
 
-    def trigger(self, detections: Detections) -> np.ndarray:
+    def trigger(self, detections: Detections) -> npt.NDArray[np.bool_]:
         """
         Determines if the detections are within the polygon zone.
 
@@ -78,13 +79,13 @@ def trigger(self, detections: Detections) -> np.ndarray:
             ]
         )
 
-        is_in_zone = (
+        is_in_zone: npt.NDArray[np.bool_] = (
             self.mask[all_clipped_anchors[:, :, 1], all_clipped_anchors[:, :, 0]]
             .transpose()
             .astype(bool)
         )
-        is_in_zone = np.all(is_in_zone, axis=1)
 
+        is_in_zone: npt.NDArray[np.bool_] = np.all(is_in_zone, axis=1)
         self.current_count = int(np.sum(is_in_zone))
         return is_in_zone.astype(bool)
 

From 123a61f2c69e4945fa44bed9314692a44536f97d Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 18 Mar 2024 01:21:26 +0000
Subject: [PATCH 006/188] :arrow_up: Bump ruff from 0.3.2 to 0.3.3

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.3.2 to 0.3.3.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.3.2...v0.3.3)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index a0c7044d2..42df1afc6 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3645,28 +3645,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.3.2"
+version = "0.3.3"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "ruff-0.3.2-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:77f2612752e25f730da7421ca5e3147b213dca4f9a0f7e0b534e9562c5441f01"},
-    {file = "ruff-0.3.2-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:9966b964b2dd1107797be9ca7195002b874424d1d5472097701ae8f43eadef5d"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b83d17ff166aa0659d1e1deaf9f2f14cbe387293a906de09bc4860717eb2e2da"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb875c6cc87b3703aeda85f01c9aebdce3d217aeaca3c2e52e38077383f7268a"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:be75e468a6a86426430373d81c041b7605137a28f7014a72d2fc749e47f572aa"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:967978ac2d4506255e2f52afe70dda023fc602b283e97685c8447d036863a302"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1231eacd4510f73222940727ac927bc5d07667a86b0cbe822024dd00343e77e9"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2c6d613b19e9a8021be2ee1d0e27710208d1603b56f47203d0abbde906929a9b"},
-    {file = "ruff-0.3.2-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c8439338a6303585d27b66b4626cbde89bb3e50fa3cae86ce52c1db7449330a7"},
-    {file = "ruff-0.3.2-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:de8b480d8379620cbb5ea466a9e53bb467d2fb07c7eca54a4aa8576483c35d36"},
-    {file = "ruff-0.3.2-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:b74c3de9103bd35df2bb05d8b2899bf2dbe4efda6474ea9681280648ec4d237d"},
-    {file = "ruff-0.3.2-py3-none-musllinux_1_2_i686.whl", hash = "sha256:f380be9fc15a99765c9cf316b40b9da1f6ad2ab9639e551703e581a5e6da6745"},
-    {file = "ruff-0.3.2-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:0ac06a3759c3ab9ef86bbeca665d31ad3aa9a4b1c17684aadb7e61c10baa0df4"},
-    {file = "ruff-0.3.2-py3-none-win32.whl", hash = "sha256:9bd640a8f7dd07a0b6901fcebccedadeb1a705a50350fb86b4003b805c81385a"},
-    {file = "ruff-0.3.2-py3-none-win_amd64.whl", hash = "sha256:0c1bdd9920cab5707c26c8b3bf33a064a4ca7842d91a99ec0634fec68f9f4037"},
-    {file = "ruff-0.3.2-py3-none-win_arm64.whl", hash = "sha256:5f65103b1d76e0d600cabd577b04179ff592064eaa451a70a81085930e907d0b"},
-    {file = "ruff-0.3.2.tar.gz", hash = "sha256:fa78ec9418eb1ca3db392811df3376b46471ae93792a81af2d1cbb0e5dcb5142"},
+    {file = "ruff-0.3.3-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:973a0e388b7bc2e9148c7f9be8b8c6ae7471b9be37e1cc732f8f44a6f6d7720d"},
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+    {file = "ruff-0.3.3-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:2700a804d5336bcffe063fd789ca2c7b02b552d2e323a336700abb8ae9e6a3f8"},
+    {file = "ruff-0.3.3-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:fd66469f1a18fdb9d32e22b79f486223052ddf057dc56dea0caaf1a47bdfaf4e"},
+    {file = "ruff-0.3.3-py3-none-musllinux_1_2_i686.whl", hash = "sha256:45817af234605525cdf6317005923bf532514e1ea3d9270acf61ca2440691376"},
+    {file = "ruff-0.3.3-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:0da458989ce0159555ef224d5b7c24d3d2e4bf4c300b85467b08c3261c6bc6a8"},
+    {file = "ruff-0.3.3-py3-none-win32.whl", hash = "sha256:f2831ec6a580a97f1ea82ea1eda0401c3cdf512cf2045fa3c85e8ef109e87de0"},
+    {file = "ruff-0.3.3-py3-none-win_amd64.whl", hash = "sha256:be90bcae57c24d9f9d023b12d627e958eb55f595428bafcb7fec0791ad25ddfc"},
+    {file = "ruff-0.3.3-py3-none-win_arm64.whl", hash = "sha256:0171aab5fecdc54383993389710a3d1227f2da124d76a2784a7098e818f92d61"},
+    {file = "ruff-0.3.3.tar.gz", hash = "sha256:38671be06f57a2f8aba957d9f701ea889aa5736be806f18c0cd03d6ff0cbca8d"},
 ]
 
 [[package]]

From 345c08691691f27710fefa30bf95067ae4000b72 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 18 Mar 2024 01:30:06 +0000
Subject: [PATCH 007/188] :arrow_up: Bump mkdocs-material from 9.5.13 to 9.5.14

Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 9.5.13 to 9.5.14.
- [Release notes](https://github.com/squidfunk/mkdocs-material/releases)
- [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG)
- [Commits](https://github.com/squidfunk/mkdocs-material/compare/9.5.13...9.5.14)

---
updated-dependencies:
- dependency-name: mkdocs-material
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index a0c7044d2..018756fca 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2183,13 +2183,13 @@ test = ["coverage[toml]", "pymdown-extensions", "pytest", "pytest-cov"]
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.13"
+version = "9.5.14"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.13-py3-none-any.whl", hash = "sha256:5cbe17fee4e3b4980c8420a04cc762d8dc052ef1e10532abd4fce88e5ea9ce6a"},
-    {file = "mkdocs_material-9.5.13.tar.gz", hash = "sha256:d8e4caae576312a88fd2609b81cf43d233cdbe36860d67a68702b018b425bd87"},
+    {file = "mkdocs_material-9.5.14-py3-none-any.whl", hash = "sha256:a45244ac221fda46ecf8337f00ec0e5cb5348ab9ffb203ca2a0c313b0d4dbc27"},
+    {file = "mkdocs_material-9.5.14.tar.gz", hash = "sha256:2a1f8e67cda2587ab93ecea9ba42d0ca61d1d7b5fad8cf690eeaeb39dcd4b9af"},
 ]
 
 [package.dependencies]

From 4abd128af5aa799ff7c047a2fd2bedb049ae769c Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 18 Mar 2024 17:48:56 +0000
Subject: [PATCH 008/188] =?UTF-8?q?chore(pre=5Fcommit):=20=E2=AC=86=20pre?=
 =?UTF-8?q?=5Fcommit=20autoupdate?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.3.2 → v0.3.3](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.2...v0.3.3)
---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index cd129b1e4..0d53b4f30 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -46,7 +46,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.3.2
+      rev: v0.3.3
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

From 0e3e41287a7a898ec8181f103da773e0d600357f Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Tue, 19 Mar 2024 16:25:38 +0300
Subject: [PATCH 009/188] =?UTF-8?q?ci:=20=F0=9F=91=B7=20publish=20pypi=20b?=
 =?UTF-8?q?ranch=20limitations=20added?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 .github/workflows/publish-test.yml | 2 ++
 .github/workflows/publish.yml      | 2 ++
 2 files changed, 4 insertions(+)

diff --git a/.github/workflows/publish-test.yml b/.github/workflows/publish-test.yml
index f5a562d24..a07af1d3f 100644
--- a/.github/workflows/publish-test.yml
+++ b/.github/workflows/publish-test.yml
@@ -5,6 +5,8 @@ on:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+a[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+b[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+rc[0-9]'
+    branches:
+      - develop
 
   # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
index b04e45380..bd748b061 100644
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@@ -3,6 +3,8 @@ on:
   push:
     tags:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]'
+    branches:
+      - main
 
   # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:

From 8a2abe72aead34443e16a8591102bf78b4987466 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 20 Mar 2024 19:37:03 +0100
Subject: [PATCH 010/188] utils refactor

---
 docs/draw/utils.md                            |  8 ++---
 .../count_people_in_zone/requirements.txt     |  2 +-
 examples/heatmap_and_track/requirements.txt   |  2 +-
 examples/speed_estimation/requirements.txt    |  2 +-
 examples/tracking/requirements.txt            |  2 +-
 examples/traffic_analysis/requirements.txt    |  2 +-
 supervision/__init__.py                       |  4 +--
 supervision/annotators/core.py                | 31 +++++++++++--------
 supervision/draw/utils.py                     | 24 +++++---------
 9 files changed, 37 insertions(+), 40 deletions(-)

diff --git a/docs/draw/utils.md b/docs/draw/utils.md
index ad3e1d6b7..7975952c3 100644
--- a/docs/draw/utils.md
+++ b/docs/draw/utils.md
@@ -41,13 +41,13 @@ comments: true
 :::supervision.draw.utils.draw_image
 
 <div class="md-typeset">
-  <h2>calculate_dynamic_font_scale</h2>
+  <h2>calculate_optimal_font_scale</h2>
 </div>
 
-:::supervision.draw.utils.calculate_dynamic_text_scale
+:::supervision.draw.utils.calculate_optimal_text_scale
 
 <div class="md-typeset">
-  <h2>calculate_dynamic_line_thickness</h2>
+  <h2>calculate_optimal_line_thickness</h2>
 </div>
 
-:::supervision.draw.utils.calculate_dynamic_line_thickness
+:::supervision.draw.utils.calculate_optimal_line_thickness
diff --git a/examples/count_people_in_zone/requirements.txt b/examples/count_people_in_zone/requirements.txt
index a8f583e8c..d9e272646 100644
--- a/examples/count_people_in_zone/requirements.txt
+++ b/examples/count_people_in_zone/requirements.txt
@@ -1,5 +1,5 @@
 gdown
 inference
-supervision
+supervision==0.19.0
 tqdm
 ultralytics
diff --git a/examples/heatmap_and_track/requirements.txt b/examples/heatmap_and_track/requirements.txt
index ffc73e1f2..27e5e57a8 100644
--- a/examples/heatmap_and_track/requirements.txt
+++ b/examples/heatmap_and_track/requirements.txt
@@ -1,2 +1,2 @@
-supervision[assets]
+supervision[assets]==0.19.0
 ultralytics
diff --git a/examples/speed_estimation/requirements.txt b/examples/speed_estimation/requirements.txt
index 59ca45cb3..36de970db 100644
--- a/examples/speed_estimation/requirements.txt
+++ b/examples/speed_estimation/requirements.txt
@@ -1,4 +1,4 @@
-supervision==0.18.0rc1
+supervision==0.19.0
 tqdm==4.66.1
 requests
 ultralytics==8.0.237
diff --git a/examples/tracking/requirements.txt b/examples/tracking/requirements.txt
index 80c28300d..8d5a9233a 100644
--- a/examples/tracking/requirements.txt
+++ b/examples/tracking/requirements.txt
@@ -1,4 +1,4 @@
 inference
-supervision
+supervision==0.19.0
 tqdm
 ultralytics
diff --git a/examples/traffic_analysis/requirements.txt b/examples/traffic_analysis/requirements.txt
index c56009a1e..6e72dd55e 100644
--- a/examples/traffic_analysis/requirements.txt
+++ b/examples/traffic_analysis/requirements.txt
@@ -1,5 +1,5 @@
 gdown
 inference
-supervision>=0.19.0rc5
+supervision>=0.19.0
 tqdm
 ultralytics
diff --git a/supervision/__init__.py b/supervision/__init__.py
index 4a102af5e..35f525b04 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -58,8 +58,8 @@
 )
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import (
-    calculate_dynamic_line_thickness,
-    calculate_dynamic_text_scale,
+    calculate_optimal_line_thickness,
+    calculate_optimal_text_scale,
     draw_filled_rectangle,
     draw_image,
     draw_line,
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index a96d91e1c..2be2562ee 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1851,9 +1851,9 @@ def __init__(
         self,
         position: Position = Position.TOP_CENTER,
         scale_factor: int = 2,
-        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
-        thickness: int = 2,
-        color_lookup: ColorLookup = ColorLookup.CLASS,
+        border_color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
+        border_thickness: int = 2,
+        border_color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
         """
         Args:
@@ -1862,12 +1862,17 @@ def __init__(
             scale_factor (int): The factor by which to scale the cropped image part. A
                 factor of 2, for example, would double the size of the cropped area,
                 allowing for a closer view of the detection.
+            border_color (Union[Color, ColorPalette]): The color or color palette to
+                use for annotating border around the cropped area.
+            border_thickness (int): The thickness of the border around the cropped area.
+            border_color_lookup (ColorLookup): Strategy for mapping colors to
+                annotations. Options are `INDEX`, `CLASS`, `TRACK`.
         """
         self.position: Position = position
         self.scale_factor: int = scale_factor
-        self.color: Union[Color, ColorPalette] = color
-        self.thickness: int = thickness
-        self.color_lookup: ColorLookup = color_lookup
+        self.border_color: Union[Color, ColorPalette] = border_color
+        self.border_thickness: int = border_thickness
+        self.border_color_lookup: ColorLookup = border_color_lookup
 
     @scene_to_annotator_img_type
     def annotate(
@@ -1923,10 +1928,10 @@ def annotate(
             )
             scene = place_image(scene=scene, image=resized_crop, anchor=(x1, y1))
             color = resolve_color(
-                color=self.color,
+                color=self.border_color,
                 detections=detections,
                 detection_idx=idx,
-                color_lookup=self.color_lookup
+                color_lookup=self.border_color_lookup
                 if custom_color_lookup is None
                 else custom_color_lookup,
             )
@@ -1935,7 +1940,7 @@ def annotate(
                 pt1=(x1, y1),
                 pt2=(x2, y2),
                 color=color.as_bgr(),
-                thickness=self.thickness,
+                thickness=self.border_thickness,
             )
 
         return scene
@@ -1948,14 +1953,14 @@ def calculate_crop_coordinates(
         width, height = crop_wh
 
         if position == Position.TOP_LEFT:
-            return ((anchor_x - width, anchor_y - height), (anchor_x, anchor_y))
+            return (anchor_x - width, anchor_y - height), (anchor_x, anchor_y)
         elif position == Position.TOP_CENTER:
             return (
                 (anchor_x - width // 2, anchor_y - height),
                 (anchor_x + width // 2, anchor_y),
             )
         elif position == Position.TOP_RIGHT:
-            return ((anchor_x, anchor_y - height), (anchor_x + width, anchor_y))
+            return (anchor_x, anchor_y - height), (anchor_x + width, anchor_y)
         elif position == Position.CENTER_LEFT:
             return (
                 (anchor_x - width, anchor_y - height // 2),
@@ -1972,11 +1977,11 @@ def calculate_crop_coordinates(
                 (anchor_x + width, anchor_y + height // 2),
             )
         elif position == Position.BOTTOM_LEFT:
-            return ((anchor_x - width, anchor_y), (anchor_x, anchor_y + height))
+            return (anchor_x - width, anchor_y), (anchor_x, anchor_y + height)
         elif position == Position.BOTTOM_CENTER:
             return (
                 (anchor_x - width // 2, anchor_y),
                 (anchor_x + width // 2, anchor_y + height),
             )
         elif position == Position.BOTTOM_RIGHT:
-            return ((anchor_x, anchor_y), (anchor_x + width, anchor_y + height))
+            return (anchor_x, anchor_y), (anchor_x + width, anchor_y + height)
diff --git a/supervision/draw/utils.py b/supervision/draw/utils.py
index 7f82b0088..638e6b750 100644
--- a/supervision/draw/utils.py
+++ b/supervision/draw/utils.py
@@ -238,13 +238,13 @@ def draw_image(
     return scene
 
 
-def calculate_dynamic_text_scale(resolution_wh: Tuple[int, int]) -> float:
+def calculate_optimal_text_scale(resolution_wh: Tuple[int, int]) -> float:
     """
-    Calculate a dynamic font scale based on the resolution of an image.
+    Calculate font scale based on the resolution of an image.
 
     Parameters:
          resolution_wh (Tuple[int, int]): A tuple representing the width and height
-                 of the image.
+             of the image.
 
     Returns:
          float: The calculated font scale factor.
@@ -252,25 +252,17 @@ def calculate_dynamic_text_scale(resolution_wh: Tuple[int, int]) -> float:
     return min(resolution_wh) * 1e-3
 
 
-def calculate_dynamic_line_thickness(resolution_wh: Tuple[int, int]) -> int:
+def calculate_optimal_line_thickness(resolution_wh: Tuple[int, int]) -> int:
     """
-    Calculate a dynamic line thickness based on the resolution of an image.
+    Calculate line thickness based on the resolution of an image.
 
     Parameters:
         resolution_wh (Tuple[int, int]): A tuple representing the width and height
-                of the image.
+            of the image.
 
     Returns:
         int: The calculated line thickness in pixels.
     """
-    min_dimension = min(resolution_wh)
-    if min_dimension < 480:
+    if min(resolution_wh) < 1080:
         return 2
-    if min_dimension < 720:
-        return 2
-    if min_dimension < 1080:
-        return 2
-    if min_dimension < 2160:
-        return 4
-    else:
-        return 4
+    return 4

From 7eba3382432c1bc98a30b66b3d65ce72ebb603bd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Wed, 20 Mar 2024 23:08:39 +0100
Subject: [PATCH 011/188] Add first draft of implementation for function
 creating image tiles

---
 .pre-commit-config.yaml         |   1 -
 supervision/annotators/utils.py |  12 +-
 supervision/utils/image.py      | 346 +++++++++++++++++++++++++++++++-
 supervision/utils/iterables.py  |  17 ++
 supervision/utils/notebook.py   |   2 +-
 5 files changed, 365 insertions(+), 13 deletions(-)
 create mode 100644 supervision/utils/iterables.py

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 0d53b4f30..7569e6b4b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -27,7 +27,6 @@ repos:
       - id: mixed-line-ending
 
 
-
   -   repo: https://github.com/PyCQA/bandit
       rev: '1.7.8'
       hooks:
diff --git a/supervision/annotators/utils.py b/supervision/annotators/utils.py
index 6f9cd9db2..0a7586a4d 100644
--- a/supervision/annotators/utils.py
+++ b/supervision/annotators/utils.py
@@ -2,7 +2,6 @@
 from functools import wraps
 from typing import Optional, Union
 
-import cv2
 import numpy as np
 from PIL import Image
 
@@ -10,6 +9,7 @@
 from supervision.detection.core import Detections
 from supervision.draw.color import Color, ColorPalette
 from supervision.geometry.core import Position
+from supervision.utils.image import cv2_to_pillow, pillow_to_cv2
 
 
 class ColorLookup(Enum):
@@ -125,12 +125,6 @@ def get(self, tracker_id: int) -> np.ndarray:
         return self.xy[self.tracker_id == tracker_id]
 
 
-def pillow_to_cv2(image: Image.Image) -> np.ndarray:
-    scene = np.array(image)
-    scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
-    return scene
-
-
 def scene_to_annotator_img_type(annotate_func):
     """
     Decorates `BaseAnnotator.annotate` implementations, converts scene to
@@ -146,9 +140,7 @@ def wrapper(self, scene: ImageType, *args, **kwargs):
         if isinstance(scene, Image.Image):
             scene = pillow_to_cv2(scene)
             annotated = annotate_func(self, scene, *args, **kwargs)
-            annotated = cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
-            annotated = Image.fromarray(annotated)
-            return annotated
+            return cv2_to_pillow(image=annotated)
 
         raise ValueError(f"Unsupported image type: {type(scene)}")
 
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 4b9372ee2..39787ca48 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -1,11 +1,43 @@
+import itertools
+import math
 import os
 import shutil
-from typing import Optional, Tuple
+from functools import partial, wraps
+from typing import Callable, List, Literal, Optional, Tuple, Union
 
 import cv2
 import numpy as np
+from PIL import Image
 
+from supervision.annotators.base import ImageType
+from supervision.draw.color import Color
+from supervision.utils.iterables import create_batches
 
+MAX_COLUMNS_FOR_SINGLE_ROW_GRID = 3
+
+
+def adjust_image_to_cv2_processing(image_processing_fun):
+    """
+    Decorates image processing functions that accept np.ndarray, converting `image` to
+    np.ndarray, converts back when processing is complete.
+    """
+
+    @wraps(image_processing_fun)
+    def wrapper(image: ImageType, *args, **kwargs):
+        if isinstance(image, np.ndarray):
+            return image_processing_fun(image, *args, **kwargs)
+
+        if isinstance(image, Image.Image):
+            scene = pillow_to_cv2(image)
+            annotated = image_processing_fun(scene, *args, **kwargs)
+            return cv2_to_pillow(image=annotated)
+
+        raise ValueError(f"Unsupported image type: {type(image)}")
+
+    return wrapper
+
+
+@adjust_image_to_cv2_processing
 def crop_image(image: np.ndarray, xyxy: np.ndarray) -> np.ndarray:
     """
     Crops the given image based on the given bounding box.
@@ -35,6 +67,7 @@ def crop_image(image: np.ndarray, xyxy: np.ndarray) -> np.ndarray:
     return image[y1:y2, x1:x2]
 
 
+@adjust_image_to_cv2_processing
 def resize_image(image: np.ndarray, scale_factor: float) -> np.ndarray:
     """
     Resizes an image by a given scale factor using cv2.INTER_LINEAR interpolation.
@@ -167,3 +200,314 @@ def save_image(self, image: np.ndarray, image_name: Optional[str] = None):
 
     def __exit__(self, exc_type, exc_value, exc_traceback):
         pass
+
+
+def create_tiles(
+    images: List[ImageType],
+    grid_size: Optional[Tuple[Optional[int], Optional[int]]] = None,
+    single_tile_size: Optional[Tuple[int, int]] = None,
+    tile_scaling: Literal["min", "max", "avg"] = "avg",
+    tile_padding_color: Union[Tuple[int, int, int], Color] = Color.WHITE,
+    tile_margin: int = 15,
+    tile_margin_color: Union[Tuple[int, int, int], Color] = Color.BLACK,
+    return_type: Literal["auto", "cv2", "pillow"] = "auto",
+) -> ImageType:
+    """
+    Creates tiles mosaic from input images, automating grid placement and
+    converting images to common resolution maintaining aspect ratio.
+
+    Automated grid placement will try to maintain square shape of grid
+    (with size being the nearest integer square root of #images), up to two exceptions:
+    * if there are up to 3 images - images will be displayed in single row
+    * if square-grid placement causes last row to be empty - number of rows is trimmed
+        until last row has at least one image
+
+    Args:
+        images (List[ImageType]): Images to create tiles. Elements can be either
+            np.ndarray or PIL.Image, common representation will be agreed by the
+            function.
+        grid_size (Optional[Tuple[Optional[int], Optional[int]]]): Expected grid
+            size in format (n_rows, n_cols). If not given - automated grid placement
+            will be applied. One may also provide only one out of two elements of the
+            tuple - then grid will be created with either n_rows or n_cols fixed,
+            leaving the other dimension to be adjusted by the number of images
+        single_tile_size (Optional[Tuple[int, int]]): sizeof a single tile element
+            provided in (width, height) format. If not given - size of tile will be
+            automatically calculated based on `tile_scaling` parameter.
+        tile_scaling (Literal["min", "max", "avg"]): If `single_tile_size` is not
+            given - parameter will be used to calculate tile size - using
+            min / max / avg size of image provided in `images` list.
+        tile_padding_color (Union[Tuple[int, int, int], sv.Color]): Color to be used in
+            images letterbox procedure (while standardising tiles sizes) as a padding.
+            If tuple provided - should be BGR.
+        tile_margin (int): size of margin between tiles (in pixels)
+        tile_margin_color (Union[Tuple[int, int, int], sv.Color]): Color of tile margin.
+            If tuple provided - should be BGR.
+        return_type (Literal["auto", "cv2", "pillow"]): Parameter dictates the format of
+            return image. One may choose specific type ("cv2" or "pillow") to enforce
+            conversion. "auto" mode takes a majority vote between types of elements in
+            `images` list - resolving draws in favour of OpenCV format. "auto" can be
+            safely used when all input images are of the same type.
+
+    Returns:
+        ImageType: Image with all input images located in tails grid. The output type is
+            determined by `return_type` parameter.
+
+    Raises:
+        ValueError: In case when input images list is empty, provided `grid_size` is too
+            small to fit all images, `tile_scaling` mode is invalid.
+    """
+    if len(images) == 0:
+        raise ValueError("Could not create image tiles from empty list of images.")
+    if return_type == "auto":
+        return_type = _negotiate_tiles_format(images=images)
+    tile_padding_color = _color_to_bgr(color=tile_padding_color)
+    tile_margin_color = _color_to_bgr(color=tile_margin_color)
+    images = images_to_cv2(images=images)
+    if single_tile_size is None:
+        single_tile_size = _aggregate_images_shape(images=images, mode=tile_scaling)
+    resized_images = [
+        letterbox_image(
+            image=i, desired_size=single_tile_size, color=tile_padding_color
+        )
+        for i in images
+    ]
+    grid_size = _establish_grid_size(images=images, grid_size=grid_size)
+    if len(images) > grid_size[0] * grid_size[1]:
+        raise ValueError(
+            f"Could not place {len(images)} in grid with size: {grid_size}."
+        )
+    tiles = _generate_tiles(
+        images=resized_images,
+        grid_size=grid_size,
+        single_tile_size=single_tile_size,
+        tile_padding_color=tile_padding_color,
+        tile_margin=tile_margin,
+        tile_margin_color=tile_margin_color,
+    )
+    if return_type == "pillow":
+        tiles = cv2_to_pillow(image=tiles)
+    return tiles
+
+
+def _negotiate_tiles_format(images: List[ImageType]) -> Literal["cv2", "pillow"]:
+    number_of_np_arrays = sum(issubclass(type(i), np.ndarray) for i in images)
+    if number_of_np_arrays >= (len(images) // 2):
+        return "cv2"
+    return "pillow"
+
+
+def _calculate_aggregated_images_shape(
+    images: List[np.ndarray], aggregator: Callable[[List[int]], float]
+) -> Tuple[int, int]:
+    height = round(aggregator([i.shape[0] for i in images]))
+    width = round(aggregator([i.shape[1] for i in images]))
+    return width, height
+
+
+SHAPE_AGGREGATION_FUN = {
+    "min": partial(_calculate_aggregated_images_shape, aggregator=np.min),
+    "max": partial(_calculate_aggregated_images_shape, aggregator=np.max),
+    "avg": partial(_calculate_aggregated_images_shape, aggregator=np.average),
+}
+
+
+def _aggregate_images_shape(
+    images: List[np.ndarray], mode: Literal["min", "max", "avg"]
+) -> Tuple[int, int]:
+    if mode not in SHAPE_AGGREGATION_FUN:
+        raise ValueError(
+            f"Could not aggregate images shape - provided unknown mode: {mode}. "
+            f"Supported modes: {list(SHAPE_AGGREGATION_FUN.keys())}."
+        )
+    return SHAPE_AGGREGATION_FUN[mode](images)
+
+
+def _establish_grid_size(
+    images: List[np.ndarray], grid_size: Optional[Tuple[Optional[int], Optional[int]]]
+) -> Tuple[int, int]:
+    if grid_size is None or all(e is None for e in grid_size):
+        return _negotiate_grid_size(images=images)
+    if grid_size[0] is None:
+        return math.ceil(len(images) / grid_size[1]), grid_size[1]
+    return grid_size[0], math.ceil(len(images) / grid_size[0])
+
+
+def _negotiate_grid_size(images: List[np.ndarray]) -> Tuple[int, int]:
+    if len(images) <= MAX_COLUMNS_FOR_SINGLE_ROW_GRID:
+        return 1, len(images)
+    nearest_sqrt = math.ceil(np.sqrt(len(images)))
+    proposed_columns = nearest_sqrt
+    proposed_rows = nearest_sqrt
+    while proposed_columns * (proposed_rows - 1) >= len(images):
+        proposed_rows -= 1
+    return proposed_rows, proposed_columns
+
+
+def _generate_tiles(
+    images: List[np.ndarray],
+    grid_size: Tuple[int, int],
+    single_tile_size: Tuple[int, int],
+    tile_padding_color: Tuple[int, int, int],
+    tile_margin: int,
+    tile_margin_color: Tuple[int, int, int],
+) -> np.ndarray:
+    rows, columns = grid_size
+    tiles_elements = list(create_batches(sequence=images, batch_size=columns))
+    while len(tiles_elements[-1]) < columns:
+        tiles_elements[-1].append(
+            _generate_color_image(shape=single_tile_size, color=tile_padding_color)
+        )
+    while len(tiles_elements) < rows:
+        tiles_elements.append(
+            [_generate_color_image(shape=single_tile_size, color=tile_padding_color)]
+            * columns
+        )
+    return _merge_tiles_elements(
+        tiles_elements=tiles_elements,
+        grid_size=grid_size,
+        single_tile_size=single_tile_size,
+        tile_margin=tile_margin,
+        tile_margin_color=tile_margin_color,
+    )
+
+
+def _merge_tiles_elements(
+    tiles_elements: List[List[np.ndarray]],
+    grid_size: Tuple[int, int],
+    single_tile_size: Tuple[int, int],
+    tile_margin: int,
+    tile_margin_color: Tuple[int, int, int],
+) -> np.ndarray:
+    vertical_padding = (
+        np.ones((single_tile_size[1], tile_margin, 3)) * tile_margin_color
+    )
+    merged_rows = [
+        np.concatenate(
+            list(
+                itertools.chain.from_iterable(
+                    zip(row, [vertical_padding] * grid_size[1])
+                )
+            )[:-1],
+            axis=1,
+        )
+        for row in tiles_elements
+    ]
+    row_width = merged_rows[0].shape[1]
+    horizontal_padding = (
+        np.ones((tile_margin, row_width, 3), dtype=np.uint8) * tile_margin_color
+    )
+    rows_with_paddings = []
+    for row in merged_rows:
+        rows_with_paddings.append(row)
+        rows_with_paddings.append(horizontal_padding)
+    return np.concatenate(
+        rows_with_paddings[:-1],
+        axis=0,
+    ).astype(np.uint8)
+
+
+def _generate_color_image(
+    shape: Tuple[int, int], color: Tuple[int, int, int]
+) -> np.ndarray:
+    return np.ones(shape[::-1] + (3,), dtype=np.uint8) * color
+
+
+@adjust_image_to_cv2_processing
+def letterbox_image(
+    image: np.ndarray,
+    desired_size: Tuple[int, int],
+    color: Union[Tuple[int, int, int], Color] = (0, 0, 0),
+) -> np.ndarray:
+    """
+    Resize and pad image to fit the desired size, preserving its aspect
+    ratio, adding padding of given color if needed to maintain aspect ratio.
+
+    Parameters:
+    - image (np.ndarray): Input image (type will be adjusted by decorator,
+        you can provide PIL.Image)
+    - desired_size (Tuple[int, int]): image size (width, height) representing
+        the target dimensions.
+    - color (Union[Tuple[int, int, int], Color]): the color to pad with - If
+        tuple provided - should be BGR.
+
+    Returns:
+        np.ndarray: letterboxed image (type may be adjusted to PIL.Image by
+            decorator if function was called with PIL.Image)
+    """
+    color = _color_to_bgr(color=color)
+    resized_img = resize_image_keeping_aspect_ratio(
+        image=image,
+        desired_size=desired_size,
+    )
+    new_height, new_width = resized_img.shape[:2]
+    top_padding = (desired_size[1] - new_height) // 2
+    bottom_padding = desired_size[1] - new_height - top_padding
+    left_padding = (desired_size[0] - new_width) // 2
+    right_padding = desired_size[0] - new_width - left_padding
+    return cv2.copyMakeBorder(
+        resized_img,
+        top_padding,
+        bottom_padding,
+        left_padding,
+        right_padding,
+        cv2.BORDER_CONSTANT,
+        value=color,
+    )
+
+
+@adjust_image_to_cv2_processing
+def resize_image_keeping_aspect_ratio(
+    image: np.ndarray,
+    desired_size: Tuple[int, int],
+) -> np.ndarray:
+    """
+    Resize and pad image preserving its aspect ratio.
+
+    Parameters:
+    - image (np.ndarray): Input image (type will be adjusted by decorator,
+        you can provide PIL.Image)
+    - desired_size (Tuple[int, int]): image size (width, height) representing the
+        target dimensions. Parameter will be used to dictate maximum size of
+        output image. Output size may be smaller - to preserve aspect ratio of original
+        image.
+
+    Returns:
+        np.ndarray: resized image (type may be adjusted to PIL.Image by decorator
+            if function was called with PIL.Image)
+    """
+    img_ratio = image.shape[1] / image.shape[0]
+    desired_ratio = desired_size[0] / desired_size[1]
+    if img_ratio >= desired_ratio:
+        new_width = desired_size[0]
+        new_height = int(desired_size[0] / img_ratio)
+    else:
+        new_height = desired_size[1]
+        new_width = int(desired_size[1] * img_ratio)
+    return cv2.resize(image, (new_width, new_height))
+
+
+def _color_to_bgr(color: Union[Tuple[int, int, int], Color]) -> Tuple[int, int, int]:
+    if issubclass(type(color), Color):
+        return color.as_bgr()
+    return color
+
+
+def images_to_cv2(images: List[ImageType]) -> List[np.ndarray]:
+    result = []
+    for image in images:
+        if issubclass(type(image), Image.Image):
+            image = pillow_to_cv2(image=image)
+        result.append(image)
+    return result
+
+
+def pillow_to_cv2(image: Image.Image) -> np.ndarray:
+    scene = np.array(image)
+    scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
+    return scene
+
+
+def cv2_to_pillow(image: np.ndarray) -> Image.Image:
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    return Image.fromarray(image)
diff --git a/supervision/utils/iterables.py b/supervision/utils/iterables.py
new file mode 100644
index 000000000..85684661b
--- /dev/null
+++ b/supervision/utils/iterables.py
@@ -0,0 +1,17 @@
+from typing import Generator, Iterable, List, TypeVar
+
+SequenceElement = TypeVar("SequenceElement")
+
+
+def create_batches(
+    sequence: Iterable[SequenceElement], batch_size: int
+) -> Generator[List[SequenceElement], None, None]:
+    batch_size = max(batch_size, 1)
+    current_batch = []
+    for element in sequence:
+        if len(current_batch) == batch_size:
+            yield current_batch
+            current_batch = []
+        current_batch.append(element)
+    if len(current_batch) > 0:
+        yield current_batch
diff --git a/supervision/utils/notebook.py b/supervision/utils/notebook.py
index 159f3c17c..346064ac3 100644
--- a/supervision/utils/notebook.py
+++ b/supervision/utils/notebook.py
@@ -5,7 +5,7 @@
 from PIL import Image
 
 from supervision.annotators.base import ImageType
-from supervision.annotators.utils import pillow_to_cv2
+from supervision.utils.image import pillow_to_cv2
 
 
 def plot_image(

From f377a992e15cbc54db35b72e8063f9639d6a4d16 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 22 Mar 2024 00:52:54 +0000
Subject: [PATCH 012/188] :arrow_up: Bump nbconvert from 7.16.2 to 7.16.3

Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 7.16.2 to 7.16.3.
- [Release notes](https://github.com/jupyter/nbconvert/releases)
- [Changelog](https://github.com/jupyter/nbconvert/blob/main/CHANGELOG.md)
- [Commits](https://github.com/jupyter/nbconvert/compare/v7.16.2...v7.16.3)

---
updated-dependencies:
- dependency-name: nbconvert
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 9b32eece1..9478a950f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2360,13 +2360,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.16.2"
+version = "7.16.3"
 description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "nbconvert-7.16.2-py3-none-any.whl", hash = "sha256:0c01c23981a8de0220255706822c40b751438e32467d6a686e26be08ba784382"},
-    {file = "nbconvert-7.16.2.tar.gz", hash = "sha256:8310edd41e1c43947e4ecf16614c61469ebc024898eb808cce0999860fc9fb16"},
+    {file = "nbconvert-7.16.3-py3-none-any.whl", hash = "sha256:ddeff14beeeedf3dd0bc506623e41e4507e551736de59df69a91f86700292b3b"},
+    {file = "nbconvert-7.16.3.tar.gz", hash = "sha256:a6733b78ce3d47c3f85e504998495b07e6ea9cf9bf6ec1c98dda63ec6ad19142"},
 ]
 
 [package.dependencies]
@@ -2393,7 +2393,7 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
 webpdf = ["playwright"]
 
 [[package]]

From 70218b85e7e7d707961443575bb2f6dbeadc78d1 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 22 Mar 2024 01:05:54 +0000
Subject: [PATCH 013/188] :arrow_up: Bump ruff from 0.3.3 to 0.3.4

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.3.3 to 0.3.4.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.3.3...v0.3.4)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 9b32eece1..8e5223284 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3645,28 +3645,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.3.3"
+version = "0.3.4"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "ruff-0.3.3-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:cfa60d23269d6e2031129b053fdb4e5a7b0637fc6c9c0586737b962b2f834493"},
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+    {file = "ruff-0.3.4-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:cf187a7e7098233d0d0c71175375c5162f880126c4c716fa28a8ac418dcf3378"},
+    {file = "ruff-0.3.4-py3-none-win32.whl", hash = "sha256:af27ac187c0a331e8ef91d84bf1c3c6a5dea97e912a7560ac0cef25c526a4102"},
+    {file = "ruff-0.3.4-py3-none-win_amd64.whl", hash = "sha256:de0d5069b165e5a32b3c6ffbb81c350b1e3d3483347196ffdf86dc0ef9e37dd6"},
+    {file = "ruff-0.3.4-py3-none-win_arm64.whl", hash = "sha256:6810563cc08ad0096b57c717bd78aeac888a1bfd38654d9113cb3dc4d3f74232"},
+    {file = "ruff-0.3.4.tar.gz", hash = "sha256:f0f4484c6541a99862b693e13a151435a279b271cff20e37101116a21e2a1ad1"},
 ]
 
 [[package]]

From 1eb877c4d924ce620bf5acbdf7ce46bfb7e8f917 Mon Sep 17 00:00:00 2001
From: Raif Olson <raif.t.olson.24@dartmouth.edu>
Date: Sat, 23 Mar 2024 18:53:05 -0500
Subject: [PATCH 014/188] Fix issue #754

---
 supervision/tracker/byte_tracker/core.py | 45 ++++++++++++++----------
 1 file changed, 27 insertions(+), 18 deletions(-)

diff --git a/supervision/tracker/byte_tracker/core.py b/supervision/tracker/byte_tracker/core.py
index 89494ee6a..9156fb581 100644
--- a/supervision/tracker/byte_tracker/core.py
+++ b/supervision/tracker/byte_tracker/core.py
@@ -3,6 +3,7 @@
 import numpy as np
 
 from supervision.detection.core import Detections
+from supervision.detection.utils import box_iou_batch
 from supervision.tracker.byte_tracker import matching
 from supervision.tracker.byte_tracker.basetrack import BaseTrack, TrackState
 from supervision.tracker.byte_tracker.kalman_filter import KalmanFilter
@@ -270,27 +271,35 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
             ```
         """
 
-        tracks = self.update_with_tensors(
-            tensors=detections2boxes(detections=detections)
-        )
-        detections = Detections.empty()
+        tensors = detections2boxes(detections=detections)
+
+        tracks = self.update_with_tensors(tensors=tensors)
+
+        final_detections = Detections.empty()
+
         if len(tracks) > 0:
-            detections.xyxy = np.array(
-                [track.tlbr for track in tracks], dtype=np.float32
-            )
-            detections.class_id = np.array(
-                [int(t.class_ids) for t in tracks], dtype=int
-            )
-            detections.tracker_id = np.array(
-                [int(t.track_id) for t in tracks], dtype=int
-            )
-            detections.confidence = np.array(
-                [t.score for t in tracks], dtype=np.float32
-            )
+            detection_bounding_boxes = np.asarray([det[:4] for det in tensors])
+            track_bounding_boxes = np.asarray([track.tlbr for track in tracks])
+
+            ious = box_iou_batch(detection_bounding_boxes, track_bounding_boxes)
+
+            iou_costs = 1 - ious
+
+            matches, _, _ = matching.linear_assignment(iou_costs, 0.5)
+            for i, idet, itrack in enumerate(matches):
+                if i == 0:
+                    final_detections = detections[[idet]]
+                    final_detections.tracker_id[0] = int(tracks[itrack].track_id)
+                else:
+                    current_detection = detections[[idet]]
+                    current_detection.tracker_id[0] = int(tracks[itrack].track_id)
+                    final_detections = Detections.merge(
+                        [final_detections, current_detection]
+                    )
         else:
-            detections.tracker_id = np.array([], dtype=int)
+            final_detections.tracker_id = np.array([], dtype=int)
 
-        return detections
+        return final_detections
 
     def reset(self):
         """

From 1fbdec6046113493d5cd44083881b30a77ae4a9d Mon Sep 17 00:00:00 2001
From: Christoforos Aristeidou <aristeidouxristos@gmail.com>
Date: Sun, 24 Mar 2024 11:35:18 +0200
Subject: [PATCH 015/188] added `corner_radius` attribute to `LabelAnnotator`

---
 supervision/annotators/core.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 2be2562ee..7dc8ab4fc 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -907,6 +907,7 @@ class LabelAnnotator:
 
     def __init__(
         self,
+        corner_radius: int = 15,
         color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         text_color: Color = Color.WHITE,
         text_scale: float = 0.5,
@@ -917,6 +918,8 @@ def __init__(
     ):
         """
         Args:
+            corner_radius (int): The radius to apply round edges. If the selected
+                value is higher than the lower dimension, width or height, is clipped.
             color (Union[Color, ColorPalette]): The color or color palette to use for
                 annotating the text background.
             text_color (Color): The color to use for the text.
@@ -928,6 +931,7 @@ def __init__(
             color_lookup (str): Strategy for mapping colors to annotations.
                 Options are `INDEX`, `CLASS`, `TRACK`.
         """
+        self.corner_radius: int = corner_radius
         self.color: Union[Color, ColorPalette] = color
         self.text_color: Color = text_color
         self.text_scale: float = text_scale

From 3e4ddd5bd9e2f37efee41a570858941bd2f1dd0c Mon Sep 17 00:00:00 2001
From: Christoforos Aristeidou <aristeidouxristos@gmail.com>
Date: Sun, 24 Mar 2024 11:36:10 +0200
Subject: [PATCH 016/188] added new custom method that draws rounded rectangles

---
 supervision/annotators/core.py | 43 ++++++++++++++++++++++++++++++++++
 1 file changed, 43 insertions(+)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 7dc8ab4fc..c137a8d4b 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1103,6 +1103,49 @@ def annotate(
             )
         return scene
 
+    @staticmethod
+    def draw_rounded_rectangle(
+        img: ImageType, pt1: Tuple[int, int], pt2: Tuple[int, int],
+        color: Tuple[int, int, int], thickness: int, corner_radius: int
+    ) -> ImageType:
+        x1, y1 = pt1
+        x2, y2 = pt2
+        
+        width = x2 - x1
+        height = y2 - y1
+        
+        max_corner_radius = min(width, height) // 2
+        
+        corner_radius = min(corner_radius, max_corner_radius)
+        
+        rectangle_coords = [
+            ((x1 + corner_radius, y1), (x2 - corner_radius, y2)),
+            ((x1, y1 + corner_radius),(x2, y2 - corner_radius))
+        ]
+        circle_centers = [
+            (x1 + corner_radius, y1 + corner_radius),
+            (x2 - corner_radius, y1 + corner_radius),
+            (x1 + corner_radius, y2 - corner_radius),
+            (x2 - corner_radius, y2 - corner_radius),
+        ]
+
+        for coords in rectangle_coords:
+            cv2.rectangle(
+                img=img,
+                pt1=coords[0],
+                pt2=coords[1],
+                color=color,
+                thickness=thickness 
+            )
+        for center in circle_centers:
+            cv2.circle(
+                img=img,
+                center=center,
+                radius=corner_radius,
+                color=color,
+                thickness=thickness
+            )
+
 
 class BlurAnnotator(BaseAnnotator):
     """

From ed3c73eb02afc6d2685b87d83b4ab8b73eff9dc8 Mon Sep 17 00:00:00 2001
From: Christoforos Aristeidou <aristeidouxristos@gmail.com>
Date: Sun, 24 Mar 2024 11:36:51 +0200
Subject: [PATCH 017/188] modified to use new custom method for rectangle
 drawing

---
 supervision/annotators/core.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index c137a8d4b..22506d2b9 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1084,12 +1084,13 @@ def annotate(
             text_x = text_background_xyxy[0] + self.text_padding
             text_y = text_background_xyxy[1] + self.text_padding + text_h
 
-            cv2.rectangle(
+            self.draw_rounded_rectangle(
                 img=scene,
                 pt1=(text_background_xyxy[0], text_background_xyxy[1]),
                 pt2=(text_background_xyxy[2], text_background_xyxy[3]),
                 color=color.as_bgr(),
                 thickness=cv2.FILLED,
+                corner_radius=self.corner_radius
             )
             cv2.putText(
                 img=scene,

From 957ced06147bcc8c44a314bd8a2926352188dd55 Mon Sep 17 00:00:00 2001
From: Christoforos Aristeidou <aristeidouxristos@gmail.com>
Date: Sun, 24 Mar 2024 11:42:19 +0200
Subject: [PATCH 018/188] (pre-commit): align spacing

---
 supervision/annotators/core.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 22506d2b9..15da147d5 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1090,7 +1090,7 @@ def annotate(
                 pt2=(text_background_xyxy[2], text_background_xyxy[3]),
                 color=color.as_bgr(),
                 thickness=cv2.FILLED,
-                corner_radius=self.corner_radius
+                corner_radius=self.corner_radius,
             )
             cv2.putText(
                 img=scene,
@@ -1106,22 +1106,26 @@ def annotate(
 
     @staticmethod
     def draw_rounded_rectangle(
-        img: ImageType, pt1: Tuple[int, int], pt2: Tuple[int, int],
-        color: Tuple[int, int, int], thickness: int, corner_radius: int
+        img: ImageType,
+        pt1: Tuple[int, int],
+        pt2: Tuple[int, int],
+        color: Tuple[int, int, int],
+        thickness: int,
+        corner_radius: int,
     ) -> ImageType:
         x1, y1 = pt1
         x2, y2 = pt2
-        
+
         width = x2 - x1
         height = y2 - y1
-        
+
         max_corner_radius = min(width, height) // 2
-        
+
         corner_radius = min(corner_radius, max_corner_radius)
-        
+
         rectangle_coords = [
             ((x1 + corner_radius, y1), (x2 - corner_radius, y2)),
-            ((x1, y1 + corner_radius),(x2, y2 - corner_radius))
+            ((x1, y1 + corner_radius), (x2, y2 - corner_radius)),
         ]
         circle_centers = [
             (x1 + corner_radius, y1 + corner_radius),
@@ -1132,11 +1136,7 @@ def draw_rounded_rectangle(
 
         for coords in rectangle_coords:
             cv2.rectangle(
-                img=img,
-                pt1=coords[0],
-                pt2=coords[1],
-                color=color,
-                thickness=thickness 
+                img=img, pt1=coords[0], pt2=coords[1], color=color, thickness=thickness
             )
         for center in circle_centers:
             cv2.circle(
@@ -1144,7 +1144,7 @@ def draw_rounded_rectangle(
                 center=center,
                 radius=corner_radius,
                 color=color,
-                thickness=thickness
+                thickness=thickness,
             )
 
 

From 6458d4454d2b6b2c6b37740d6a218b466134bfc5 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 01:07:38 +0000
Subject: [PATCH 019/188] :arrow_up: Bump mkdocs-material from 9.5.14 to 9.5.15

Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 9.5.14 to 9.5.15.
- [Release notes](https://github.com/squidfunk/mkdocs-material/releases)
- [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG)
- [Commits](https://github.com/squidfunk/mkdocs-material/compare/9.5.14...9.5.15)

---
updated-dependencies:
- dependency-name: mkdocs-material
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 2ec7f6529..304b28059 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2183,13 +2183,13 @@ test = ["coverage[toml]", "pymdown-extensions", "pytest", "pytest-cov"]
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.14"
+version = "9.5.15"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.14-py3-none-any.whl", hash = "sha256:a45244ac221fda46ecf8337f00ec0e5cb5348ab9ffb203ca2a0c313b0d4dbc27"},
-    {file = "mkdocs_material-9.5.14.tar.gz", hash = "sha256:2a1f8e67cda2587ab93ecea9ba42d0ca61d1d7b5fad8cf690eeaeb39dcd4b9af"},
+    {file = "mkdocs_material-9.5.15-py3-none-any.whl", hash = "sha256:e5c96dec3d19491de49ca643fc1dbb92b278e43cdb816c775bc47db77d9b62fb"},
+    {file = "mkdocs_material-9.5.15.tar.gz", hash = "sha256:39f03cca45e82bf54eb7456b5a18bd252eabfdd67f237a229471484a0a4d4635"},
 ]
 
 [package.dependencies]

From c3b617d47e31319aa9fc869ac2b473dab6c79d0e Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 01:26:28 +0000
Subject: [PATCH 020/188] :arrow_up: Bump tox from 4.14.1 to 4.14.2

Bumps [tox](https://github.com/tox-dev/tox) from 4.14.1 to 4.14.2.
- [Release notes](https://github.com/tox-dev/tox/releases)
- [Changelog](https://github.com/tox-dev/tox/blob/main/docs/changelog.rst)
- [Commits](https://github.com/tox-dev/tox/compare/4.14.1...4.14.2)

---
updated-dependencies:
- dependency-name: tox
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 2ec7f6529..896521a59 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3942,13 +3942,13 @@ files = [
 
 [[package]]
 name = "tox"
-version = "4.14.1"
+version = "4.14.2"
 description = "tox is a generic virtualenv management and test command line tool"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tox-4.14.1-py3-none-any.whl", hash = "sha256:b03754b6ee6dadc70f2611da82b4ed8f625fcafd247e15d1d0cb056f90a06d3b"},
-    {file = "tox-4.14.1.tar.gz", hash = "sha256:f0ad758c3bbf7e237059c929d3595479363c3cdd5a06ac3e49d1dd020ffbee45"},
+    {file = "tox-4.14.2-py3-none-any.whl", hash = "sha256:2900c4eb7b716af4a928a7fdc2ed248ad6575294ed7cfae2ea41203937422847"},
+    {file = "tox-4.14.2.tar.gz", hash = "sha256:0defb44f6dafd911b61788325741cc6b2e12ea71f987ac025ad4d649f1f1a104"},
 ]
 
 [package.dependencies]

From 57c618232525be5d7aa9f71ac84391e4f78a084c Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 13:11:47 +0100
Subject: [PATCH 021/188] initial changes

---
 docs/how_to/detect_and_annotate.md | 215 +++++++++++++++++++++++------
 1 file changed, 172 insertions(+), 43 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index ca0c56664..b068a923e 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -4,17 +4,29 @@ comments: true
 
 # Detect and Annotate
 
-Supervision offers a streamlined solution to effortlessly annotate predictions from a
-range of object detection and segmentation models. This guide demonstrates how to
-execute inference using the YOLOv8 model with either the
-[Inference](https://github.com/roboflow/inference) or
-[Ultralytics](https://github.com/ultralytics/ultralytics) packages. Following this,
-you'll learn how to import these predictions into Supervision for image annotation
-purposes.
+Supervision provides a seamless process for annotating predictions generated by various 
+object detection and segmentation models. This guide shows how to perform inference 
+with the  [Inference](https://github.com/roboflow/inference), 
+[Ultralytics](https://github.com/ultralytics/ultralytics) or 
+[Transformers](https://github.com/huggingface/transformers) packages. Following this,
+you'll learn how to import these predictions into Supervision and use them to annotate 
+source image.
 
 ## Run Inference
 
-First, you'll need to obtain predictions from your object detection or segmentation model.
+First, you'll need to obtain predictions from your object detection or segmentation 
+model.
+
+=== "Inference"
+
+    ```python
+    import cv2
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model.infer(image)[0]
+    ```
 
 === "Ultralytics"
 
@@ -27,26 +39,52 @@ First, you'll need to obtain predictions from your object detection or segmentat
     results = model(image)[0]
     ```
 
-=== "Inference"
+=== "Transformers"
 
     ```python
-    import cv2
-    from inference.models.utils import get_roboflow_model
-
-    model = get_roboflow_model(model_id="yolov8n-640", api_key=<ROBOFLOW API KEY>)
-    image = cv2.imread(<PATH TO IMAGE>)
-    results = model.infer(image)[0]
+    import torch
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<PATH TO IMAGE>)
+    inputs = processor(images=image, return_tensors="pt")
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
     ```
 
 ## Load Predictions into Supervision
 
 Now that we have predictions from a model, we can load them into Supervision.
 
+=== "Inference"
+
+    We can do so using the [`sv.Detections.from_inference`](detection/core/#supervision.detection.core.Detections.from_inference) method, which accepts model results from both detection and segmentation models.
+
+    ```{ .py hl_lines="2 8" }
+    import cv2
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model.infer(image)[0]
+    detections = sv.Detections.from_inference(results)
+    ```
+
 === "Ultralytics"
 
     We can do so using the [`sv.Detections.from_ultralytics`](detection/core/#supervision.detection.core.Detections.from_ultralytics) method, which accepts model results from both detection and segmentation models.
 
-    ```python
+    ```{ .py hl_lines="2 8" }
     import cv2
     import supervision as sv
     from ultralytics import YOLO
@@ -57,34 +95,123 @@ Now that we have predictions from a model, we can load them into Supervision.
     detections = sv.Detections.from_ultralytics(results)
     ```
 
-=== "Inference"
+=== "Transformers"
 
-    We can do so using the [`sv.Detections.from_inference`](detection/core/#supervision.detection.core.Detections.from_inference) method, which accepts model results from both detection and segmentation models.
+    We can do so using the [`sv.Detections.from_transformers`](detection/core/#supervision.detection.core.Detections.from_transformers) method, which accepts model results from both detection and segmentation models.
 
-    ```python
-    import cv2
+    ```{ .py hl_lines="2 19" }
+    import torch
     import supervision as sv
-    from inference.models.utils import get_roboflow_model
-
-    model = get_roboflow_model(model_id="yolov8n-640", api_key=<ROBOFLOW API KEY>
-    image = cv2.imread(<PATH TO IMAGE>)
-    results = model.infer(image)[0]
-    detections = sv.Detections.from_inference(results)
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<PATH TO IMAGE>)
+    inputs = processor(images=image, return_tensors="pt")
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    detections = sv.Detections.from_transformers(results)
     ```
 
-You can conveniently load predictions from other computer vision frameworks and libraries using:
+You can load predictions from other computer vision frameworks and libraries using:
 
 - [`from_deepsparse`](detection/core/#supervision.detection.core.Detections.from_deepsparse) ([Deepsparse](https://github.com/neuralmagic/deepsparse))
 - [`from_detectron2`](detection/core/#supervision.detection.core.Detections.from_detectron2) ([Detectron2](https://github.com/facebookresearch/detectron2))
 - [`from_mmdetection`](detection/core/#supervision.detection.core.Detections.from_mmdetection) ([MMDetection](https://github.com/open-mmlab/mmdetection))
-- [`from_inference`](detection/core/#supervision.detection.core.Detections.from_inference) ([Roboflow Inference](https://github.com/roboflow/inference))
 - [`from_sam`](detection/core/#supervision.detection.core.Detections.from_sam) ([Segment Anything Model](https://github.com/facebookresearch/segment-anything))
-- [`from_transformers`](detection/core/#supervision.detection.core.Detections.from_transformers) ([HuggingFace Transformers](https://github.com/huggingface/transformers))
 - [`from_yolo_nas`](detection/core/#supervision.detection.core.Detections.from_yolo_nas) ([YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md))
 
-## Annotate Image
+## Annotate Image with Detections
 
-Finally, we can annotate the image with the predictions. Since we are working with an object detection model, we will use the [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) and [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator) classes. If you are running the segmentation model [`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) is a drop-in replacement for [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) that will allow you to draw masks instead of boxes.
+Finally, we can annotate the image with the predictions. Since we are working with an object detection model, we will use the [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) and [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator) classes.
+
+=== "Inference"
+
+    ```{ .py hl_lines="10-16" }
+    import cv2
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model.infer(image)[0]
+    detections = sv.Detections.from_inference(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Ultralytics"
+
+    ```{ .py hl_lines="10-16" }
+    import cv2
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8n.pt")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model(image)[0]
+    detections = sv.Detections.from_ultralytics(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Transformers"
+
+    ```{ .py hl_lines="21-27" }
+    import torch
+    import supervision as sv
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<PATH TO IMAGE>)
+    inputs = processor(images=image, return_tensors="pt")
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    detections = sv.Detections.from_transformers(results)
+    
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+![basic-annotation](https://media.roboflow.com/supervision_annotate_example.png)
+
+## Display Custom Labels
+
+<TODO>
 
 === "Ultralytics"
 
@@ -102,9 +229,9 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     label_annotator = sv.LabelAnnotator()
 
     labels = [
-        model.model.names[class_id]
-        for class_id
-        in detections.class_id
+        f"{class_name} {confidence:.2f}"
+        for class_name, confidence
+        in zip(detections['class_name'], detections.confidence)
     ]
 
     annotated_image = bounding_box_annotator.annotate(
@@ -118,9 +245,9 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     ```python
     import cv2
     import supervision as sv
-    from inference.models.utils import get_roboflow_model
+    from inference import get_model
 
-    model = get_roboflow_model(model_id="yolov8n-640", api_key=<ROBOFLOW API KEY>
+    model = get_model(model_id="yolov8n-640")
     image = cv2.imread(<PATH TO IMAGE>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
@@ -128,18 +255,20 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
 
+    labels = [
+        f"{class_name} {confidence:.2f}"
+        for class_name, confidence
+        in zip(detections['class_name'], detections.confidence)
+    ]
+
     annotated_image = bounding_box_annotator.annotate(
         scene=image, detections=detections)
     annotated_image = label_annotator.annotate(
         scene=annotated_image, detections=detections)
     ```
 
-![Predictions plotted on an image](https://media.roboflow.com/supervision_annotate_example.png)
-
-## Display Annotated Image
+![custom-label-annotation](https://media.roboflow.com/supervision-annotator-examples/label-annotator-example-purple.png)
 
-To display the annotated image in Jupyter Notebook or Google Colab, use the [`sv.plot_image`](utils/notebook/#supervision.utils.notebook.plot_image) function.
+## Annotate Image with Segmentations
 
-```python
-sv.plot_image(annotated_image)
-```
+If you are running the segmentation model [`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) is a drop-in replacement for [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) that will allow you to draw masks instead of boxes.
\ No newline at end of file

From bc586562b5a242ff3406cebd005d0a9b8d0afe81 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 12:14:41 +0000
Subject: [PATCH 022/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/detect_and_annotate.md | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index b068a923e..960730445 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -4,17 +4,17 @@ comments: true
 
 # Detect and Annotate
 
-Supervision provides a seamless process for annotating predictions generated by various 
-object detection and segmentation models. This guide shows how to perform inference 
-with the  [Inference](https://github.com/roboflow/inference), 
-[Ultralytics](https://github.com/ultralytics/ultralytics) or 
+Supervision provides a seamless process for annotating predictions generated by various
+object detection and segmentation models. This guide shows how to perform inference
+with the  [Inference](https://github.com/roboflow/inference),
+[Ultralytics](https://github.com/ultralytics/ultralytics) or
 [Transformers](https://github.com/huggingface/transformers) packages. Following this,
-you'll learn how to import these predictions into Supervision and use them to annotate 
+you'll learn how to import these predictions into Supervision and use them to annotate
 source image.
 
 ## Run Inference
 
-First, you'll need to obtain predictions from your object detection or segmentation 
+First, you'll need to obtain predictions from your object detection or segmentation
 model.
 
 === "Inference"
@@ -51,10 +51,10 @@ model.
 
     image = Image.open(<PATH TO IMAGE>)
     inputs = processor(images=image, return_tensors="pt")
-    
+
     with torch.no_grad():
         outputs = model(**inputs)
-    
+
     width, height = image.size
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
@@ -110,10 +110,10 @@ Now that we have predictions from a model, we can load them into Supervision.
 
     image = Image.open(<PATH TO IMAGE>)
     inputs = processor(images=image, return_tensors="pt")
-    
+
     with torch.no_grad():
         outputs = model(**inputs)
-    
+
     width, height = image.size
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
@@ -188,16 +188,16 @@ Finally, we can annotate the image with the predictions. Since we are working wi
 
     image = Image.open(<PATH TO IMAGE>)
     inputs = processor(images=image, return_tensors="pt")
-    
+
     with torch.no_grad():
         outputs = model(**inputs)
-    
+
     width, height = image.size
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(results)
-    
+
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
 
@@ -271,4 +271,4 @@ Finally, we can annotate the image with the predictions. Since we are working wi
 
 ## Annotate Image with Segmentations
 
-If you are running the segmentation model [`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) is a drop-in replacement for [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) that will allow you to draw masks instead of boxes.
\ No newline at end of file
+If you are running the segmentation model [`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) is a drop-in replacement for [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) that will allow you to draw masks instead of boxes.

From e7b4d6ec419192789a84dfb37b1291fe06f51c05 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 13:55:13 +0100
Subject: [PATCH 023/188] more improvements

---
 docs/how_to/detect_and_annotate.md | 122 +++++++++++++++++++++++++----
 1 file changed, 106 insertions(+), 16 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 960730445..3eb65a9c0 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -12,6 +12,8 @@ with the  [Inference](https://github.com/roboflow/inference),
 you'll learn how to import these predictions into Supervision and use them to annotate
 source image.
 
+![basic-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_1.png)
+
 ## Run Inference
 
 First, you'll need to obtain predictions from your object detection or segmentation
@@ -207,15 +209,44 @@ Finally, we can annotate the image with the predictions. Since we are working wi
         scene=annotated_image, detections=detections)
     ```
 
-![basic-annotation](https://media.roboflow.com/supervision_annotate_example.png)
+![basic-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_1.png)
 
 ## Display Custom Labels
 
-<TODO>
+By default, [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator) 
+will label each detection with its `class_name` (if possible) or `class_id`. You can 
+override this behavior by passing a list of custom `labels` to the `annotate` method.
+
+=== "Inference"
+
+    ```{ .py hl_lines="13-17 22" }
+    import cv2
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model.infer(image)[0]
+    detections = sv.Detections.from_inference(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    labels = [
+        f"{class_name} {confidence:.2f}"
+        for class_name, confidence
+        in zip(detections['class_name'], detections.confidence)
+    ]
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections, labels=labels)
+    ```
 
 === "Ultralytics"
 
-    ```python
+    ```{ .py hl_lines="13-17 22" }
     import cv2
     import supervision as sv
     from ultralytics import YOLO
@@ -240,6 +271,54 @@ Finally, we can annotate the image with the predictions. Since we are working wi
         scene=annotated_image, detections=detections, labels=labels)
     ```
 
+=== "Transformers"
+
+    ```{ .py hl_lines="24-28 33" }
+    import torch
+    import supervision as sv
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<PATH TO IMAGE>)
+    inputs = processor(images=image, return_tensors="pt")
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    detections = sv.Detections.from_transformers(results)
+    
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    labels = [
+        f"{model.config.id2label[class_id]} {confidence:.2f}"
+        for class_id, confidence
+        in zip(detections.class_id, detections.confidence)
+    ]
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections, labels=labels)
+    ```
+
+![custom-label-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_2.png)
+
+## Annotate Image with Segmentations
+
+If you are running the segmentation model 
+[`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) 
+is a drop-in replacement for 
+[`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) 
+that will allow you to draw masks instead of boxes.
+
 === "Inference"
 
     ```python
@@ -247,28 +326,39 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     import supervision as sv
     from inference import get_model
 
-    model = get_model(model_id="yolov8n-640")
+    model = get_model(model_id="yolov8n-seg-640")
     image = cv2.imread(<PATH TO IMAGE>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
-    bounding_box_annotator = sv.BoundingBoxAnnotator()
-    label_annotator = sv.LabelAnnotator()
-
-    labels = [
-        f"{class_name} {confidence:.2f}"
-        for class_name, confidence
-        in zip(detections['class_name'], detections.confidence)
-    ]
+    mask_annotator = sv.MaskAnnotator()
+    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
 
-    annotated_image = bounding_box_annotator.annotate(
+    annotated_image = mask_annotator.annotate(
         scene=image, detections=detections)
     annotated_image = label_annotator.annotate(
         scene=annotated_image, detections=detections)
     ```
 
-![custom-label-annotation](https://media.roboflow.com/supervision-annotator-examples/label-annotator-example-purple.png)
+=== "Ultralytics"
 
-## Annotate Image with Segmentations
+    ```python
+    import cv2
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8n-seg.pt")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model(image)[0]
+    detections = sv.Detections.from_ultralytics(results)
+
+    mask_annotator = sv.MaskAnnotator()
+    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+
+    annotated_image = mask_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
 
-If you are running the segmentation model [`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) is a drop-in replacement for [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) that will allow you to draw masks instead of boxes.
+![segmentation-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_3.png)
\ No newline at end of file

From 4660dfd0d33170bc2f4ddc0b35d07b4efec4754f Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 12:55:27 +0000
Subject: [PATCH 024/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/detect_and_annotate.md | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 3eb65a9c0..b88e36a54 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -213,8 +213,8 @@ Finally, we can annotate the image with the predictions. Since we are working wi
 
 ## Display Custom Labels
 
-By default, [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator) 
-will label each detection with its `class_name` (if possible) or `class_id`. You can 
+By default, [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator)
+will label each detection with its `class_name` (if possible) or `class_id`. You can
 override this behavior by passing a list of custom `labels` to the `annotate` method.
 
 === "Inference"
@@ -284,16 +284,16 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
 
     image = Image.open(<PATH TO IMAGE>)
     inputs = processor(images=image, return_tensors="pt")
-    
+
     with torch.no_grad():
         outputs = model(**inputs)
-    
+
     width, height = image.size
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(results)
-    
+
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
 
@@ -313,10 +313,10 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
 
 ## Annotate Image with Segmentations
 
-If you are running the segmentation model 
-[`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator) 
-is a drop-in replacement for 
-[`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) 
+If you are running the segmentation model
+[`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator)
+is a drop-in replacement for
+[`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator)
 that will allow you to draw masks instead of boxes.
 
 === "Inference"
@@ -361,4 +361,4 @@ that will allow you to draw masks instead of boxes.
         scene=annotated_image, detections=detections)
     ```
 
-![segmentation-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_3.png)
\ No newline at end of file
+![segmentation-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_3.png)

From 6d27b8067b8e795d2d15d0a7202036752842e6a4 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 14:54:34 +0100
Subject: [PATCH 025/188] mention that `VideoSink` and `ImageSink` accept
 images in BGR color format.

---
 supervision/utils/image.py | 3 ++-
 supervision/utils/video.py | 7 +++++++
 2 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 4b9372ee2..0b005464e 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -153,7 +153,8 @@ def save_image(self, image: np.ndarray, image_name: Optional[str] = None):
         Save a given image in the target directory.
 
         Args:
-            image (np.ndarray): The image to be saved.
+            image (np.ndarray): The image to be saved. The image must be in BGR color
+                format.
             image_name (str, optional): The name to use for the saved image.
                 If not provided, a name will be
                 generated using the `image_name_pattern`.
diff --git a/supervision/utils/video.py b/supervision/utils/video.py
index 2314a7e2f..418114a11 100644
--- a/supervision/utils/video.py
+++ b/supervision/utils/video.py
@@ -105,6 +105,13 @@ def __enter__(self):
         return self
 
     def write_frame(self, frame: np.ndarray):
+        """
+        Writes a single video frame to the target video file.
+
+        Args:
+            frame (np.ndarray): The video frame to be written to the file. The frame
+                must be in BGR color format.
+        """
         self.__writer.write(frame)
 
     def __exit__(self, exc_type, exc_value, exc_traceback):

From fec251d9795ef88f2d5c375f561037f44323040c Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 15:01:59 +0100
Subject: [PATCH 026/188] fix `LabelAnnotator` code snippets

---
 docs/annotators.md             | 13 ++++++++++---
 supervision/annotators/core.py | 11 +++++++++--
 2 files changed, 19 insertions(+), 5 deletions(-)

diff --git a/docs/annotators.md b/docs/annotators.md
index dde7cebb1..e1f4b115f 100644
--- a/docs/annotators.md
+++ b/docs/annotators.md
@@ -260,15 +260,22 @@ status: new
 === "Label"
 
     ```python
-     import supervision as sv
+    import supervision as sv
 
     image = ...
     detections = sv.Detections(...)
 
+    labels = [
+        f"{class_name} {confidence:.2f}"
+        for class_name, confidence
+        in zip(detections['class_name'], detections.confidence)
+    ]
+
     label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
     annotated_frame = label_annotator.annotate(
         scene=image.copy(),
-        detections=detections
+        detections=detections,
+        labels=labels
     )
     ```
 
@@ -281,7 +288,7 @@ status: new
 === "Crop"
 
     ```python
-     import supervision as sv
+    import supervision as sv
 
     image = ...
     detections = sv.Detections(...)
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 2be2562ee..fb63a1de7 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1015,15 +1015,22 @@ def annotate(
 
         Example:
             ```python
-            import supervision as sv
+             import supervision as sv
 
             image = ...
             detections = sv.Detections(...)
 
+            labels = [
+                f"{class_name} {confidence:.2f}"
+                for class_name, confidence
+                in zip(detections['class_name'], detections.confidence)
+            ]
+
             label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
             annotated_frame = label_annotator.annotate(
                 scene=image.copy(),
-                detections=detections
+                detections=detections,
+                labels=labels
             )
             ```
 

From 4bb711dcea29916001b0610e2fce2db53191c7a1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Mon, 25 Mar 2024 15:09:21 +0100
Subject: [PATCH 027/188] Add draft of changes to support adding titles

---
 supervision/annotators/utils.py |   2 +-
 supervision/draw/color.py       |  10 +++
 supervision/utils/conversion.py |  27 ++++++
 supervision/utils/image.py      | 141 +++++++++++++++++++++++++++-----
 supervision/utils/iterables.py  |  11 +++
 supervision/utils/notebook.py   |   2 +-
 6 files changed, 170 insertions(+), 23 deletions(-)
 create mode 100644 supervision/utils/conversion.py

diff --git a/supervision/annotators/utils.py b/supervision/annotators/utils.py
index 0a7586a4d..385380ee8 100644
--- a/supervision/annotators/utils.py
+++ b/supervision/annotators/utils.py
@@ -9,7 +9,7 @@
 from supervision.detection.core import Detections
 from supervision.draw.color import Color, ColorPalette
 from supervision.geometry.core import Position
-from supervision.utils.image import cv2_to_pillow, pillow_to_cv2
+from supervision.utils.conversion import cv2_to_pillow, pillow_to_cv2
 
 
 class ColorLookup(Enum):
diff --git a/supervision/draw/color.py b/supervision/draw/color.py
index 149908d8c..825b0da5e 100644
--- a/supervision/draw/color.py
+++ b/supervision/draw/color.py
@@ -124,6 +124,16 @@ def from_hex(cls, color_hex: str) -> Color:
         r, g, b = (int(color_hex[i : i + 2], 16) for i in range(0, 6, 2))
         return cls(r, g, b)
 
+    @classmethod
+    def from_rgb_tuple(cls, color_tuple: Tuple[int, int, int]) -> Color:
+        r, g, b = color_tuple
+        return cls(r=r, g=g, b=b)
+
+    @classmethod
+    def from_bgr_tuple(cls, color_tuple: Tuple[int, int, int]) -> Color:
+        b, g, r = color_tuple
+        return cls(r=r, g=g, b=b)
+
     def as_hex(self) -> str:
         """
         Converts the Color instance to a hex string.
diff --git a/supervision/utils/conversion.py b/supervision/utils/conversion.py
new file mode 100644
index 000000000..3b01b3606
--- /dev/null
+++ b/supervision/utils/conversion.py
@@ -0,0 +1,27 @@
+from typing import List
+
+import cv2
+import numpy as np
+from PIL import Image
+
+from supervision.annotators.base import ImageType
+
+
+def images_to_cv2(images: List[ImageType]) -> List[np.ndarray]:
+    result = []
+    for image in images:
+        if issubclass(type(image), Image.Image):
+            image = pillow_to_cv2(image=image)
+        result.append(image)
+    return result
+
+
+def pillow_to_cv2(image: Image.Image) -> np.ndarray:
+    scene = np.array(image)
+    scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
+    return scene
+
+
+def cv2_to_pillow(image: np.ndarray) -> Image.Image:
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    return Image.fromarray(image)
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 39787ca48..6e918f3b9 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -11,7 +11,12 @@
 
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color
-from supervision.utils.iterables import create_batches
+from supervision.draw.utils import calculate_optimal_text_scale, draw_text
+from supervision.geometry.core import Point
+from supervision.utils.conversion import cv2_to_pillow, images_to_cv2, pillow_to_cv2
+from supervision.utils.iterables import create_batches, fill
+
+RelativePosition = Literal["top", "bottom"]
 
 MAX_COLUMNS_FOR_SINGLE_ROW_GRID = 3
 
@@ -211,6 +216,15 @@ def create_tiles(
     tile_margin: int = 15,
     tile_margin_color: Union[Tuple[int, int, int], Color] = Color.BLACK,
     return_type: Literal["auto", "cv2", "pillow"] = "auto",
+    titles: Optional[List[Optional[str]]] = None,
+    titles_anchors: Optional[Union[Point, List[Optional[Point]]]] = None,
+    titles_color: Union[Tuple[int, int, int], Color] = Color.BLACK,
+    titles_scale: Optional[float] = None,
+    titles_thickness: int = 1,
+    titles_padding: int = 10,
+    titles_text_font: int = cv2.FONT_HERSHEY_SIMPLEX,
+    titles_background_color: Union[Tuple[int, int, int], Color] = Color.WHITE,
+    default_title_anchor: RelativePosition = "top",
 ) -> ImageType:
     """
     Creates tiles mosaic from input images, automating grid placement and
@@ -277,6 +291,18 @@ def create_tiles(
         raise ValueError(
             f"Could not place {len(images)} in grid with size: {grid_size}."
         )
+    if titles is not None:
+        titles = fill(sequence=titles, desired_size=len(images), padding=None)
+    titles_anchors = (
+        [titles_anchors]
+        if not issubclass(type(titles_anchors), list)
+        else titles_anchors
+    )
+    titles_anchors = fill(
+        sequence=titles_anchors, desired_size=len(images), padding=None
+    )
+    titles_color = _color_to_bgr(color=titles_color)
+    titles_background_color = _color_to_bgr(color=titles_background_color)
     tiles = _generate_tiles(
         images=resized_images,
         grid_size=grid_size,
@@ -284,6 +310,15 @@ def create_tiles(
         tile_padding_color=tile_padding_color,
         tile_margin=tile_margin,
         tile_margin_color=tile_margin_color,
+        titles=titles,
+        titles_anchors=titles_anchors,
+        titles_color=titles_color,
+        titles_scale=titles_scale,
+        titles_thickness=titles_thickness,
+        titles_padding=titles_padding,
+        titles_text_font=titles_text_font,
+        titles_background_color=titles_background_color,
+        default_title_anchor=default_title_anchor,
     )
     if return_type == "pillow":
         tiles = cv2_to_pillow(image=tiles)
@@ -351,7 +386,28 @@ def _generate_tiles(
     tile_padding_color: Tuple[int, int, int],
     tile_margin: int,
     tile_margin_color: Tuple[int, int, int],
+    titles: Optional[List[Optional[str]]],
+    titles_anchors: List[Optional[Point]],
+    titles_color: Tuple[int, int, int],
+    titles_scale: Optional[float],
+    titles_thickness: int,
+    titles_padding: int,
+    titles_text_font: int,
+    titles_background_color: Tuple[int, int, int],
+    default_title_anchor: RelativePosition,
 ) -> np.ndarray:
+    images = _draw_texts(
+        images=images,
+        titles=titles,
+        titles_anchors=titles_anchors,
+        titles_color=titles_color,
+        titles_scale=titles_scale,
+        titles_thickness=titles_thickness,
+        titles_padding=titles_padding,
+        titles_text_font=titles_text_font,
+        titles_background_color=titles_background_color,
+        default_title_anchor=default_title_anchor,
+    )
     rows, columns = grid_size
     tiles_elements = list(create_batches(sequence=images, batch_size=columns))
     while len(tiles_elements[-1]) < columns:
@@ -372,6 +428,69 @@ def _generate_tiles(
     )
 
 
+def _draw_texts(
+    images: List[np.ndarray],
+    titles: Optional[List[Optional[str]]],
+    titles_anchors: List[Optional[Point]],
+    titles_color: Tuple[int, int, int],
+    titles_scale: Optional[float],
+    titles_thickness: int,
+    titles_padding: int,
+    titles_text_font: int,
+    titles_background_color: Tuple[int, int, int],
+    default_title_anchor: RelativePosition,
+) -> List[np.ndarray]:
+    if titles is None:
+        return images
+    titles_anchors = _prepare_default_titles_anchors(
+        images=images,
+        titles_anchors=titles_anchors,
+        default_title_anchor=default_title_anchor,
+    )
+    if titles_scale is None:
+        image_height, image_width = images[0].shape[:2]
+        titles_scale = calculate_optimal_text_scale(
+            resolution_wh=(image_width, image_height)
+        )
+    result = []
+    for image, text, anchor in zip(images, titles, titles_anchors):
+        if text is None:
+            result.append(image)
+            continue
+        processed_image = draw_text(
+            scene=image,
+            text=text,
+            text_anchor=anchor,
+            text_color=Color.from_bgr_tuple(titles_color),
+            text_scale=titles_scale,
+            text_thickness=titles_thickness,
+            text_padding=titles_padding,
+            text_font=titles_text_font,
+            background_color=Color.from_bgr_tuple(titles_background_color),
+        )
+        result.append(processed_image)
+    return result
+
+
+def _prepare_default_titles_anchors(
+    images: List[np.ndarray],
+    titles_anchors: List[Optional[Point]],
+    default_title_anchor: RelativePosition,
+) -> List[Point]:
+    result = []
+    for image, anchor in zip(images, titles_anchors):
+        if anchor is not None:
+            result.append(anchor)
+            continue
+        image_height, image_width = image.shape[:2]
+        if default_title_anchor == "top":
+            default_anchor = Point(x=image_width / 2, y=image_height * 0.1)
+        else:
+            default_anchor = Point(x=image_width / 2, y=image_height * 0.9)
+        result.append(default_anchor)
+    return result
+
+
 def _merge_tiles_elements(
     tiles_elements: List[List[np.ndarray]],
     grid_size: Tuple[int, int],
@@ -491,23 +610,3 @@ def _color_to_bgr(color: Union[Tuple[int, int, int], Color]) -> Tuple[int, int,
     if issubclass(type(color), Color):
         return color.as_bgr()
     return color
-
-
-def images_to_cv2(images: List[ImageType]) -> List[np.ndarray]:
-    result = []
-    for image in images:
-        if issubclass(type(image), Image.Image):
-            image = pillow_to_cv2(image=image)
-        result.append(image)
-    return result
-
-
-def pillow_to_cv2(image: Image.Image) -> np.ndarray:
-    scene = np.array(image)
-    scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
-    return scene
-
-
-def cv2_to_pillow(image: np.ndarray) -> Image.Image:
-    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-    return Image.fromarray(image)
diff --git a/supervision/utils/iterables.py b/supervision/utils/iterables.py
index 85684661b..e88548d98 100644
--- a/supervision/utils/iterables.py
+++ b/supervision/utils/iterables.py
@@ -15,3 +15,14 @@ def create_batches(
         current_batch.append(element)
     if len(current_batch) > 0:
         yield current_batch
+
+
+def fill(
+    sequence: List[SequenceElement],
+    desired_size: int,
+    padding: SequenceElement,
+) -> List[SequenceElement]:
+    missing_size = max(0, desired_size - len(sequence))
+    required_padding = [padding] * missing_size
+    sequence.extend(required_padding)
+    return sequence
diff --git a/supervision/utils/notebook.py b/supervision/utils/notebook.py
index 346064ac3..19f5eaed5 100644
--- a/supervision/utils/notebook.py
+++ b/supervision/utils/notebook.py
@@ -5,7 +5,7 @@
 from PIL import Image
 
 from supervision.annotators.base import ImageType
-from supervision.utils.image import pillow_to_cv2
+from supervision.utils.conversion import pillow_to_cv2
 
 
 def plot_image(

From 444853054f3cea32d7dc515fda3262bfa465ae97 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Mon, 25 Mar 2024 15:22:52 +0100
Subject: [PATCH 028/188] Add docstrings for image module

---
 supervision/utils/image.py | 43 ++++++++++++++++++++++++++++++--------
 1 file changed, 34 insertions(+), 9 deletions(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 6e918f3b9..372d3fd37 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -224,11 +224,13 @@ def create_tiles(
     titles_padding: int = 10,
     titles_text_font: int = cv2.FONT_HERSHEY_SIMPLEX,
     titles_background_color: Union[Tuple[int, int, int], Color] = Color.WHITE,
-    default_title_anchor: RelativePosition = "top",
+    default_title_placement: RelativePosition = "top",
 ) -> ImageType:
     """
     Creates tiles mosaic from input images, automating grid placement and
-    converting images to common resolution maintaining aspect ratio.
+    converting images to common resolution maintaining aspect ratio. It is
+    also possible to render text titles on tiles, using optional set of
+    parameters specifying text drawing (see parameters description).
 
     Automated grid placement will try to maintain square shape of grid
     (with size being the nearest integer square root of #images), up to two exceptions:
@@ -262,6 +264,29 @@ def create_tiles(
             conversion. "auto" mode takes a majority vote between types of elements in
             `images` list - resolving draws in favour of OpenCV format. "auto" can be
             safely used when all input images are of the same type.
+        titles (Optional[List[Optional[str]]]): Optional titles to be added to tiles.
+            Elements of that list may be empty - then specific tile (in order presented
+            in `images` parameter) will not be filled with title. It is possible to
+            provide list of titles shorter than `images` - then remaining titles will
+            be assumed empty.
+        titles_anchors (Optional[Union[Point, List[Optional[Point]]]]): Parameter to
+            specify anchor points for titles. It is possible to specify anchor either
+            globally or for specific tiles (following order of `images`).
+            If not given (either globally, or for specific element of the list),
+            it will be calculated automatically based on `default_title_placement`.
+        titles_color (Union[Tuple[int, int, int], Color]): Color of titles text.
+            If tuple provided - should be BGR.
+        titles_scale (Optional[float]): Scale of titles. If not provided - value will
+            be calculated using `calculate_optimal_text_scale(...)`.
+        titles_thickness (int): Thickness of titles text.
+        titles_padding (int): Size of titles padding.
+        titles_text_font (int): Font to be used to render titles. Must be integer
+            constant representing OpenCV font.
+            (See docs: https://docs.opencv.org/4.x/d6/d6e/group__imgproc__draw.html)
+        titles_background_color (Union[Tuple[int, int, int], Color]): Color of title
+            text padding.
+        default_title_placement (Literal["top", "bottom"]): Parameter specifies title
+            anchor placement in case if explicit anchor is not provided.
 
     Returns:
         ImageType: Image with all input images located in tails grid. The output type is
@@ -318,7 +343,7 @@ def create_tiles(
         titles_padding=titles_padding,
         titles_text_font=titles_text_font,
         titles_background_color=titles_background_color,
-        default_title_anchor=default_title_anchor,
+        default_title_placement=default_title_placement,
     )
     if return_type == "pillow":
         tiles = cv2_to_pillow(image=tiles)
@@ -394,7 +419,7 @@ def _generate_tiles(
     titles_padding: int,
     titles_text_font: int,
     titles_background_color: Tuple[int, int, int],
-    default_title_anchor: RelativePosition,
+    default_title_placement: RelativePosition,
 ) -> np.ndarray:
     images = _draw_texts(
         images=images,
@@ -406,7 +431,7 @@ def _generate_tiles(
         titles_padding=titles_padding,
         titles_text_font=titles_text_font,
         titles_background_color=titles_background_color,
-        default_title_anchor=default_title_anchor,
+        default_title_placement=default_title_placement,
     )
     rows, columns = grid_size
     tiles_elements = list(create_batches(sequence=images, batch_size=columns))
@@ -438,14 +463,14 @@ def _draw_texts(
     titles_padding: int,
     titles_text_font: int,
     titles_background_color: Tuple[int, int, int],
-    default_title_anchor: RelativePosition,
+    default_title_placement: RelativePosition,
 ) -> List[np.ndarray]:
     if titles is None:
         return images
     titles_anchors = _prepare_default_titles_anchors(
         images=images,
         titles_anchors=titles_anchors,
-        default_title_anchor=default_title_anchor,
+        default_title_placement=default_title_placement,
     )
     if titles_scale is None:
         image_height, image_width = images[0].shape[:2]
@@ -475,7 +500,7 @@ def _draw_texts(
 def _prepare_default_titles_anchors(
     images: List[np.ndarray],
     titles_anchors: List[Optional[Point]],
-    default_title_anchor: RelativePosition,
+    default_title_placement: RelativePosition,
 ) -> List[Point]:
     result = []
     for image, anchor in zip(images, titles_anchors):
@@ -483,7 +508,7 @@ def _prepare_default_titles_anchors(
             result.append(anchor)
             continue
         image_height, image_width = image.shape[:2]
-        if default_title_anchor == "top":
+        if default_title_placement == "top":
             default_anchor = Point(x=image_width / 2, y=image_height * 0.1)
         else:
             default_anchor = Point(x=image_width / 2, y=image_height * 0.9)

From 4adb2339a4457a9d29ee67f3552d866622bd3ba9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Mon, 25 Mar 2024 16:02:00 +0100
Subject: [PATCH 029/188] Add tests and docstrings for utils

---
 supervision/utils/conversion.py |  32 ++++++++
 supervision/utils/image.py      |   4 +-
 supervision/utils/iterables.py  |  34 ++++++++-
 test/utils/conftest.py          |  13 ++++
 test/utils/test_conversion.py   |  92 +++++++++++++++++++++++
 test/utils/test_iterables.py    | 127 ++++++++++++++++++++++++++++++++
 6 files changed, 298 insertions(+), 4 deletions(-)
 create mode 100644 test/utils/conftest.py
 create mode 100644 test/utils/test_conversion.py
 create mode 100644 test/utils/test_iterables.py

diff --git a/supervision/utils/conversion.py b/supervision/utils/conversion.py
index 3b01b3606..6e7b03c3d 100644
--- a/supervision/utils/conversion.py
+++ b/supervision/utils/conversion.py
@@ -8,6 +8,18 @@
 
 
 def images_to_cv2(images: List[ImageType]) -> List[np.ndarray]:
+    """
+    Converts images provided either as Pillow images or OpenCV
+    images into OpenCV format.
+
+    Args:
+        images (List[ImageType]): Images to be converted
+
+    Returns:
+        List[np.ndarray]: List of input images in OpenCV format
+            (with order preserved).
+
+    """
     result = []
     for image in images:
         if issubclass(type(image), Image.Image):
@@ -17,11 +29,31 @@ def images_to_cv2(images: List[ImageType]) -> List[np.ndarray]:
 
 
 def pillow_to_cv2(image: Image.Image) -> np.ndarray:
+    """
+    Converts Pillow image into OpenCV image, handling RGB -> BGR
+    conversion.
+
+    Args:
+        image (Image.Image): Pillow image (in RGB format).
+
+    Returns:
+        np.ndarray: Input image converted to OpenCV format.
+    """
     scene = np.array(image)
     scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
     return scene
 
 
 def cv2_to_pillow(image: np.ndarray) -> Image.Image:
+    """
+    Converts OpenCV image into Pillow image, handling BGR -> RGB
+    conversion.
+
+    Args:
+        image (np.ndarray): OpenCV image (in BGR format).
+
+    Returns:
+        Image.Image: Input image converted to Pillow format.
+    """
     image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
     return Image.fromarray(image)
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 372d3fd37..8531e9fd6 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -317,14 +317,14 @@ def create_tiles(
             f"Could not place {len(images)} in grid with size: {grid_size}."
         )
     if titles is not None:
-        titles = fill(sequence=titles, desired_size=len(images), padding=None)
+        titles = fill(sequence=titles, desired_size=len(images), content=None)
     titles_anchors = (
         [titles_anchors]
         if not issubclass(type(titles_anchors), list)
         else titles_anchors
     )
     titles_anchors = fill(
-        sequence=titles_anchors, desired_size=len(images), padding=None
+        sequence=titles_anchors, desired_size=len(images), content=None
     )
     titles_color = _color_to_bgr(color=titles_color)
     titles_background_color = _color_to_bgr(color=titles_background_color)
diff --git a/supervision/utils/iterables.py b/supervision/utils/iterables.py
index e88548d98..529ceadb1 100644
--- a/supervision/utils/iterables.py
+++ b/supervision/utils/iterables.py
@@ -6,6 +6,21 @@
 def create_batches(
     sequence: Iterable[SequenceElement], batch_size: int
 ) -> Generator[List[SequenceElement], None, None]:
+    """
+    Provides a generator that yields chunks of input sequence
+    of size specified by `batch_size` parameter. Last
+    chunk may be smaller batch.
+
+    Args:
+        sequence (Iterable[SequenceElement]): Sequence to be
+            split into batches.
+        batch_size (int): Expected size of a batch
+
+    Returns:
+        Generator[List[SequenceElement], None, None]: Generator
+            to yield chinks of `sequence` of size `batch_size`,
+            up to the length of input `sequence`.
+    """
     batch_size = max(batch_size, 1)
     current_batch = []
     for element in sequence:
@@ -20,9 +35,24 @@ def create_batches(
 def fill(
     sequence: List[SequenceElement],
     desired_size: int,
-    padding: SequenceElement,
+    content: SequenceElement,
 ) -> List[SequenceElement]:
+    """
+    Fill the sequence with padding elements until sequence reaches
+    desired size.
+
+    Args:
+        sequence (List[SequenceElement]): Input sequence.
+        desired_size (int): Expected size of output list - difference
+            between this value and actual `sequence` length (if positive)
+            dictates how many elements will be added as padding.
+        content (SequenceElement): Element to be placed at the end of
+            input `sequence` as padding.
+
+    Returns:
+        List[SequenceElement]: Padded version of input `sequence` (if needed)
+    """
     missing_size = max(0, desired_size - len(sequence))
-    required_padding = [padding] * missing_size
+    required_padding = [content] * missing_size
     sequence.extend(required_padding)
     return sequence
diff --git a/test/utils/conftest.py b/test/utils/conftest.py
new file mode 100644
index 000000000..374fbf020
--- /dev/null
+++ b/test/utils/conftest.py
@@ -0,0 +1,13 @@
+import numpy as np
+from _pytest.fixtures import fixture
+from PIL import Image
+
+
+@fixture(scope="function")
+def empty_opencv_image() -> np.ndarray:
+    return np.zeros((128, 128, 3), dtype=np.uint8)
+
+
+@fixture(scope="function")
+def empty_pillow_image() -> Image.Image:
+    return Image.new(mode="RGB", size=(128, 128), color=(0, 0, 0))
diff --git a/test/utils/test_conversion.py b/test/utils/test_conversion.py
new file mode 100644
index 000000000..0ce46db0d
--- /dev/null
+++ b/test/utils/test_conversion.py
@@ -0,0 +1,92 @@
+import numpy as np
+from PIL import Image, ImageChops
+
+from supervision.utils.conversion import cv2_to_pillow, images_to_cv2, pillow_to_cv2
+
+
+def test_cv2_to_pillow(
+    empty_opencv_image: np.ndarray, empty_pillow_image: Image.Image
+) -> None:
+    # when
+    result = cv2_to_pillow(image=empty_opencv_image)
+
+    # then
+    difference = ImageChops.difference(result, empty_pillow_image)
+    assert (
+        difference.getbbox() is None
+    ), "Conversion to PIL.Image expected not to change the content of image"
+
+
+def test_pillow_to_cv2(
+    empty_opencv_image: np.ndarray, empty_pillow_image: Image.Image
+) -> None:
+    # when
+    result = pillow_to_cv2(image=empty_pillow_image)
+
+    # then
+    assert np.allclose(
+        result, empty_opencv_image
+    ), "Conversion to OpenCV image expected not to change the content of image"
+
+
+def test_images_to_cv2_when_empty_input_provided() -> None:
+    # when
+    result = images_to_cv2(images=[])
+
+    # then
+    assert result == [], "Expected empty output when empty input provided"
+
+
+def test_images_to_cv2_when_only_cv2_images_provided(
+    empty_opencv_image: np.ndarray,
+) -> None:
+    # given
+    images = [empty_opencv_image] * 5
+
+    # when
+    result = images_to_cv2(images=images)
+
+    # then
+    assert len(result) == 5, "Expected the same number of output element as input ones"
+    for result_element in result:
+        assert (
+            result_element is empty_opencv_image
+        ), "Expected CV images not to be touched by conversion"
+
+
+def test_images_to_cv2_when_only_pillow_images_provided(
+    empty_pillow_image: Image.Image,
+    empty_opencv_image: np.ndarray,
+) -> None:
+    # given
+    images = [empty_pillow_image] * 5
+
+    # when
+    result = images_to_cv2(images=images)
+
+    # then
+    assert len(result) == 5, "Expected the same number of output element as input ones"
+    for result_element in result:
+        assert np.allclose(
+            result_element, empty_opencv_image
+        ), "Output images expected to be equal to empty OpenCV image"
+
+
+def test_images_to_cv2_when_mixed_input_provided(
+    empty_pillow_image: Image.Image,
+    empty_opencv_image: np.ndarray,
+) -> None:
+    # given
+    images = [empty_pillow_image, empty_opencv_image]
+
+    # when
+    result = images_to_cv2(images=images)
+
+    # then
+    assert len(result) == 2, "Expected the same number of output element as input ones"
+    assert np.allclose(
+        result[0], empty_opencv_image
+    ), "PIL image should be converted to OpenCV one, equal to example empty image"
+    assert (
+        result[1] is empty_opencv_image
+    ), "Expected CV images not to be touched by conversion"
diff --git a/test/utils/test_iterables.py b/test/utils/test_iterables.py
new file mode 100644
index 000000000..313b2baf1
--- /dev/null
+++ b/test/utils/test_iterables.py
@@ -0,0 +1,127 @@
+from supervision.utils.iterables import create_batches, fill
+
+
+def test_create_batches_when_empty_sequence_given() -> None:
+    # when
+    result = list(create_batches(sequence=[], batch_size=4))
+
+    # then
+    assert result == [], "Expected empty generator"
+
+
+def test_create_batches_when_not_allowed_batch_size_given() -> None:
+    # when
+    result = list(create_batches(sequence=[1, 2, 3], batch_size=0))
+
+    # then
+    assert result == [[1], [2], [3]], (
+        "Expected min_batch_size to be established and each element of input "
+        "list provided in separate batch"
+    )
+
+
+def test_create_batches_when_batch_size_larger_than_sequence() -> None:
+    # when
+    result = list(create_batches(sequence=[1, 2], batch_size=4))
+
+    # then
+    assert result == [[1, 2]], (
+        "Expected whole content to be returned in single batch as input sequence "
+        "is smaller than batch size"
+    )
+
+
+def test_create_batches_when_batch_size_multiplier_fits_sequence_length() -> None:
+    # when
+    result = list(create_batches(sequence=[1, 2, 3, 4], batch_size=2))
+
+    # then
+    assert result == [[1, 2], [3, 4]], (
+        "Expected input sequence to be returned in two chunks as batch size "
+        "is half of sequence length"
+    )
+
+
+def test_create_batches_when_batch_size_multiplier_does_not_fir_sequence_length() -> (
+    None
+):
+    # when
+    result = list(create_batches(sequence=[1, 2, 3, 4], batch_size=3))
+
+    # then
+    assert result == [[1, 2, 3], [4]], (
+        "Expected first batch to be of size 3 and last one to be not "
+        "full, with only one element"
+    )
+
+
+def test_fill_when_empty_sequence_given_and_padding_not_needed() -> None:
+    # given
+    sequence = []
+
+    # when
+    result = fill(sequence=sequence, desired_size=0, content=1)
+
+    # then
+    assert result == [], "Expected no elements to be added into sequence"
+
+
+def test_fill_when_empty_sequence_given_and_padding_needed() -> None:
+    # given
+    sequence = []
+
+    # when
+    result = fill(sequence=sequence, desired_size=3, content=1)
+
+    # then
+    assert result == [1, 1, 1], "Expected three padding element to be added"
+
+
+def test_fill_when_non_empty_sequence_given_and_sequence_equal_to_desired_size() -> (
+    None
+):
+    # given
+    sequence = [2, 2, 2]
+
+    # when
+    result = fill(sequence=sequence, desired_size=3, content=1)
+
+    # then
+    assert result == [
+        2,
+        2,
+        2,
+    ], "Expected nothing to be added to sequence, as it is already " "in desired size"
+
+
+def test_fill_when_non_empty_sequence_given_and_sequence_longer_then_desired_size() -> (
+    None
+):
+    # given
+    sequence = [2, 2, 2, 2]
+
+    # when
+    result = fill(sequence=sequence, desired_size=3, content=1)
+
+    # then
+    assert result == [
+        2,
+        2,
+        2,
+        2,
+    ], "Expected nothing to be added to sequence, as it already " "exceeds desired size"
+
+
+def test_fill_when_non_empty_sequence_given_and_padding_needed() -> None:
+    # given
+    sequence = [2]
+
+    # when
+    result = fill(sequence=sequence, desired_size=3, content=1)
+
+    # then
+    assert result == [
+        2,
+        1,
+        1,
+    ], "Expected 2 padding elements to be added to fit desired size"

From b585bb0724f8392856a281ab9e9a2788b77c2c13 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 17:28:59 +0100
Subject: [PATCH 030/188] test slightly simplified API

---
 supervision/annotators/core.py | 63 ++++++++++++++++------------------
 1 file changed, 30 insertions(+), 33 deletions(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 15da147d5..2e28d658e 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -907,7 +907,6 @@ class LabelAnnotator:
 
     def __init__(
         self,
-        corner_radius: int = 15,
         color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         text_color: Color = Color.WHITE,
         text_scale: float = 0.5,
@@ -915,11 +914,10 @@ def __init__(
         text_padding: int = 10,
         text_position: Position = Position.TOP_LEFT,
         color_lookup: ColorLookup = ColorLookup.CLASS,
+        border_radius: int = 0,
     ):
         """
         Args:
-            corner_radius (int): The radius to apply round edges. If the selected
-                value is higher than the lower dimension, width or height, is clipped.
             color (Union[Color, ColorPalette]): The color or color palette to use for
                 annotating the text background.
             text_color (Color): The color to use for the text.
@@ -930,8 +928,10 @@ def __init__(
                 Possible values are defined in the `Position` enum.
             color_lookup (str): Strategy for mapping colors to annotations.
                 Options are `INDEX`, `CLASS`, `TRACK`.
+            border_radius (int): The radius to apply round edges. If the selected
+                value is higher than the lower dimension, width or height, is clipped.
         """
-        self.corner_radius: int = corner_radius
+        self.border_radius: int = border_radius
         self.color: Union[Color, ColorPalette] = color
         self.text_color: Color = text_color
         self.text_scale: float = text_scale
@@ -1085,12 +1085,10 @@ def annotate(
             text_y = text_background_xyxy[1] + self.text_padding + text_h
 
             self.draw_rounded_rectangle(
-                img=scene,
-                pt1=(text_background_xyxy[0], text_background_xyxy[1]),
-                pt2=(text_background_xyxy[2], text_background_xyxy[3]),
+                scene=scene,
+                xyxy=text_background_xyxy,
                 color=color.as_bgr(),
-                thickness=cv2.FILLED,
-                corner_radius=self.corner_radius,
+                border_radius=self.border_radius,
             )
             cv2.putText(
                 img=scene,
@@ -1106,46 +1104,45 @@ def annotate(
 
     @staticmethod
     def draw_rounded_rectangle(
-        img: ImageType,
-        pt1: Tuple[int, int],
-        pt2: Tuple[int, int],
+        scene: np.ndarray,
+        xyxy: Tuple[int, int, int, int],
         color: Tuple[int, int, int],
-        thickness: int,
-        corner_radius: int,
-    ) -> ImageType:
-        x1, y1 = pt1
-        x2, y2 = pt2
-
+        border_radius: int,
+    ) -> np.ndarray:
+        x1, y1, x2, y2 = xyxy
         width = x2 - x1
         height = y2 - y1
 
-        max_corner_radius = min(width, height) // 2
-
-        corner_radius = min(corner_radius, max_corner_radius)
+        border_radius = min(border_radius, min(width, height) // 2)
 
-        rectangle_coords = [
-            ((x1 + corner_radius, y1), (x2 - corner_radius, y2)),
-            ((x1, y1 + corner_radius), (x2, y2 - corner_radius)),
+        rectangle_coordinates = [
+            ((x1 + border_radius, y1), (x2 - border_radius, y2)),
+            ((x1, y1 + border_radius), (x2, y2 - border_radius)),
         ]
         circle_centers = [
-            (x1 + corner_radius, y1 + corner_radius),
-            (x2 - corner_radius, y1 + corner_radius),
-            (x1 + corner_radius, y2 - corner_radius),
-            (x2 - corner_radius, y2 - corner_radius),
+            (x1 + border_radius, y1 + border_radius),
+            (x2 - border_radius, y1 + border_radius),
+            (x1 + border_radius, y2 - border_radius),
+            (x2 - border_radius, y2 - border_radius),
         ]
 
-        for coords in rectangle_coords:
+        for coordinates in rectangle_coordinates:
             cv2.rectangle(
-                img=img, pt1=coords[0], pt2=coords[1], color=color, thickness=thickness
+                img=scene,
+                pt1=coordinates[0],
+                pt2=coordinates[1],
+                color=color,
+                thickness=-1
             )
         for center in circle_centers:
             cv2.circle(
-                img=img,
+                img=scene,
                 center=center,
-                radius=corner_radius,
+                radius=border_radius,
                 color=color,
-                thickness=thickness,
+                thickness=-1,
             )
+        return scene
 
 
 class BlurAnnotator(BaseAnnotator):

From 90f6893d3de1d54ee04367e20dcd8bae065a9d99 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 16:29:14 +0000
Subject: [PATCH 031/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/annotators/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 2e28d658e..6ae5a3eaa 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1132,7 +1132,7 @@ def draw_rounded_rectangle(
                 pt1=coordinates[0],
                 pt2=coordinates[1],
                 color=color,
-                thickness=-1
+                thickness=-1,
             )
         for center in circle_centers:
             cv2.circle(

From ca425a628d6b06b4951632c3f575bbc6cdd88d2f Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 17:44:14 +0000
Subject: [PATCH 032/188] =?UTF-8?q?chore(pre=5Fcommit):=20=E2=AC=86=20pre?=
 =?UTF-8?q?=5Fcommit=20autoupdate?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.3.3 → v0.3.4](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.3...v0.3.4)
---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 0d53b4f30..04f21d151 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -46,7 +46,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.3.3
+      rev: v0.3.4
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

From de8222203cbae297bd32da5a0f5858c50fb823ad Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Mon, 25 Mar 2024 19:44:46 +0100
Subject: [PATCH 033/188] Add tests for tiles creation

---
 supervision/utils/image.py                    |  25 +-
 test/utils/assets/1.jpg                       | Bin 0 -> 68941 bytes
 test/utils/assets/2.jpg                       | Bin 0 -> 37741 bytes
 test/utils/assets/3.jpg                       | Bin 0 -> 47648 bytes
 test/utils/assets/4.jpg                       | Bin 0 -> 40681 bytes
 test/utils/assets/5.jpg                       | Bin 0 -> 45731 bytes
 test/utils/assets/all_images_tile.png         | Bin 0 -> 336614 bytes
 .../all_images_tile_and_custom_colors.png     | Bin 0 -> 336198 bytes
 ...ages_tile_and_custom_colors_and_titles.png | Bin 0 -> 339450 bytes
 .../all_images_tile_and_custom_grid.png       | Bin 0 -> 342323 bytes
 ...es_tile_and_titles_with_custom_configs.png | Bin 0 -> 330963 bytes
 test/utils/assets/four_images_tile.png        | Bin 0 -> 272231 bytes
 test/utils/assets/single_image_tile.png       | Bin 0 -> 80595 bytes
 .../single_image_tile_enforced_grid.png       | Bin 0 -> 86888 bytes
 test/utils/assets/three_images_tile.png       | Bin 0 -> 218360 bytes
 test/utils/assets/two_images_tile.png         | Bin 0 -> 144577 bytes
 test/utils/conftest.py                        |  86 +++++
 test/utils/test_image.py                      | 323 ++++++++++++++++++
 18 files changed, 428 insertions(+), 6 deletions(-)
 create mode 100644 test/utils/assets/1.jpg
 create mode 100644 test/utils/assets/2.jpg
 create mode 100644 test/utils/assets/3.jpg
 create mode 100644 test/utils/assets/4.jpg
 create mode 100644 test/utils/assets/5.jpg
 create mode 100644 test/utils/assets/all_images_tile.png
 create mode 100644 test/utils/assets/all_images_tile_and_custom_colors.png
 create mode 100644 test/utils/assets/all_images_tile_and_custom_colors_and_titles.png
 create mode 100644 test/utils/assets/all_images_tile_and_custom_grid.png
 create mode 100644 test/utils/assets/all_images_tile_and_titles_with_custom_configs.png
 create mode 100644 test/utils/assets/four_images_tile.png
 create mode 100644 test/utils/assets/single_image_tile.png
 create mode 100644 test/utils/assets/single_image_tile_enforced_grid.png
 create mode 100644 test/utils/assets/three_images_tile.png
 create mode 100644 test/utils/assets/two_images_tile.png
 create mode 100644 test/utils/test_image.py

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 8531e9fd6..c1c6b1cfa 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -212,18 +212,20 @@ def create_tiles(
     grid_size: Optional[Tuple[Optional[int], Optional[int]]] = None,
     single_tile_size: Optional[Tuple[int, int]] = None,
     tile_scaling: Literal["min", "max", "avg"] = "avg",
-    tile_padding_color: Union[Tuple[int, int, int], Color] = Color.WHITE,
-    tile_margin: int = 15,
-    tile_margin_color: Union[Tuple[int, int, int], Color] = Color.BLACK,
+    tile_padding_color: Union[Tuple[int, int, int], Color] = Color.from_hex("#D9D9D9"),
+    tile_margin: int = 10,
+    tile_margin_color: Union[Tuple[int, int, int], Color] = Color.from_hex("#BFBEBD"),
     return_type: Literal["auto", "cv2", "pillow"] = "auto",
     titles: Optional[List[Optional[str]]] = None,
     titles_anchors: Optional[Union[Point, List[Optional[Point]]]] = None,
-    titles_color: Union[Tuple[int, int, int], Color] = Color.BLACK,
+    titles_color: Union[Tuple[int, int, int], Color] = Color.from_hex("#262523"),
     titles_scale: Optional[float] = None,
     titles_thickness: int = 1,
     titles_padding: int = 10,
     titles_text_font: int = cv2.FONT_HERSHEY_SIMPLEX,
-    titles_background_color: Union[Tuple[int, int, int], Color] = Color.WHITE,
+    titles_background_color: Union[Tuple[int, int, int], Color] = Color.from_hex(
+        "#D9D9D9"
+    ),
     default_title_placement: RelativePosition = "top",
 ) -> ImageType:
     """
@@ -390,7 +392,9 @@ def _establish_grid_size(
         return _negotiate_grid_size(images=images)
     if grid_size[0] is None:
         return math.ceil(len(images) / grid_size[1]), grid_size[1]
-    return grid_size[0], math.ceil(len(images) / grid_size[0])
+    if grid_size[1] is None:
+        return grid_size[0], math.ceil(len(images) / grid_size[0])
+    return grid_size
 
 
 def _negotiate_grid_size(images: List[np.ndarray]) -> Tuple[int, int]:
@@ -608,6 +612,13 @@ def resize_image_keeping_aspect_ratio(
     """
     Resize and pad image preserving its aspect ratio.
 
+    For example: input image is (640, 480) and we want to resize into
+    (1024, 1024). If this rectangular image is just resized naively
+    to square-shape output - aspect ratio would be altered. If we do not
+    want this to happen - we may resize bigger dimension (640) to 1024.
+    Ratio of change is 1.6. This ratio is later on used to calculate scaling
+    in the other dimension. As a result we have (1024, 768) image.
+
     Parameters:
     - image (np.ndarray): Input image (type will be adjusted by decorator,
         you can provide PIL.Image)
@@ -620,6 +631,8 @@ def resize_image_keeping_aspect_ratio(
         np.ndarray: resized image (type may be adjusted to PIL.Image by decorator
             if function was called with PIL.Image)
     """
+    if image.shape[:2] == desired_size[::-1]:
+        return image
     img_ratio = image.shape[1] / image.shape[0]
     desired_ratio = desired_size[0] / desired_size[1]
     if img_ratio >= desired_ratio:
diff --git a/test/utils/assets/1.jpg b/test/utils/assets/1.jpg
new file mode 100644
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z@aEFe!oUlS{4G?*z~IkNc#WFz{D@0J>&O&;W>#)o^9}Jfm!QxOUpCRF`WI2hd7VE)
zlel!q10VaVUcGp6<*M+rf>r$OhrQ!JksMG4XKvqbJ_B!-2T9wCe-wZZLV*g_NX2jM
zPs98!Vc3gl!7_fgj-pVakgsC47akHBuYS-=OQ4|+T*++*Zi?R}M?>GYUe2pvT&=ZA
zzv?LeSoFZVgSLJb=XyBq>g%q_3nq)2kh`A}eIRAw%wKfJ#sG}UkqFRKz@c|jC2q+Q
z;${HWoD5NdSBg3f3T)4kfhX|9s?Ox(*@7_CQ+Z0V6}>^{OEn&>tXU5yn*J0J;s2M!
z2!<S2>63+%7!43|a4}f?B`7@zk9I(4xdRgz5Vw=aagUQ3fH+_X!IYMmh8`Xd=QPUx
z@EAzs2HJ;wRCR#__qQ6rd*Fx%kn%eM0U1UH4DWrI=ZK&&Z>ue!AfFSZ=6Lq*Ju5CQ
zCbveNpdML*NIw0ejjV}*iP6gYBH!;lGxa3caMq_i<@NP;M=7`0jpRD|)f?Z#-X@9C
z89?w)bHKye3l6Wnu?1+Qjb#6jKJ*ZtPwFz|1_%)Hwe~=IrO%<6MI<p-<zO(tL(Add
zGU9Zvk~RN}W*a66e`P_-=X%T?=(&HCG%w4bYFAUOgw4iFtxQ31$7$Cs(Amv`*)Jkp
zB-s%K;x;%8oyQ7lVdnM2j?WxflU0Zjd@r*-<ui=J1$(x1!B}`!1~Tj;(j+5TnIYm+
z4^Zt{0CO|bxmV?YTo3m%pv?yXmW1A)hZ$oo?A?HhpBJ9&p00)$<}z?&Q-h1}L%uTQ
z8FTe0*-BII>GF5^wH-sG^CGVP&`dS+bWS(9=71d&GQiZzUl;7LdRK+o@PSrt@1J^W
zOJe+Yo)4^4x_I_3*k~bneJ#Qvg4e)Ge3?iUiOT-c#*tSn(;ck*9Icu>8goPkE|K(K
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PfFDyM3s|+GThjjn!M6sO

literal 0
HcmV?d00001

diff --git a/test/utils/conftest.py b/test/utils/conftest.py
index 374fbf020..cc134f8ce 100644
--- a/test/utils/conftest.py
+++ b/test/utils/conftest.py
@@ -1,7 +1,14 @@
+import os
+from typing import List
+
+import cv2
 import numpy as np
 from _pytest.fixtures import fixture
 from PIL import Image
 
+ASSETS_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "assets"))
+ALL_IMAGES_LIST = [os.path.join(ASSETS_DIR, f"{i}.jpg") for i in range(1, 6)]
+
 
 @fixture(scope="function")
 def empty_opencv_image() -> np.ndarray:
@@ -11,3 +18,82 @@ def empty_opencv_image() -> np.ndarray:
 @fixture(scope="function")
 def empty_pillow_image() -> Image.Image:
     return Image.new(mode="RGB", size=(128, 128), color=(0, 0, 0))
+
+
+@fixture(scope="function")
+def all_images() -> List[np.ndarray]:
+    return [cv2.imread(path) for path in ALL_IMAGES_LIST]
+
+
+@fixture(scope="function")
+def one_image() -> np.ndarray:
+    return cv2.imread(ALL_IMAGES_LIST[0])
+
+
+@fixture(scope="function")
+def two_images() -> List[np.ndarray]:
+    return [cv2.imread(path) for path in ALL_IMAGES_LIST[:2]]
+
+
+@fixture(scope="function")
+def three_images() -> List[np.ndarray]:
+    return [cv2.imread(path) for path in ALL_IMAGES_LIST[:3]]
+
+
+@fixture(scope="function")
+def four_images() -> List[np.ndarray]:
+    return [cv2.imread(path) for path in ALL_IMAGES_LIST[:4]]
+
+
+@fixture(scope="function")
+def all_images_tile() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "all_images_tile.png"))
+
+
+@fixture(scope="function")
+def all_images_tile_and_custom_colors() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "all_images_tile_and_custom_colors.png"))
+
+
+@fixture(scope="function")
+def all_images_tile_and_custom_grid() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "all_images_tile_and_custom_grid.png"))
+
+
+@fixture(scope="function")
+def four_images_tile() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "four_images_tile.png"))
+
+
+@fixture(scope="function")
+def single_image_tile() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "single_image_tile.png"))
+
+
+@fixture(scope="function")
+def single_image_tile_enforced_grid() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "single_image_tile_enforced_grid.png"))
+
+
+@fixture(scope="function")
+def three_images_tile() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "three_images_tile.png"))
+
+
+@fixture(scope="function")
+def two_images_tile() -> np.ndarray:
+    return cv2.imread(os.path.join(ASSETS_DIR, "two_images_tile.png"))
+
+
+@fixture(scope="function")
+def all_images_tile_and_custom_colors_and_titles() -> np.ndarray:
+    return cv2.imread(
+        os.path.join(ASSETS_DIR, "all_images_tile_and_custom_colors_and_titles.png")
+    )
+
+
+@fixture(scope="function")
+def all_images_tile_and_titles_with_custom_configs() -> np.ndarray:
+    return cv2.imread(
+        os.path.join(ASSETS_DIR, "all_images_tile_and_titles_with_custom_configs.png")
+    )
diff --git a/test/utils/test_image.py b/test/utils/test_image.py
new file mode 100644
index 000000000..66bb6689a
--- /dev/null
+++ b/test/utils/test_image.py
@@ -0,0 +1,323 @@
+from typing import List
+
+import numpy as np
+import pytest
+from PIL import Image, ImageChops
+
+from supervision import Color, Point
+from supervision.utils.image import (
+    adjust_image_to_cv2_processing,
+    create_tiles,
+    letterbox_image,
+    resize_image_keeping_aspect_ratio,
+)
+
+
+def test_adjust_image_to_cv2_processing_when_pillow_image_submitted(
+    empty_opencv_image: np.ndarray, empty_pillow_image: Image.Image
+) -> None:
+    # given
+    param_a_value = 3
+    param_b_value = "some"
+
+    @adjust_image_to_cv2_processing
+    def my_custom_processing_function(
+        image: np.ndarray,
+        param_a: int,
+        param_b: str,
+    ) -> np.ndarray:
+        assert np.allclose(
+            image, empty_opencv_image
+        ), "Expected conversion to OpenCV image to happen"
+        assert (
+            param_a == param_a_value
+        ), f"Parameter a expected to be {param_a_value} in target function"
+        assert (
+            param_b == param_b_value
+        ), f"Parameter b expected to be {param_b_value} in target function"
+        return image
+
+    # when
+    result = my_custom_processing_function(
+        empty_pillow_image,
+        param_a_value,
+        param_b=param_b_value,
+    )
+
+    # then
+    difference = ImageChops.difference(result, empty_pillow_image)
+    assert difference.getbbox() is None, (
+        "Wrapper is expected to convert-back the OpenCV image "
+        "into Pillow format without changes to content"
+    )
+
+
+def test_adjust_image_to_cv2_processing_when_opencv_image_submitted(
+    empty_opencv_image: np.ndarray,
+) -> None:
+    # given
+    param_a_value = 3
+    param_b_value = "some"
+
+    @adjust_image_to_cv2_processing
+    def my_custom_processing_function(
+        image: np.ndarray,
+        param_a: int,
+        param_b: str,
+    ) -> np.ndarray:
+        assert np.allclose(
+            image, empty_opencv_image
+        ), "Expected conversion to OpenCV image to happen"
+        assert (
+            param_a == param_a_value
+        ), f"Parameter a expected to be {param_a_value} in target function"
+        assert (
+            param_b == param_b_value
+        ), f"Parameter b expected to be {param_b_value} in target function"
+        return image
+
+    # when
+    result = my_custom_processing_function(
+        empty_opencv_image,
+        param_a_value,
+        param_b=param_b_value,
+    )
+
+    # then
+    assert (
+        result is empty_opencv_image
+    ), "Expected to return OpenCV image without changes"
+
+
+def test_resize_image_keeping_aspect_ratio_for_opencv_image() -> None:
+    # given
+    image = np.zeros((480, 640, 3), dtype=np.uint8)
+    expected_result = np.zeros((768, 1024, 3), dtype=np.uint8)
+
+    # when
+    result = resize_image_keeping_aspect_ratio(
+        image=image,
+        desired_size=(1024, 1024),
+    )
+
+    # then
+    assert np.allclose(
+        result, expected_result
+    ), "Expected output shape to be (w, h): (1024, 768)"
+
+
+def test_resize_image_keeping_aspect_ratio_for_pillow_image() -> None:
+    # given
+    image = Image.new(mode="RGB", size=(640, 480), color=(0, 0, 0))
+    expected_result = Image.new(mode="RGB", size=(1024, 768), color=(0, 0, 0))
+
+    # when
+    result = resize_image_keeping_aspect_ratio(
+        image=image,
+        desired_size=(1024, 1024),
+    )
+
+    # then
+    assert result.size == (1024, 768), "Expected output shape to be (w, h): (1024, 768)"
+    difference = ImageChops.difference(result, expected_result)
+    assert (
+        difference.getbbox() is None
+    ), "Expected no difference in resized image content as the image is all zeros"
+
+
+def test_letterbox_image_for_opencv_image() -> None:
+    # given
+    image = np.zeros((480, 640, 3), dtype=np.uint8)
+    expected_result = np.concatenate(
+        [
+            np.ones((128, 1024, 3), dtype=np.uint8) * 255,
+            np.zeros((768, 1024, 3), dtype=np.uint8),
+            np.ones((128, 1024, 3), dtype=np.uint8) * 255,
+        ],
+        axis=0,
+    )
+
+    # when
+    result = letterbox_image(
+        image=image, desired_size=(1024, 1024), color=(255, 255, 255)
+    )
+
+    # then
+    assert np.allclose(result, expected_result), (
+        "Expected output shape to be (w, h): "
+        "(1024, 1024) with padding added top and bottom"
+    )
+
+
+def test_letterbox_image_for_pillow_image() -> None:
+    # given
+    image = Image.new(mode="RGB", size=(640, 480), color=(0, 0, 0))
+    expected_result = Image.fromarray(
+        np.concatenate(
+            [
+                np.ones((128, 1024, 3), dtype=np.uint8) * 255,
+                np.zeros((768, 1024, 3), dtype=np.uint8),
+                np.ones((128, 1024, 3), dtype=np.uint8) * 255,
+            ],
+            axis=0,
+        )
+    )
+
+    # when
+    result = letterbox_image(
+        image=image, desired_size=(1024, 1024), color=(255, 255, 255)
+    )
+
+    # then
+    assert result.size == (
+        1024,
+        1024,
+    ), "Expected output shape to be (w, h): (1024, 1024)"
+    difference = ImageChops.difference(result, expected_result)
+    assert (
+        difference.getbbox() is None
+    ), "Expected padding to be added top and bottom with padding added top and bottom"
+
+
+def test_create_tiles_with_one_image(
+    one_image: np.ndarray, single_image_tile: np.ndarray
+) -> None:
+    # when
+    result = create_tiles(images=[one_image], single_tile_size=(240, 240))
+
+    # # then
+    assert np.allclose(result, single_image_tile, atol=5.0)
+
+
+def test_create_tiles_with_one_image_and_enforced_grid(
+    one_image: np.ndarray, single_image_tile_enforced_grid: np.ndarray
+) -> None:
+    # when
+    result = create_tiles(
+        images=[one_image],
+        grid_size=(None, 3),
+        single_tile_size=(240, 240),
+    )
+
+    # then
+    assert np.allclose(result, single_image_tile_enforced_grid, atol=5.0)
+
+
+def test_create_tiles_with_two_images(
+    two_images: List[np.ndarray], two_images_tile: np.ndarray
+) -> None:
+    # when
+    result = create_tiles(images=two_images, single_tile_size=(240, 240))
+
+    # then
+    assert np.allclose(result, two_images_tile, atol=5.0)
+
+
+def test_create_tiles_with_three_images(
+    three_images: List[np.ndarray], three_images_tile: np.ndarray
+) -> None:
+    # when
+    result = create_tiles(images=three_images, single_tile_size=(240, 240))
+
+    # then
+    assert np.allclose(result, three_images_tile, atol=5.0)
+
+
+def test_create_tiles_with_four_images(
+    four_images: List[np.ndarray],
+    four_images_tile: np.ndarray,
+) -> None:
+    # when
+    result = create_tiles(images=four_images, single_tile_size=(240, 240))
+
+    # then
+    assert np.allclose(result, four_images_tile, atol=5.0)
+
+
+def test_create_tiles_with_all_images(
+    all_images: List[np.ndarray],
+    all_images_tile: np.ndarray,
+) -> None:
+    # when
+    result = create_tiles(images=all_images, single_tile_size=(240, 240))
+
+    # then
+    assert np.allclose(result, all_images_tile, atol=5.0)
+
+
+def test_create_tiles_with_all_images_and_custom_grid(
+    all_images: List[np.ndarray], all_images_tile_and_custom_grid: np.ndarray
+) -> None:
+    # when
+    result = create_tiles(
+        images=all_images,
+        grid_size=(3, 3),
+        single_tile_size=(240, 240),
+    )
+
+    # then
+    assert np.allclose(result, all_images_tile_and_custom_grid, atol=5.0)
+
+
+def test_create_tiles_with_all_images_and_custom_colors(
+    all_images: List[np.ndarray], all_images_tile_and_custom_colors: np.ndarray
+) -> None:
+    # when
+    result = create_tiles(
+        images=all_images,
+        tile_margin_color=(127, 127, 127),
+        tile_padding_color=(224, 224, 224),
+        single_tile_size=(240, 240),
+    )
+
+    # then
+    assert np.allclose(result, all_images_tile_and_custom_colors, atol=5.0)
+
+
+def test_create_tiles_with_all_images_and_titles(
+    all_images: List[np.ndarray],
+    all_images_tile_and_custom_colors_and_titles: np.ndarray,
+) -> None:
+    # when
+    result = create_tiles(
+        images=all_images,
+        titles=["Image 1", None, "Image 3", "Image 4"],
+        single_tile_size=(240, 240),
+    )
+
+    # then
+    assert np.allclose(result, all_images_tile_and_custom_colors_and_titles, atol=5.0)
+
+
+def test_create_tiles_with_all_images_and_titles_with_custom_configs(
+    all_images: List[np.ndarray],
+    all_images_tile_and_titles_with_custom_configs: np.ndarray,
+) -> None:
+    # when
+    result = create_tiles(
+        images=all_images,
+        titles=["Image 1", None, "Image 3", "Image 4"],
+        single_tile_size=(240, 240),
+        titles_anchors=[
+            Point(x=200, y=300),
+            Point(x=300, y=400),
+            None,
+            Point(x=300, y=400),
+        ],
+        titles_color=Color.RED,
+        titles_scale=1.5,
+        titles_thickness=3,
+        titles_padding=20,
+        titles_background_color=Color.BLACK,
+        default_title_placement="bottom",
+    )
+
+    # then
+    assert np.allclose(result, all_images_tile_and_titles_with_custom_configs, atol=5.0)
+
+
+def test_create_tiles_with_all_images_and_custom_grid_to_small_to_fit_images(
+    all_images: List[np.ndarray],
+) -> None:
+    with pytest.raises(ValueError):
+        _ = create_tiles(images=all_images, grid_size=(2, 2))

From 0aacfa47d365b2f784afd4890a4b2925e3fa7c1d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Mon, 25 Mar 2024 19:47:45 +0100
Subject: [PATCH 034/188] Add new utils to library interface

---
 supervision/__init__.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 35f525b04..8c3acc265 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -72,7 +72,15 @@
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
 from supervision.utils.file import list_files_with_extensions
-from supervision.utils.image import ImageSink, crop_image, place_image, resize_image
+from supervision.utils.image import (
+    ImageSink,
+    create_tiles,
+    crop_image,
+    letterbox_image,
+    place_image,
+    resize_image,
+    resize_image_keeping_aspect_ratio,
+)
 from supervision.utils.notebook import plot_image, plot_images_grid
 from supervision.utils.video import (
     FPSMonitor,

From b2b417af5bbbbfa4c88cf815397f77fce925e8dc Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Tue, 26 Mar 2024 00:39:11 +0530
Subject: [PATCH 035/188] Enhanced from_transformers to support class name
 extraction

---
 supervision/detection/core.py | 22 ++++++++++++++++------
 1 file changed, 16 insertions(+), 6 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index f170563ca..91dfde17b 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -388,19 +388,29 @@ def from_mmdetection(cls, mmdet_results) -> Detections:
         )
 
     @classmethod
-    def from_transformers(cls, transformers_results: dict) -> Detections:
+    def from_transformers(cls, transformers_results: dict, id2label: Dict[int, str]) -> Detections:
         """
-        Creates a Detections instance from object detection
-        [transformer](https://github.com/huggingface/transformers) inference result.
+        Constructs a Detections instance from the inference results of a Transformers object detection model.
+        [transformer](https://github.com/huggingface/transformers)
+
+        Args:
+            transformers_results (dict): A dictionary containing the scores, labels, and boxes for an image
+                as predicted by the Transformers model.
+            id2label (Dict[int, str]): A dictionary mapping class IDs to class names.
 
         Returns:
             Detections: A new Detections object.
         """
 
+        boxes = transformers_results["boxes"].cpu().numpy()
+        scores = transformers_results["scores"].cpu().numpy()
+        class_ids = transformers_results["labels"].cpu().numpy().astype(int)
+        class_names = np.array([id2label[class_id] for class_id in class_ids])
         return cls(
-            xyxy=transformers_results["boxes"].cpu().numpy(),
-            confidence=transformers_results["scores"].cpu().numpy(),
-            class_id=transformers_results["labels"].cpu().numpy().astype(int),
+            xyxy=boxes,
+            confidence=scores,
+            class_id=class_ids,
+            data={CLASS_NAME_DATA_FIELD: class_names},
         )
 
     @classmethod

From 8694f0023dd1c2a3eba569d7a249181e5298c06e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 19:24:20 +0000
Subject: [PATCH 036/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/core.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 91dfde17b..f6c413a52 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -388,7 +388,9 @@ def from_mmdetection(cls, mmdet_results) -> Detections:
         )
 
     @classmethod
-    def from_transformers(cls, transformers_results: dict, id2label: Dict[int, str]) -> Detections:
+    def from_transformers(
+        cls, transformers_results: dict, id2label: Dict[int, str]
+    ) -> Detections:
         """
         Constructs a Detections instance from the inference results of a Transformers object detection model.
         [transformer](https://github.com/huggingface/transformers)

From 15e17adef149c8f83d5c724fa33009ee6c0b2f5f Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 21:11:47 +0100
Subject: [PATCH 037/188] Detect Small Objects documentation

---
 docs/how_to/detect_and_annotate.md  |   1 +
 docs/how_to/detect_small_objects.md | 262 ++++++++++++++++++++++++++++
 docs/index.md                       |   8 +
 mkdocs.yml                          |   1 +
 4 files changed, 272 insertions(+)
 create mode 100644 docs/how_to/detect_small_objects.md

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index b88e36a54..18739b283 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -1,5 +1,6 @@
 ---
 comments: true
+status: new
 ---
 
 # Detect and Annotate
diff --git a/docs/how_to/detect_small_objects.md b/docs/how_to/detect_small_objects.md
new file mode 100644
index 000000000..ebd6c0968
--- /dev/null
+++ b/docs/how_to/detect_small_objects.md
@@ -0,0 +1,262 @@
+---
+comments: true
+status: new
+---
+
+# Detect Small Objects
+
+This guide shows how to detect small objects
+with the  [Inference](https://github.com/roboflow/inference),
+[Ultralytics](https://github.com/ultralytics/ultralytics) or
+[Transformers](https://github.com/huggingface/transformers) packages using 
+[`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer).
+
+<video controls>
+    <source src="https://media.roboflow.com/supervision_detect_small_objects_example.mp4" type="video/mp4">
+</video>
+
+## Baseline Detection
+
+Small object detection in high-resolution images presents challenges due to the objects'
+size relative to the image resolution.
+
+=== "Inference"
+
+    ```python
+    import cv2
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8x-640")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model.infer(image)[0]
+    detections = sv.Detections.from_inference(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Ultralytics"
+
+    ```python
+    import cv2
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8x.pt")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model(image)[0]
+    detections = sv.Detections.from_ultralytics(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Transformers"
+
+    ```python
+    import torch
+    import supervision as sv
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<PATH TO IMAGE>)
+    inputs = processor(images=image, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    detections = sv.Detections.from_transformers(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    labels = [
+        model.config.id2label[class_id]
+        for class_id
+        in detections.class_id
+    ]
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections, labels=labels)
+    ```
+
+![basic-detection](https://media.roboflow.com/supervision_detect_small_objects_example_1.png)
+
+## Input Resolution
+
+Modifying the input resolution of images before detection can enhance small object 
+identification at the cost of processing speed and increased memory usage. This method 
+is less effective for ultra-high-resolution images (4K and above).
+
+=== "Inference"
+
+    ```{ .py hl_lines="5" }
+    import cv2
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8x-1280")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model.infer(image)[0]
+    detections = sv.Detections.from_inference(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Ultralytics"
+
+    ```{ .py hl_lines="7" }
+    import cv2
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8x.pt")
+    image = cv2.imread(<PATH TO IMAGE>)
+    results = model(image, imgsz=1280)[0]
+    detections = sv.Detections.from_ultralytics(results)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+![detection-with-high-input-resolution](https://media.roboflow.com/supervision_detect_small_objects_example_2.png)
+
+## Inference Slicer
+
+[`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer) 
+processes high-resolution images by dividing them into smaller segments, detecting 
+objects within each, and aggregating the results.
+
+=== "Inference"
+
+    ```{ .py hl_lines="9-14" }
+    import cv2
+    import numpy as np
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8x-640")
+    image = cv2.imread(<PATH TO IMAGE>)
+
+    def callback(image_slice: np.ndarray) -> sv.Detections:
+        results = model.infer(image_slice)[0]
+        detections = sv.Detections.from_inference(results)
+
+    slicer = sv.InferenceSlicer(callback = callback)
+    detections = slicer(image)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Ultralytics"
+
+    ```{ .py hl_lines="9-14" }
+    import cv2
+    import numpy as np
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8x.pt")
+    image = cv2.imread(<PATH TO IMAGE>)
+
+    def callback(image_slice: np.ndarray) -> sv.Detections:
+        result = model(image_slice)[0]
+        return sv.Detections.from_ultralytics(result)
+    
+    slicer = sv.InferenceSlicer(callback = callback)
+    detections = slicer(image)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
+=== "Transformers"
+
+    ```{ .py hl_lines="13-28" }
+    import cv2
+    import torch
+    import numpy as np
+    import supervision as sv
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = cv2.imread(<PATH TO IMAGE>)
+
+    def callback(image_slice: np.ndarray) -> sv.Detections:
+        image_slice = cv2.cvtColor(image_slice, cv2.COLOR_BGR2RGB)
+        image_slice = Image.fromarray(image_slice)
+        inputs = processor(images=image_slice, return_tensors="pt")
+
+        with torch.no_grad():
+            outputs = model(**inputs)
+
+        width, height = image.size
+        target_size = torch.tensor([[height, width]])
+        results = processor.post_process_object_detection(
+            outputs=outputs, target_sizes=target_size)[0]
+        return sv.Detections.from_transformers(results)
+    
+    slicer = sv.InferenceSlicer(callback = callback)
+    detections = slicer(image)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    label_annotator = sv.LabelAnnotator()
+
+    labels = [
+        model.config.id2label[class_id]
+        for class_id
+        in detections.class_id
+    ]
+
+    annotated_image = bounding_box_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections, labels=labels)
+    ```
+
+![detection-with-inference-slicer](https://media.roboflow.com/supervision_detect_small_objects_example_3.png)
diff --git a/docs/index.md b/docs/index.md
index 7e4733fe9..6846acb1c 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -109,6 +109,14 @@ You can install `supervision` with pip in a
 
     [:octicons-arrow-right-24: Tutorial](how_to/track_objects.md)
 
+-   __Detect Small Objects__
+
+    ---
+
+    Learn how to detect small objects in images 
+
+    [:octicons-arrow-right-24: Tutorial](how_to/detect_small_objects.md)
+
 -   > __Count Objects Crossing Line__
 
     ---
diff --git a/mkdocs.yml b/mkdocs.yml
index 5444290b9..d325eb658 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -38,6 +38,7 @@ nav:
   - Home: index.md
   - How to:
       - Detect and Annotate: how_to/detect_and_annotate.md
+      - Detect Small Objects: how_to/detect_small_objects.md
       - Track Objects: how_to/track_objects.md
       - Filter Detections: how_to/filter_detections.md
   - API:

From cf88cc03845e9e87f395addf88a45b503e9f2566 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 25 Mar 2024 20:14:14 +0000
Subject: [PATCH 038/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/detect_small_objects.md | 14 +++++++-------
 docs/index.md                       |  2 +-
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/docs/how_to/detect_small_objects.md b/docs/how_to/detect_small_objects.md
index ebd6c0968..e21a27d36 100644
--- a/docs/how_to/detect_small_objects.md
+++ b/docs/how_to/detect_small_objects.md
@@ -8,7 +8,7 @@ status: new
 This guide shows how to detect small objects
 with the  [Inference](https://github.com/roboflow/inference),
 [Ultralytics](https://github.com/ultralytics/ultralytics) or
-[Transformers](https://github.com/huggingface/transformers) packages using 
+[Transformers](https://github.com/huggingface/transformers) packages using
 [`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer).
 
 <video controls>
@@ -104,8 +104,8 @@ size relative to the image resolution.
 
 ## Input Resolution
 
-Modifying the input resolution of images before detection can enhance small object 
-identification at the cost of processing speed and increased memory usage. This method 
+Modifying the input resolution of images before detection can enhance small object
+identification at the cost of processing speed and increased memory usage. This method
 is less effective for ultra-high-resolution images (4K and above).
 
 === "Inference"
@@ -154,8 +154,8 @@ is less effective for ultra-high-resolution images (4K and above).
 
 ## Inference Slicer
 
-[`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer) 
-processes high-resolution images by dividing them into smaller segments, detecting 
+[`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer)
+processes high-resolution images by dividing them into smaller segments, detecting
 objects within each, and aggregating the results.
 
 === "Inference"
@@ -199,7 +199,7 @@ objects within each, and aggregating the results.
     def callback(image_slice: np.ndarray) -> sv.Detections:
         result = model(image_slice)[0]
         return sv.Detections.from_ultralytics(result)
-    
+
     slicer = sv.InferenceSlicer(callback = callback)
     detections = slicer(image)
 
@@ -240,7 +240,7 @@ objects within each, and aggregating the results.
         results = processor.post_process_object_detection(
             outputs=outputs, target_sizes=target_size)[0]
         return sv.Detections.from_transformers(results)
-    
+
     slicer = sv.InferenceSlicer(callback = callback)
     detections = slicer(image)
 
diff --git a/docs/index.md b/docs/index.md
index 6846acb1c..17151f5e7 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -113,7 +113,7 @@ You can install `supervision` with pip in a
 
     ---
 
-    Learn how to detect small objects in images 
+    Learn how to detect small objects in images
 
     [:octicons-arrow-right-24: Tutorial](how_to/detect_small_objects.md)
 

From 0d16b13e7a10c0cd8d98f43d759986ee0b080a1f Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Mon, 25 Mar 2024 22:09:23 +0100
Subject: [PATCH 039/188] Added additional visualization

---
 docs/how_to/detect_small_objects.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/docs/how_to/detect_small_objects.md b/docs/how_to/detect_small_objects.md
index e21a27d36..ed8b067a1 100644
--- a/docs/how_to/detect_small_objects.md
+++ b/docs/how_to/detect_small_objects.md
@@ -158,6 +158,10 @@ is less effective for ultra-high-resolution images (4K and above).
 processes high-resolution images by dividing them into smaller segments, detecting
 objects within each, and aggregating the results.
 
+<video controls>
+    <source src="https://media.roboflow.com/supervision_detect_small_objects_example_2.mp4" type="video/mp4">
+</video>
+
 === "Inference"
 
     ```{ .py hl_lines="9-14" }

From 8a06de47e98fe12fc8e5c4f6862ac79153a817d6 Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Tue, 26 Mar 2024 07:35:45 +0530
Subject: [PATCH 040/188] made  id2label param optional and handle class names

---
 supervision/detection/core.py | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index f6c413a52..49b3d62d1 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -388,9 +388,7 @@ def from_mmdetection(cls, mmdet_results) -> Detections:
         )
 
     @classmethod
-    def from_transformers(
-        cls, transformers_results: dict, id2label: Dict[int, str]
-    ) -> Detections:
+    def from_transformers(cls, transformers_results: dict, id2label: Optional[Dict[int, str]] = None) -> Detections:
         """
         Constructs a Detections instance from the inference results of a Transformers object detection model.
         [transformer](https://github.com/huggingface/transformers)
@@ -407,14 +405,18 @@ def from_transformers(
         boxes = transformers_results["boxes"].cpu().numpy()
         scores = transformers_results["scores"].cpu().numpy()
         class_ids = transformers_results["labels"].cpu().numpy().astype(int)
-        class_names = np.array([id2label[class_id] for class_id in class_ids])
+        data = {}
+        if id2label is not None:
+            class_names = np.array([id2label[class_id] for class_id in class_ids])
+            data[CLASS_NAME_DATA_FIELD] = class_names
         return cls(
             xyxy=boxes,
             confidence=scores,
             class_id=class_ids,
-            data={CLASS_NAME_DATA_FIELD: class_names},
+            data= data,
         )
 
+
     @classmethod
     def from_detectron2(cls, detectron2_results) -> Detections:
         """

From c56c446eb6778e928c79e61200394d827d9c093c Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 26 Mar 2024 02:06:07 +0000
Subject: [PATCH 041/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/core.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 49b3d62d1..d9827ba64 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -388,7 +388,9 @@ def from_mmdetection(cls, mmdet_results) -> Detections:
         )
 
     @classmethod
-    def from_transformers(cls, transformers_results: dict, id2label: Optional[Dict[int, str]] = None) -> Detections:
+    def from_transformers(
+        cls, transformers_results: dict, id2label: Optional[Dict[int, str]] = None
+    ) -> Detections:
         """
         Constructs a Detections instance from the inference results of a Transformers object detection model.
         [transformer](https://github.com/huggingface/transformers)
@@ -413,10 +415,9 @@ def from_transformers(cls, transformers_results: dict, id2label: Optional[Dict[i
             xyxy=boxes,
             confidence=scores,
             class_id=class_ids,
-            data= data,
+            data=data,
         )
 
-
     @classmethod
     def from_detectron2(cls, detectron2_results) -> Detections:
         """

From 3ed4aeffffae41164fb5d882280eaaa92818fefe Mon Sep 17 00:00:00 2001
From: Raif Olson <raif.t.olson.24@dartmouth.edu>
Date: Mon, 25 Mar 2024 21:41:38 -0400
Subject: [PATCH 042/188] fix bugs in PR #1035

fix tuple unpacking bug in PR #1035

Fix bug with detections with un-initialized tracker_ids
---
 supervision/tracker/byte_tracker/core.py | 16 +++++++++++++---
 1 file changed, 13 insertions(+), 3 deletions(-)

diff --git a/supervision/tracker/byte_tracker/core.py b/supervision/tracker/byte_tracker/core.py
index 9156fb581..4d6416e89 100644
--- a/supervision/tracker/byte_tracker/core.py
+++ b/supervision/tracker/byte_tracker/core.py
@@ -286,13 +286,23 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
             iou_costs = 1 - ious
 
             matches, _, _ = matching.linear_assignment(iou_costs, 0.5)
-            for i, idet, itrack in enumerate(matches):
+            for i, (idet, itrack) in enumerate(matches):
                 if i == 0:
                     final_detections = detections[[idet]]
-                    final_detections.tracker_id[0] = int(tracks[itrack].track_id)
+                    if final_detections.tracker_id is None:
+                        final_detections.tracker_id = np.asarray(
+                            [int(tracks[itrack].track_id)]
+                        )
+                    else:
+                        final_detections.tracker_id[0] = int(tracks[itrack].track_id)
                 else:
                     current_detection = detections[[idet]]
-                    current_detection.tracker_id[0] = int(tracks[itrack].track_id)
+                    if current_detection.tracker_id is None:
+                        current_detection.tracker_id = np.asarray(
+                            [int(tracks[itrack].track_id)]
+                        )
+                    else:
+                        current_detection.tracker_id[0] = int(tracks[itrack].track_id)
                     final_detections = Detections.merge(
                         [final_detections, current_detection]
                     )

From 5a040969d76bc87eeeefdb7cdc90400500674c1c Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 26 Mar 2024 09:53:16 +0100
Subject: [PATCH 043/188] fix how-to links

---
 docs/how_to/detect_and_annotate.md  | 18 +++++++++---------
 docs/how_to/detect_small_objects.md |  4 ++--
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 18739b283..45d0487a9 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -126,15 +126,15 @@ Now that we have predictions from a model, we can load them into Supervision.
 
 You can load predictions from other computer vision frameworks and libraries using:
 
-- [`from_deepsparse`](detection/core/#supervision.detection.core.Detections.from_deepsparse) ([Deepsparse](https://github.com/neuralmagic/deepsparse))
-- [`from_detectron2`](detection/core/#supervision.detection.core.Detections.from_detectron2) ([Detectron2](https://github.com/facebookresearch/detectron2))
-- [`from_mmdetection`](detection/core/#supervision.detection.core.Detections.from_mmdetection) ([MMDetection](https://github.com/open-mmlab/mmdetection))
-- [`from_sam`](detection/core/#supervision.detection.core.Detections.from_sam) ([Segment Anything Model](https://github.com/facebookresearch/segment-anything))
-- [`from_yolo_nas`](detection/core/#supervision.detection.core.Detections.from_yolo_nas) ([YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md))
+- [`from_deepsparse`](/latest/detection/core/#supervision.detection.core.Detections.from_deepsparse) ([Deepsparse](https://github.com/neuralmagic/deepsparse))
+- [`from_detectron2`](/latest/detection/core/#supervision.detection.core.Detections.from_detectron2) ([Detectron2](https://github.com/facebookresearch/detectron2))
+- [`from_mmdetection`](/latest/detection/core/#supervision.detection.core.Detections.from_mmdetection) ([MMDetection](https://github.com/open-mmlab/mmdetection))
+- [`from_sam`](/latest/detection/core/#supervision.detection.core.Detections.from_sam) ([Segment Anything Model](https://github.com/facebookresearch/segment-anything))
+- [`from_yolo_nas`](/latest/detection/core/#supervision.detection.core.Detections.from_yolo_nas) ([YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md))
 
 ## Annotate Image with Detections
 
-Finally, we can annotate the image with the predictions. Since we are working with an object detection model, we will use the [`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator) and [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator) classes.
+Finally, we can annotate the image with the predictions. Since we are working with an object detection model, we will use the [`sv.BoundingBoxAnnotator`](/latest/annotators/#supervision.annotators.core.BoundingBoxAnnotator) and [`sv.LabelAnnotator`](/latest/annotators/#supervision.annotators.core.LabelAnnotator) classes.
 
 === "Inference"
 
@@ -214,7 +214,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
 
 ## Display Custom Labels
 
-By default, [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator)
+By default, [`sv.LabelAnnotator`](/latest/annotators/#supervision.annotators.core.LabelAnnotator)
 will label each detection with its `class_name` (if possible) or `class_id`. You can
 override this behavior by passing a list of custom `labels` to the `annotate` method.
 
@@ -315,9 +315,9 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
 ## Annotate Image with Segmentations
 
 If you are running the segmentation model
-[`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator)
+[`sv.MaskAnnotator`](/latest/annotators/#supervision.annotators.core.MaskAnnotator)
 is a drop-in replacement for
-[`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator)
+[`sv.BoundingBoxAnnotator`](/latest/annotators/#supervision.annotators.core.BoundingBoxAnnotator)
 that will allow you to draw masks instead of boxes.
 
 === "Inference"
diff --git a/docs/how_to/detect_small_objects.md b/docs/how_to/detect_small_objects.md
index ed8b067a1..9f35a96c5 100644
--- a/docs/how_to/detect_small_objects.md
+++ b/docs/how_to/detect_small_objects.md
@@ -9,7 +9,7 @@ This guide shows how to detect small objects
 with the  [Inference](https://github.com/roboflow/inference),
 [Ultralytics](https://github.com/ultralytics/ultralytics) or
 [Transformers](https://github.com/huggingface/transformers) packages using
-[`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer).
+[`InferenceSlicer`](/latest/detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer).
 
 <video controls>
     <source src="https://media.roboflow.com/supervision_detect_small_objects_example.mp4" type="video/mp4">
@@ -154,7 +154,7 @@ is less effective for ultra-high-resolution images (4K and above).
 
 ## Inference Slicer
 
-[`InferenceSlicer`](detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer)
+[`InferenceSlicer`](/latest/detection/tools/inference_slicer/#supervision.detection.tools.inference_slicer.InferenceSlicer)
 processes high-resolution images by dividing them into smaller segments, detecting
 objects within each, and aggregating the results.
 

From d41caed36f28bd08be407f1636b2ea5f7a9cf36a Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Tue, 26 Mar 2024 18:38:04 +0300
Subject: [PATCH 044/188] =?UTF-8?q?ci:=20=F0=9F=91=B7=20publish=20pypi=20o?=
 =?UTF-8?q?n=20branch=20removed?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 .github/workflows/publish.yml | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
index bd748b061..76d1c67c1 100644
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@@ -3,8 +3,6 @@ on:
   push:
     tags:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]'
-    branches:
-      - main
 
   # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
@@ -14,7 +12,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.8]
+        python-version: [3.10]
     steps:
       - name: 🛎️ Checkout
         uses: actions/checkout@v4

From c67078b53c8a7fb6c60f4b1f7568e160400ac9a2 Mon Sep 17 00:00:00 2001
From: Griffin-Sullivan <gsulliva@redhat.com>
Date: Mon, 25 Mar 2024 18:03:57 -0400
Subject: [PATCH 045/188] Add segmentation model support to from_transformers

---
 supervision/detection/core.py | 25 +++++++++++++++++++------
 1 file changed, 19 insertions(+), 6 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index f170563ca..0af7c12e8 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -14,6 +14,7 @@
     get_data_item,
     is_data_equal,
     mask_non_max_suppression,
+    mask_to_xyxy,
     merge_data,
     process_roboflow_result,
     validate_detections_fields,
@@ -390,18 +391,30 @@ def from_mmdetection(cls, mmdet_results) -> Detections:
     @classmethod
     def from_transformers(cls, transformers_results: dict) -> Detections:
         """
-        Creates a Detections instance from object detection
+        Creates a Detections instance from object detection or segmentation
         [transformer](https://github.com/huggingface/transformers) inference result.
 
         Returns:
             Detections: A new Detections object.
         """
+        boxes = transformers_results.get("boxes")
 
-        return cls(
-            xyxy=transformers_results["boxes"].cpu().numpy(),
-            confidence=transformers_results["scores"].cpu().numpy(),
-            class_id=transformers_results["labels"].cpu().numpy().astype(int),
-        )
+        # If the boxes key is in the transformers_results then we know it's an 
+        # object detection result. Else, we can assume it's a segmentation model
+        if boxes:
+            return cls(
+                xyxy=transformers_results["boxes"].cpu().numpy(),
+                confidence=transformers_results["scores"].cpu().numpy(),
+                class_id=transformers_results["labels"].cpu().numpy().astype(int),
+            )
+        else:
+            masks = transformers_results["masks"].cpu().numpy().astype(bool)
+            return cls(
+                xyxy=mask_to_xyxy(masks),
+                mask=masks,
+                confidence=transformers_results["scores"].cpu().numpy(),
+                class_id=transformers_results["labels"].cpu().numpy().astype(int),
+            )
 
     @classmethod
     def from_detectron2(cls, detectron2_results) -> Detections:

From 13f85ae6cc49e204bdcd932fbafb824c7809690d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 26 Mar 2024 21:05:02 +0000
Subject: [PATCH 046/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 0af7c12e8..60ff07f33 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -399,7 +399,7 @@ def from_transformers(cls, transformers_results: dict) -> Detections:
         """
         boxes = transformers_results.get("boxes")
 
-        # If the boxes key is in the transformers_results then we know it's an 
+        # If the boxes key is in the transformers_results then we know it's an
         # object detection result. Else, we can assume it's a segmentation model
         if boxes:
             return cls(

From 725d95c6ce9cde2455315fb12a6f9717805a564e Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Wed, 27 Mar 2024 00:12:12 +0100
Subject: [PATCH 047/188] time in zone / dwell time demo  (#1026)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* initial commit

* initial stream processing script

* fix(pre_commit): 🎨 auto format pre-commit hooks

* work in progress

* fix(pre_commit): 🎨 auto format pre-commit hooks

* work in progress

* fix(pre_commit): 🎨 auto format pre-commit hooks

* ultralytics file and stream versions ready

* fix(pre_commit): 🎨 auto format pre-commit hooks

* ultralytics file and stream versions ready

* class based filtering

* fix(pre_commit): 🎨 auto format pre-commit hooks

* timer improvements

* inference static file processing script

* fix(pre_commit): 🎨 auto format pre-commit hooks

* inference stream processing script

* fix(pre_commit): 🎨 auto format pre-commit hooks

* all scripts are working

* fix(pre_commit): 🎨 auto format pre-commit hooks

* all video or stream processing scripts refactored

* fix(pre_commit): 🎨 auto format pre-commit hooks

* README.md update

* fix(pre_commit): 🎨 auto format pre-commit hooks

* initial version of draw ones script

* fix(pre_commit): 🎨 auto format pre-commit hooks

* loading image or video, drawing multiple polygons, quiting app, and aborting currently drawn polygon works.

* fix(pre_commit): 🎨 auto format pre-commit hooks

* loading image or video, drawing multiple polygons, quiting app, and aborting currently drawn polygon works.

* fix(pre_commit): 🎨 auto format pre-commit hooks

* Dynamic drawing of currently edited polygon.

* fix(pre_commit): 🎨 auto format pre-commit hooks

* Drawing tool is ready.

* fix(pre_commit): 🎨 auto format pre-commit hooks

* Final touches.

* fix(pre_commit): 🎨 auto format pre-commit hooks

* Update README.md

* fix(pre_commit): 🎨 auto format pre-commit hooks

* Update README.md

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
---
 examples/time_in_zone/.gitignore              |   9 +
 examples/time_in_zone/README.md               | 262 ++++++++++++++++++
 .../time_in_zone/inference_file_example.py    | 132 +++++++++
 .../inference_naive_stream_example.py         | 142 ++++++++++
 .../time_in_zone/inference_stream_example.py  | 158 +++++++++++
 examples/time_in_zone/requirements.txt        |   5 +
 .../scripts/download_from_youtube.py          |  46 +++
 examples/time_in_zone/scripts/draw_zones.py   | 176 ++++++++++++
 .../time_in_zone/scripts/stream_from_file.py  | 104 +++++++
 .../time_in_zone/ultralytics_file_example.py  | 144 ++++++++++
 .../ultralytics_naive_stream_example.py       | 154 ++++++++++
 .../ultralytics_stream_example.py             | 173 ++++++++++++
 examples/time_in_zone/utils/__init__.py       |   0
 examples/time_in_zone/utils/general.py        |  66 +++++
 examples/time_in_zone/utils/timers.py         |  88 ++++++
 15 files changed, 1659 insertions(+)
 create mode 100644 examples/time_in_zone/.gitignore
 create mode 100644 examples/time_in_zone/README.md
 create mode 100644 examples/time_in_zone/inference_file_example.py
 create mode 100644 examples/time_in_zone/inference_naive_stream_example.py
 create mode 100644 examples/time_in_zone/inference_stream_example.py
 create mode 100644 examples/time_in_zone/requirements.txt
 create mode 100644 examples/time_in_zone/scripts/download_from_youtube.py
 create mode 100644 examples/time_in_zone/scripts/draw_zones.py
 create mode 100644 examples/time_in_zone/scripts/stream_from_file.py
 create mode 100644 examples/time_in_zone/ultralytics_file_example.py
 create mode 100644 examples/time_in_zone/ultralytics_naive_stream_example.py
 create mode 100644 examples/time_in_zone/ultralytics_stream_example.py
 create mode 100644 examples/time_in_zone/utils/__init__.py
 create mode 100644 examples/time_in_zone/utils/general.py
 create mode 100644 examples/time_in_zone/utils/timers.py

diff --git a/examples/time_in_zone/.gitignore b/examples/time_in_zone/.gitignore
new file mode 100644
index 000000000..34efd9e06
--- /dev/null
+++ b/examples/time_in_zone/.gitignore
@@ -0,0 +1,9 @@
+data/
+venv*/
+*.pt
+*.pth
+*.mp4
+*.mov
+*.png
+*.jpg
+*.jpeg
diff --git a/examples/time_in_zone/README.md b/examples/time_in_zone/README.md
new file mode 100644
index 000000000..3898c4525
--- /dev/null
+++ b/examples/time_in_zone/README.md
@@ -0,0 +1,262 @@
+# time in zone
+
+## 👋 hello
+
+Practical demonstration on leveraging computer vision for analyzing wait times and
+monitoring the duration that objects or individuals spend in predefined areas of video
+frames. This example project, perfect for retail analytics or traffic management
+applications.
+
+https://github.com/roboflow/supervision/assets/26109316/d051cc8a-dd15-41d4-aa36-d38b86334c39
+
+## 💻 install
+
+- clone repository and navigate to example directory
+
+  ```bash
+  git clone https://github.com/roboflow/supervision.git
+  cd supervision/examples/time_in_zone
+  ```
+
+- setup python environment and activate it [optional]
+
+  ```bash
+  python3 -m venv venv
+  source venv/bin/activate
+  ```
+
+- install required dependencies
+
+  ```bash
+  pip install -r requirements.txt
+  ```
+
+## 🛠 scripts
+
+### `download_from_youtube`
+
+This script allows you to download a video from YouTube.
+
+- `--url`: The full URL of the YouTube video you wish to download.
+- `--output_path` (optional): Specifies the directory where the video will be saved.
+- `--file_name` (optional): Sets the name of the saved video file.
+
+```bash
+python scripts/download_from_youtube.py \
+--url "https://youtu.be/8zyEwAa50Q" \
+--output_path "data/checkout" \
+--file_name "video.mp4"
+```
+
+```bash
+python scripts/download_from_youtube.py \
+--url "https://youtu.be/MNn9qKG2UFI" \
+--output_path "data/traffic" \
+--file_name "video.mp4"
+```
+
+### `stream_from_file`
+
+This script allows you to stream video files from a directory. It's an awesome way to
+mock a live video stream for local testing. Video will be streamed in a loop under
+`rtsp://localhost:8554/live0.stream` URL. This script requires docker to be installed.
+
+- `--video_directory`: Directory containing video files to stream.
+- `--number_of_streams`: Number of video files to stream.
+
+```bash
+python scripts/stream_from_file.py \
+--video_directory "data/checkout" \
+--number_of_streams 1
+```
+
+```bash
+python scripts/stream_from_file.py \
+--video_directory "data/traffic" \
+--number_of_streams 1
+```
+
+### `draw_zones`
+
+If you want to test zone time in zone analysis on your own video, you can use this
+script to design custom zones and save results as a JSON file. The script will open a
+window where you can draw polygons on the source image or video file. The polygons will
+be saved as a JSON file.
+
+- `--source_path`: Path to the source image or video file for drawing polygons.
+- `--zone_configuration_path`: Path where the polygon annotations will be saved as a JSON file.
+
+
+- `enter` - finish drawing the current polygon.
+- `escape` - cancel drawing the current polygon.
+- `q` - quit the drawing window.
+- `s` - save zone configuration to a JSON file.
+
+```bash
+python scripts/draw_zones.py \
+--source_path "data/checkout/video.mp4" \
+--zone_configuration_path "data/checkout/custom_config.json"
+```
+
+```bash
+python scripts/draw_zones.py \
+--source_path "data/traffic/video.mp4" \
+--zone_configuration_path "data/traffic/custom_config.json"
+```
+
+https://github.com/roboflow/supervision/assets/26109316/9d514c9e-2a61-418b-ae49-6ac1ad6ae5ac
+
+## 🎬 video & stream processing
+
+### `inference_file_example`
+
+Script to run object detection on a video file using the Roboflow Inference model.
+
+  - `--zone_configuration_path`: Path to the zone configuration JSON file.
+  - `--source_video_path`: Path to the source video file.
+  - `--model_id`: Roboflow model ID.
+  - `--classes`: List of class IDs to track. If empty, all classes are tracked.
+  - `--confidence_threshold`: Confidence level for detections (`0` to `1`). Default is `0.3`.
+  - `--iou_threshold`: IOU threshold for non-max suppression. Default is `0.7`.
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/checkout/config.json" \
+--source_video_path "data/checkout/video.mp4" \
+--model_id "yolov8x-640" \
+--classes 0 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+https://github.com/roboflow/supervision/assets/26109316/d051cc8a-dd15-41d4-aa36-d38b86334c39
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/traffic/config.json" \
+--source_video_path "data/traffic/video.mp4" \
+--model_id "yolov8x-640" \
+--classes 2 5 6 7 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+https://github.com/roboflow/supervision/assets/26109316/5ec896d7-4b39-4426-8979-11e71666878b
+
+### `inference_stream_example`
+
+Script to run object detection on a video stream using the Roboflow Inference model.
+
+  - `--zone_configuration_path`: Path to the zone configuration JSON file.
+  - `--rtsp_url`: Complete RTSP URL for the video stream.
+  - `--model_id`: Roboflow model ID.
+  - `--classes`: List of class IDs to track. If empty, all classes are tracked.
+  - `--confidence_threshold`: Confidence level for detections (`0` to `1`). Default is `0.3`.
+  - `--iou_threshold`: IOU threshold for non-max suppression. Default is `0.7`.
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/checkout/config.json" \
+--rtsp_url "rtsp://localhost:8554/live0.stream" \
+--model_id "yolov8x-640" \
+--classes 0 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/traffic/config.json" \
+--rtsp_url "rtsp://localhost:8554/live0.stream" \
+--model_id "yolov8x-640" \
+--classes 2 5 6 7 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+<details>
+<summary>👉 show ultralytics examples</summary>
+
+### `ultralytics_file_example`
+
+Script to run object detection on a video file using the Ultralytics YOLOv8 model.
+
+  - `--zone_configuration_path`: Path to the zone configuration JSON file.
+  - `--source_video_path`: Path to the source video file.
+  - `--weights`: Path to the model weights file. Default is `'yolov8s.pt'`.
+  - `--device`: Computation device (`'cpu'`, `'mps'` or `'cuda'`). Default is `'cpu'`.
+  - `--classes`: List of class IDs to track. If empty, all classes are tracked.
+  - `--confidence_threshold`: Confidence level for detections (`0` to `1`). Default is `0.3`.
+  - `--iou_threshold`: IOU threshold for non-max suppression. Default is `0.7`.
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/checkout/config.json" \
+--source_video_path "data/checkout/video.mp4" \
+--weights "yolov8x.pt" \
+--device "cpu" \
+--classes 0 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/traffic/config.json" \
+--source_video_path "data/traffic/video.mp4" \
+--weights "yolov8x.pt" \
+--device "cpu" \
+--classes 2 5 6 7 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+### `ultralytics_stream_example`
+
+Script to run object detection on a video stream using the Ultralytics YOLOv8 model.
+
+  - `--zone_configuration_path`: Path to the zone configuration JSON file.
+  - `--rtsp_url`: Complete RTSP URL for the video stream.
+  - `--weights`: Path to the model weights file. Default is `'yolov8s.pt'`.
+  - `--device`: Computation device (`'cpu'`, `'mps'` or `'cuda'`). Default is `'cpu'`.
+  - `--classes`: List of class IDs to track. If empty, all classes are tracked.
+  - `--confidence_threshold`: Confidence level for detections (`0` to `1`). Default is `0.3`.
+  - `--iou_threshold`: IOU threshold for non-max suppression. Default is `0.7`.
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/checkout/config.json" \
+--rtsp_url "rtsp://localhost:8554/live0.stream" \
+--weights "yolov8x.pt" \
+--device "cpu" \
+--classes 0 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+```bash
+python inference_file_example.py \
+--zone_configuration_path "data/traffic/config.json" \
+--rtsp_url "rtsp://localhost:8554/live0.stream" \
+--weights "yolov8x.pt" \
+--device "cpu" \
+--classes 2 5 6 7 \
+--confidence_threshold 0.3 \
+--iou_threshold 0.7
+```
+
+</details>
+
+## © license
+
+This demo integrates two main components, each with its own licensing:
+
+- ultralytics: The object detection model used in this demo, YOLOv8, is distributed
+  under the [AGPL-3.0 license](https://github.com/ultralytics/ultralytics/blob/main/LICENSE).
+  You can find more details about this license here.
+
+- supervision: The analytics code that powers the zone-based analysis in this demo is
+  based on the Supervision library, which is licensed under the
+  [MIT license](https://github.com/roboflow/supervision/blob/develop/LICENSE.md). This
+  makes the Supervision part of the code fully open source and freely usable in your
+  projects.
diff --git a/examples/time_in_zone/inference_file_example.py b/examples/time_in_zone/inference_file_example.py
new file mode 100644
index 000000000..5feb1d836
--- /dev/null
+++ b/examples/time_in_zone/inference_file_example.py
@@ -0,0 +1,132 @@
+import argparse
+from typing import List
+
+import cv2
+import numpy as np
+from inference import get_model
+from utils.general import find_in_list, load_zones_config
+from utils.timers import FPSBasedTimer
+
+import supervision as sv
+
+COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
+COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
+LABEL_ANNOTATOR = sv.LabelAnnotator(
+    color=COLORS, text_color=sv.Color.from_hex("#000000")
+)
+
+
+def main(
+    source_video_path: str,
+    zone_configuration_path: str,
+    model_id: str,
+    confidence: float,
+    iou: float,
+    classes: List[int],
+) -> None:
+    model = get_model(model_id=model_id)
+    tracker = sv.ByteTrack(minimum_matching_threshold=0.5)
+    video_info = sv.VideoInfo.from_video_path(video_path=source_video_path)
+    frames_generator = sv.get_video_frames_generator(source_video_path)
+
+    frame = next(frames_generator)
+    resolution_wh = frame.shape[1], frame.shape[0]
+
+    polygons = load_zones_config(file_path=zone_configuration_path)
+    zones = [
+        sv.PolygonZone(
+            polygon=polygon,
+            frame_resolution_wh=resolution_wh,
+            triggering_anchors=(sv.Position.CENTER,),
+        )
+        for polygon in polygons
+    ]
+    timers = [FPSBasedTimer(video_info.fps) for _ in zones]
+
+    for frame in frames_generator:
+        results = model.infer(frame, confidence=confidence, iou_threshold=iou)[0]
+        detections = sv.Detections.from_inference(results)
+        detections = detections[find_in_list(detections.class_id, classes)]
+        detections = tracker.update_with_detections(detections)
+
+        annotated_frame = frame.copy()
+
+        for idx, zone in enumerate(zones):
+            annotated_frame = sv.draw_polygon(
+                scene=annotated_frame, polygon=zone.polygon, color=COLORS.by_idx(idx)
+            )
+
+            detections_in_zone = detections[zone.trigger(detections)]
+            time_in_zone = timers[idx].tick(detections_in_zone)
+            custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
+
+            annotated_frame = COLOR_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                custom_color_lookup=custom_color_lookup,
+            )
+            labels = [
+                f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
+                for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
+            ]
+            annotated_frame = LABEL_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                labels=labels,
+                custom_color_lookup=custom_color_lookup,
+            )
+
+        cv2.imshow("Processed Video", annotated_frame)
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculating detections dwell time in zones, using video file."
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path to the zone configuration JSON file.",
+    )
+    parser.add_argument(
+        "--source_video_path",
+        type=str,
+        required=True,
+        help="Path to the source video file.",
+    )
+    parser.add_argument(
+        "--model_id", type=str, default="yolov8s-640", help="Roboflow model ID."
+    )
+    parser.add_argument(
+        "--confidence_threshold",
+        type=float,
+        default=0.3,
+        help="Confidence level for detections (0 to 1). Default is 0.3.",
+    )
+    parser.add_argument(
+        "--iou_threshold",
+        default=0.7,
+        type=float,
+        help="IOU threshold for non-max suppression. Default is 0.7.",
+    )
+    parser.add_argument(
+        "--classes",
+        nargs="*",
+        type=int,
+        default=[],
+        help="List of class IDs to track. If empty, all classes are tracked.",
+    )
+    args = parser.parse_args()
+
+    main(
+        source_video_path=args.source_video_path,
+        zone_configuration_path=args.zone_configuration_path,
+        model_id=args.model_id,
+        confidence=args.confidence_threshold,
+        iou=args.iou_threshold,
+        classes=args.classes,
+    )
diff --git a/examples/time_in_zone/inference_naive_stream_example.py b/examples/time_in_zone/inference_naive_stream_example.py
new file mode 100644
index 000000000..dd2d68a5d
--- /dev/null
+++ b/examples/time_in_zone/inference_naive_stream_example.py
@@ -0,0 +1,142 @@
+import argparse
+from typing import List
+
+import cv2
+import numpy as np
+from inference import get_model
+from utils.general import find_in_list, get_stream_frames_generator, load_zones_config
+from utils.timers import ClockBasedTimer
+
+import supervision as sv
+
+COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
+COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
+LABEL_ANNOTATOR = sv.LabelAnnotator(
+    color=COLORS, text_color=sv.Color.from_hex("#000000")
+)
+
+
+def main(
+    rtsp_url: str,
+    zone_configuration_path: str,
+    model_id: str,
+    confidence: float,
+    iou: float,
+    classes: List[int],
+) -> None:
+    model = get_model(model_id=model_id)
+    tracker = sv.ByteTrack(minimum_matching_threshold=0.5)
+    frames_generator = get_stream_frames_generator(rtsp_url=rtsp_url)
+    fps_monitor = sv.FPSMonitor()
+
+    frame = next(frames_generator)
+    resolution_wh = frame.shape[1], frame.shape[0]
+
+    polygons = load_zones_config(file_path=zone_configuration_path)
+    zones = [
+        sv.PolygonZone(
+            polygon=polygon,
+            frame_resolution_wh=resolution_wh,
+            triggering_anchors=(sv.Position.CENTER,),
+        )
+        for polygon in polygons
+    ]
+    timers = [ClockBasedTimer() for _ in zones]
+
+    for frame in frames_generator:
+        fps_monitor.tick()
+        fps = fps_monitor.fps
+
+        results = model.infer(frame, confidence=confidence, iou_threshold=iou)[0]
+        detections = sv.Detections.from_inference(results)
+        detections = detections[find_in_list(detections.class_id, classes)]
+        detections = tracker.update_with_detections(detections)
+
+        annotated_frame = frame.copy()
+        annotated_frame = sv.draw_text(
+            scene=annotated_frame,
+            text=f"{fps:.1f}",
+            text_anchor=sv.Point(40, 30),
+            background_color=sv.Color.from_hex("#A351FB"),
+            text_color=sv.Color.from_hex("#000000"),
+        )
+
+        for idx, zone in enumerate(zones):
+            annotated_frame = sv.draw_polygon(
+                scene=annotated_frame, polygon=zone.polygon, color=COLORS.by_idx(idx)
+            )
+
+            detections_in_zone = detections[zone.trigger(detections)]
+            time_in_zone = timers[idx].tick(detections_in_zone)
+            custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
+
+            annotated_frame = COLOR_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                custom_color_lookup=custom_color_lookup,
+            )
+            labels = [
+                f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
+                for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
+            ]
+            annotated_frame = LABEL_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                labels=labels,
+                custom_color_lookup=custom_color_lookup,
+            )
+
+        cv2.imshow("Processed Video", annotated_frame)
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculating detections dwell time in zones, using RTSP stream."
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path to the zone configuration JSON file.",
+    )
+    parser.add_argument(
+        "--rtsp_url",
+        type=str,
+        required=True,
+        help="Complete RTSP URL for the video stream.",
+    )
+    parser.add_argument(
+        "--model_id", type=str, default="yolov8s-640", help="Roboflow model ID."
+    )
+    parser.add_argument(
+        "--confidence_threshold",
+        type=float,
+        default=0.3,
+        help="Confidence level for detections (0 to 1). Default is 0.3.",
+    )
+    parser.add_argument(
+        "--iou_threshold",
+        default=0.7,
+        type=float,
+        help="IOU threshold for non-max suppression. Default is 0.7.",
+    )
+    parser.add_argument(
+        "--classes",
+        nargs="*",
+        type=int,
+        default=[],
+        help="List of class IDs to track. If empty, all classes are tracked.",
+    )
+    args = parser.parse_args()
+
+    main(
+        rtsp_url=args.rtsp_url,
+        zone_configuration_path=args.zone_configuration_path,
+        model_id=args.model_id,
+        confidence=args.confidence_threshold,
+        iou=args.iou_threshold,
+        classes=args.classes,
+    )
diff --git a/examples/time_in_zone/inference_stream_example.py b/examples/time_in_zone/inference_stream_example.py
new file mode 100644
index 000000000..e1fae57f9
--- /dev/null
+++ b/examples/time_in_zone/inference_stream_example.py
@@ -0,0 +1,158 @@
+import argparse
+from typing import List
+
+import cv2
+import numpy as np
+from inference import InferencePipeline
+from inference.core.interfaces.camera.entities import VideoFrame
+from utils.general import find_in_list, load_zones_config
+from utils.timers import ClockBasedTimer
+
+import supervision as sv
+
+COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
+COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
+LABEL_ANNOTATOR = sv.LabelAnnotator(
+    color=COLORS, text_color=sv.Color.from_hex("#000000")
+)
+
+
+class CustomSink:
+    def __init__(self, zone_configuration_path: str, classes: List[int]):
+        self.classes = classes
+        self.tracker = sv.ByteTrack(minimum_matching_threshold=0.5)
+        self.fps_monitor = sv.FPSMonitor()
+        self.polygons = load_zones_config(file_path=zone_configuration_path)
+        self.timers = [ClockBasedTimer() for _ in self.polygons]
+        self.zones = None
+
+    def on_prediction(self, result: dict, frame: VideoFrame) -> None:
+        if self.zones is None:
+            resolution_wh = frame.image.shape[1], frame.image.shape[0]
+            self.zones = [
+                sv.PolygonZone(
+                    polygon=polygon,
+                    frame_resolution_wh=resolution_wh,
+                    triggering_anchors=(sv.Position.CENTER,),
+                )
+                for polygon in self.polygons
+            ]
+
+        self.fps_monitor.tick()
+        fps = self.fps_monitor.fps
+
+        detections = sv.Detections.from_inference(result)
+        detections = detections[find_in_list(detections.class_id, self.classes)]
+        detections = self.tracker.update_with_detections(detections)
+
+        annotated_frame = frame.image.copy()
+        annotated_frame = sv.draw_text(
+            scene=annotated_frame,
+            text=f"{fps:.1f}",
+            text_anchor=sv.Point(40, 30),
+            background_color=sv.Color.from_hex("#A351FB"),
+            text_color=sv.Color.from_hex("#000000"),
+        )
+
+        for idx, zone in enumerate(self.zones):
+            annotated_frame = sv.draw_polygon(
+                scene=annotated_frame, polygon=zone.polygon, color=COLORS.by_idx(idx)
+            )
+
+            detections_in_zone = detections[zone.trigger(detections)]
+            time_in_zone = self.timers[idx].tick(detections_in_zone)
+            custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
+
+            annotated_frame = COLOR_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                custom_color_lookup=custom_color_lookup,
+            )
+            labels = [
+                f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
+                for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
+            ]
+            annotated_frame = LABEL_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                labels=labels,
+                custom_color_lookup=custom_color_lookup,
+            )
+        cv2.imshow("Processed Video", annotated_frame)
+        cv2.waitKey(1)
+
+
+def main(
+    rtsp_url: str,
+    zone_configuration_path: str,
+    model_id: str,
+    confidence: float,
+    iou: float,
+    classes: List[int],
+) -> None:
+    sink = CustomSink(zone_configuration_path=zone_configuration_path, classes=classes)
+
+    pipeline = InferencePipeline.init(
+        model_id=model_id,
+        video_reference=rtsp_url,
+        on_prediction=sink.on_prediction,
+        confidence=confidence,
+        iou_threshold=iou,
+    )
+
+    pipeline.start()
+
+    try:
+        pipeline.join()
+    except KeyboardInterrupt:
+        pipeline.terminate()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculating detections dwell time in zones, using RTSP stream."
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path to the zone configuration JSON file.",
+    )
+    parser.add_argument(
+        "--rtsp_url",
+        type=str,
+        required=True,
+        help="Complete RTSP URL for the video stream.",
+    )
+    parser.add_argument(
+        "--model_id", type=str, default="yolov8s-640", help="Roboflow model ID."
+    )
+    parser.add_argument(
+        "--confidence_threshold",
+        type=float,
+        default=0.3,
+        help="Confidence level for detections (0 to 1). Default is 0.3.",
+    )
+    parser.add_argument(
+        "--iou_threshold",
+        default=0.7,
+        type=float,
+        help="IOU threshold for non-max suppression. Default is 0.7.",
+    )
+    parser.add_argument(
+        "--classes",
+        nargs="*",
+        type=int,
+        default=[],
+        help="List of class IDs to track. If empty, all classes are tracked.",
+    )
+    args = parser.parse_args()
+
+    main(
+        rtsp_url=args.rtsp_url,
+        zone_configuration_path=args.zone_configuration_path,
+        model_id=args.model_id,
+        confidence=args.confidence_threshold,
+        iou=args.iou_threshold,
+        classes=args.classes,
+    )
diff --git a/examples/time_in_zone/requirements.txt b/examples/time_in_zone/requirements.txt
new file mode 100644
index 000000000..fa17b9864
--- /dev/null
+++ b/examples/time_in_zone/requirements.txt
@@ -0,0 +1,5 @@
+opencv-python
+supervision
+ultralytics
+inference
+pytube
diff --git a/examples/time_in_zone/scripts/download_from_youtube.py b/examples/time_in_zone/scripts/download_from_youtube.py
new file mode 100644
index 000000000..ff7d94c3f
--- /dev/null
+++ b/examples/time_in_zone/scripts/download_from_youtube.py
@@ -0,0 +1,46 @@
+import argparse
+import os
+from typing import Optional
+
+from pytube import YouTube
+
+
+def main(url: str, output_path: Optional[str], file_name: Optional[str]) -> None:
+    yt = YouTube(url)
+    stream = yt.streams.get_highest_resolution()
+
+    if not os.path.exists(output_path):
+        os.makedirs(output_path)
+
+    stream.download(output_path=output_path, filename=file_name)
+    final_name = file_name if file_name else yt.title
+    final_path = output_path if output_path else "current directory"
+    print(f"Download completed! Video saved as '{final_name}' in '{final_path}'.")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Download a specific YouTube video by providing its URL."
+    )
+    parser.add_argument(
+        "--url",
+        type=str,
+        required=True,
+        help="The full URL of the YouTube video you wish to download.",
+    )
+    parser.add_argument(
+        "--output_path",
+        type=str,
+        default="data/source",
+        required=False,
+        help="Optional. Specifies the directory where the video will be saved.",
+    )
+    parser.add_argument(
+        "--file_name",
+        type=str,
+        default="video.mp4",
+        required=False,
+        help="Optional. Sets the name of the saved video file.",
+    )
+    args = parser.parse_args()
+    main(url=args.url, output_path=args.output_path, file_name=args.file_name)
diff --git a/examples/time_in_zone/scripts/draw_zones.py b/examples/time_in_zone/scripts/draw_zones.py
new file mode 100644
index 000000000..3afae9e70
--- /dev/null
+++ b/examples/time_in_zone/scripts/draw_zones.py
@@ -0,0 +1,176 @@
+import argparse
+import json
+import os
+from typing import Any, Optional, Tuple
+
+import cv2
+import numpy as np
+
+import supervision as sv
+
+KEY_ENTER = 13
+KEY_NEWLINE = 10
+KEY_ESCAPE = 27
+KEY_QUIT = ord("q")
+KEY_SAVE = ord("s")
+
+THICKNESS = 2
+COLORS = sv.ColorPalette.DEFAULT
+WINDOW_NAME = "Draw Zones"
+POLYGONS = [[]]
+
+current_mouse_position: Optional[Tuple[int, int]] = None
+
+
+def resolve_source(source_path: str) -> Optional[np.ndarray]:
+    if not os.path.exists(source_path):
+        return None
+
+    image = cv2.imread(source_path)
+    if image is not None:
+        return image
+
+    frame_generator = sv.get_video_frames_generator(source_path=source_path)
+    frame = next(frame_generator)
+    return frame
+
+
+def mouse_event(event: int, x: int, y: int, flags: int, param: Any) -> None:
+    global current_mouse_position
+    if event == cv2.EVENT_MOUSEMOVE:
+        current_mouse_position = (x, y)
+    elif event == cv2.EVENT_LBUTTONDOWN:
+        POLYGONS[-1].append((x, y))
+
+
+def redraw(image: np.ndarray, original_image: np.ndarray) -> None:
+    global POLYGONS, current_mouse_position
+    image[:] = original_image.copy()
+    for idx, polygon in enumerate(POLYGONS):
+        color = (
+            COLORS.by_idx(idx).as_bgr()
+            if idx < len(POLYGONS) - 1
+            else sv.Color.WHITE.as_bgr()
+        )
+
+        if len(polygon) > 1:
+            for i in range(1, len(polygon)):
+                cv2.line(
+                    img=image,
+                    pt1=polygon[i - 1],
+                    pt2=polygon[i],
+                    color=color,
+                    thickness=THICKNESS,
+                )
+            if idx < len(POLYGONS) - 1:
+                cv2.line(
+                    img=image,
+                    pt1=polygon[-1],
+                    pt2=polygon[0],
+                    color=color,
+                    thickness=THICKNESS,
+                )
+        if idx == len(POLYGONS) - 1 and current_mouse_position is not None and polygon:
+            cv2.line(
+                img=image,
+                pt1=polygon[-1],
+                pt2=current_mouse_position,
+                color=color,
+                thickness=THICKNESS,
+            )
+    cv2.imshow(WINDOW_NAME, image)
+
+
+def close_and_finalize_polygon(image: np.ndarray, original_image: np.ndarray) -> None:
+    if len(POLYGONS[-1]) > 2:
+        cv2.line(
+            img=image,
+            pt1=POLYGONS[-1][-1],
+            pt2=POLYGONS[-1][0],
+            color=COLORS.by_idx(0).as_bgr(),
+            thickness=THICKNESS,
+        )
+    POLYGONS.append([])
+    image[:] = original_image.copy()
+    redraw_polygons(image)
+    cv2.imshow(WINDOW_NAME, image)
+
+
+def redraw_polygons(image: np.ndarray) -> None:
+    for idx, polygon in enumerate(POLYGONS[:-1]):
+        if len(polygon) > 1:
+            color = COLORS.by_idx(idx).as_bgr()
+            for i in range(len(polygon) - 1):
+                cv2.line(
+                    img=image,
+                    pt1=polygon[i],
+                    pt2=polygon[i + 1],
+                    color=color,
+                    thickness=THICKNESS,
+                )
+            cv2.line(
+                img=image,
+                pt1=polygon[-1],
+                pt2=polygon[0],
+                color=color,
+                thickness=THICKNESS,
+            )
+
+
+def save_polygons_to_json(polygons, target_path):
+    data_to_save = polygons if polygons[-1] else polygons[:-1]
+    with open(target_path, "w") as f:
+        json.dump(data_to_save, f)
+
+
+def main(source_path: str, zone_configuration_path: str) -> None:
+    global current_mouse_position
+    original_image = resolve_source(source_path=source_path)
+    if original_image is None:
+        print("Failed to load source image.")
+        return
+
+    image = original_image.copy()
+    cv2.imshow(WINDOW_NAME, image)
+    cv2.setMouseCallback(WINDOW_NAME, mouse_event, image)
+
+    while True:
+        key = cv2.waitKey(1) & 0xFF
+        if key == KEY_ENTER or key == KEY_NEWLINE:
+            close_and_finalize_polygon(image, original_image)
+        elif key == KEY_ESCAPE:
+            POLYGONS[-1] = []
+            current_mouse_position = None
+        elif key == KEY_SAVE:
+            save_polygons_to_json(POLYGONS, zone_configuration_path)
+            print(f"Polygons saved to {zone_configuration_path}")
+            break
+        redraw(image, original_image)
+        if key == KEY_QUIT:
+            break
+
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Interactively draw polygons on images or video frames and save "
+        "the annotations."
+    )
+    parser.add_argument(
+        "--source_path",
+        type=str,
+        required=True,
+        help="Path to the source image or video file for drawing polygons.",
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path where the polygon annotations will be saved as a JSON file.",
+    )
+    arguments = parser.parse_args()
+    main(
+        source_path=arguments.source_path,
+        zone_configuration_path=arguments.zone_configuration_path,
+    )
diff --git a/examples/time_in_zone/scripts/stream_from_file.py b/examples/time_in_zone/scripts/stream_from_file.py
new file mode 100644
index 000000000..23588f680
--- /dev/null
+++ b/examples/time_in_zone/scripts/stream_from_file.py
@@ -0,0 +1,104 @@
+import argparse
+import os
+import subprocess
+import tempfile
+from glob import glob
+from threading import Thread
+
+import yaml
+
+SERVER_CONFIG = {"protocols": ["tcp"], "paths": {"all": {"source": "publisher"}}}
+BASE_STREAM_URL = "rtsp://localhost:8554/live"
+
+
+def main(video_directory: str, number_of_streams: int) -> None:
+    video_files = find_video_files_in_directory(video_directory, number_of_streams)
+    try:
+        with tempfile.TemporaryDirectory() as temporary_directory:
+            config_file_path = create_server_config_file(temporary_directory)
+            run_rtsp_server(config_path=config_file_path)
+            stream_videos(video_files)
+    finally:
+        stop_rtsp_server()
+
+
+def find_video_files_in_directory(directory: str, limit: int) -> list:
+    video_formats = ["*.mp4", "*.webm"]
+    video_paths = []
+    for video_format in video_formats:
+        video_paths.extend(glob(os.path.join(directory, video_format)))
+    return video_paths[:limit]
+
+
+def create_server_config_file(directory: str) -> str:
+    config_path = os.path.join(directory, "rtsp-simple-server.yml")
+    with open(config_path, "w") as config_file:
+        yaml.dump(SERVER_CONFIG, config_file)
+    return config_path
+
+
+def run_rtsp_server(config_path: str) -> None:
+    command = (
+        "docker run --rm --name rtsp_server -d -v "
+        f"{config_path}:/rtsp-simple-server.yml -p 8554:8554 "
+        "aler9/rtsp-simple-server:v1.3.0"
+    )
+    if run_command(command.split()) != 0:
+        raise RuntimeError("Could not start the RTSP server!")
+
+
+def stop_rtsp_server() -> None:
+    run_command("docker kill rtsp_server".split())
+
+
+def stream_videos(video_files: list) -> None:
+    threads = []
+    for index, video_file in enumerate(video_files):
+        stream_url = f"{BASE_STREAM_URL}{index}.stream"
+        print(f"Streaming {video_file} under {stream_url}")
+        thread = stream_video_to_url(video_file, stream_url)
+        threads.append(thread)
+    for thread in threads:
+        thread.join()
+
+
+def stream_video_to_url(video_path: str, stream_url: str) -> Thread:
+    command = (
+        f"ffmpeg -re -stream_loop -1 -i {video_path} "
+        f"-f rtsp -rtsp_transport tcp {stream_url}"
+    )
+    return run_command_in_thread(command.split())
+
+
+def run_command_in_thread(command: list) -> Thread:
+    thread = Thread(target=run_command, args=(command,))
+    thread.start()
+    return thread
+
+
+def run_command(command: list) -> int:
+    process = subprocess.run(command)
+    return process.returncode
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Script to stream videos using RTSP protocol."
+    )
+    parser.add_argument(
+        "--video_directory",
+        type=str,
+        required=True,
+        help="Directory containing video files to stream.",
+    )
+    parser.add_argument(
+        "--number_of_streams",
+        type=int,
+        default=6,
+        help="Number of video files to stream.",
+    )
+    arguments = parser.parse_args()
+    main(
+        video_directory=arguments.video_directory,
+        number_of_streams=arguments.number_of_streams,
+    )
diff --git a/examples/time_in_zone/ultralytics_file_example.py b/examples/time_in_zone/ultralytics_file_example.py
new file mode 100644
index 000000000..fe8ce58df
--- /dev/null
+++ b/examples/time_in_zone/ultralytics_file_example.py
@@ -0,0 +1,144 @@
+import argparse
+from typing import List
+
+import cv2
+import numpy as np
+from ultralytics import YOLO
+from utils.general import find_in_list, load_zones_config
+from utils.timers import FPSBasedTimer
+
+import supervision as sv
+
+COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
+COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
+LABEL_ANNOTATOR = sv.LabelAnnotator(
+    color=COLORS, text_color=sv.Color.from_hex("#000000")
+)
+
+
+def main(
+    source_video_path: str,
+    zone_configuration_path: str,
+    weights: str,
+    device: str,
+    confidence: float,
+    iou: float,
+    classes: List[int],
+) -> None:
+    model = YOLO(weights)
+    tracker = sv.ByteTrack(minimum_matching_threshold=0.5)
+    video_info = sv.VideoInfo.from_video_path(video_path=source_video_path)
+    frames_generator = sv.get_video_frames_generator(source_video_path)
+
+    frame = next(frames_generator)
+    resolution_wh = frame.shape[1], frame.shape[0]
+
+    polygons = load_zones_config(file_path=zone_configuration_path)
+    zones = [
+        sv.PolygonZone(
+            polygon=polygon,
+            frame_resolution_wh=resolution_wh,
+            triggering_anchors=(sv.Position.CENTER,),
+        )
+        for polygon in polygons
+    ]
+    timers = [FPSBasedTimer(video_info.fps) for _ in zones]
+
+    for frame in frames_generator:
+        results = model(frame, verbose=False, device=device, conf=confidence)[0]
+        detections = sv.Detections.from_ultralytics(results)
+        detections = detections[find_in_list(detections.class_id, classes)]
+        detections = detections.with_nms(threshold=iou)
+        detections = tracker.update_with_detections(detections)
+
+        annotated_frame = frame.copy()
+
+        for idx, zone in enumerate(zones):
+            annotated_frame = sv.draw_polygon(
+                scene=annotated_frame, polygon=zone.polygon, color=COLORS.by_idx(idx)
+            )
+
+            detections_in_zone = detections[zone.trigger(detections)]
+            time_in_zone = timers[idx].tick(detections_in_zone)
+            custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
+
+            annotated_frame = COLOR_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                custom_color_lookup=custom_color_lookup,
+            )
+            labels = [
+                f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
+                for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
+            ]
+            annotated_frame = LABEL_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                labels=labels,
+                custom_color_lookup=custom_color_lookup,
+            )
+
+        cv2.imshow("Processed Video", annotated_frame)
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculating detections dwell time in zones, using video file."
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path to the zone configuration JSON file.",
+    )
+    parser.add_argument(
+        "--source_video_path",
+        type=str,
+        required=True,
+        help="Path to the source video file.",
+    )
+    parser.add_argument(
+        "--weights",
+        type=str,
+        default="yolov8s.pt",
+        help="Path to the model weights file. Default is 'yolov8s.pt'.",
+    )
+    parser.add_argument(
+        "--device",
+        type=str,
+        default="cpu",
+        help="Computation device ('cpu', 'mps' or 'cuda'). Default is 'cpu'.",
+    )
+    parser.add_argument(
+        "--confidence_threshold",
+        type=float,
+        default=0.3,
+        help="Confidence level for detections (0 to 1). Default is 0.3.",
+    )
+    parser.add_argument(
+        "--iou_threshold",
+        default=0.7,
+        type=float,
+        help="IOU threshold for non-max suppression. Default is 0.7.",
+    )
+    parser.add_argument(
+        "--classes",
+        nargs="*",
+        type=int,
+        default=[],
+        help="List of class IDs to track. If empty, all classes are tracked.",
+    )
+    args = parser.parse_args()
+
+    main(
+        source_video_path=args.source_video_path,
+        zone_configuration_path=args.zone_configuration_path,
+        weights=args.weights,
+        device=args.device,
+        confidence=args.confidence_threshold,
+        iou=args.iou_threshold,
+        classes=args.classes,
+    )
diff --git a/examples/time_in_zone/ultralytics_naive_stream_example.py b/examples/time_in_zone/ultralytics_naive_stream_example.py
new file mode 100644
index 000000000..1cc82b446
--- /dev/null
+++ b/examples/time_in_zone/ultralytics_naive_stream_example.py
@@ -0,0 +1,154 @@
+import argparse
+from typing import List
+
+import cv2
+import numpy as np
+from ultralytics import YOLO
+from utils.general import find_in_list, get_stream_frames_generator, load_zones_config
+from utils.timers import ClockBasedTimer
+
+import supervision as sv
+
+COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
+COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
+LABEL_ANNOTATOR = sv.LabelAnnotator(
+    color=COLORS, text_color=sv.Color.from_hex("#000000")
+)
+
+
+def main(
+    rtsp_url: str,
+    zone_configuration_path: str,
+    weights: str,
+    device: str,
+    confidence: float,
+    iou: float,
+    classes: List[int],
+) -> None:
+    model = YOLO(weights)
+    tracker = sv.ByteTrack(minimum_matching_threshold=0.5)
+    frames_generator = get_stream_frames_generator(rtsp_url=rtsp_url)
+    fps_monitor = sv.FPSMonitor()
+
+    frame = next(frames_generator)
+    resolution_wh = frame.shape[1], frame.shape[0]
+
+    polygons = load_zones_config(file_path=zone_configuration_path)
+    zones = [
+        sv.PolygonZone(
+            polygon=polygon,
+            frame_resolution_wh=resolution_wh,
+            triggering_anchors=(sv.Position.CENTER,),
+        )
+        for polygon in polygons
+    ]
+    timers = [ClockBasedTimer() for _ in zones]
+
+    for frame in frames_generator:
+        fps_monitor.tick()
+        fps = fps_monitor.fps
+
+        results = model(frame, verbose=False, device=device, conf=confidence)[0]
+        detections = sv.Detections.from_ultralytics(results)
+        detections = detections[find_in_list(detections.class_id, classes)]
+        detections = detections.with_nms(threshold=iou)
+        detections = tracker.update_with_detections(detections)
+
+        annotated_frame = frame.copy()
+        annotated_frame = sv.draw_text(
+            scene=annotated_frame,
+            text=f"{fps:.1f}",
+            text_anchor=sv.Point(40, 30),
+            background_color=sv.Color.from_hex("#A351FB"),
+            text_color=sv.Color.from_hex("#000000"),
+        )
+
+        for idx, zone in enumerate(zones):
+            annotated_frame = sv.draw_polygon(
+                scene=annotated_frame, polygon=zone.polygon, color=COLORS.by_idx(idx)
+            )
+
+            detections_in_zone = detections[zone.trigger(detections)]
+            time_in_zone = timers[idx].tick(detections_in_zone)
+            custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
+
+            annotated_frame = COLOR_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                custom_color_lookup=custom_color_lookup,
+            )
+            labels = [
+                f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
+                for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
+            ]
+            annotated_frame = LABEL_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                labels=labels,
+                custom_color_lookup=custom_color_lookup,
+            )
+
+        cv2.imshow("Processed Video", annotated_frame)
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculating detections dwell time in zones, using RTSP stream."
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path to the zone configuration JSON file.",
+    )
+    parser.add_argument(
+        "--rtsp_url",
+        type=str,
+        required=True,
+        help="Complete RTSP URL for the video stream.",
+    )
+    parser.add_argument(
+        "--weights",
+        type=str,
+        default="yolov8s.pt",
+        help="Path to the model weights file. Default is 'yolov8s.pt'.",
+    )
+    parser.add_argument(
+        "--device",
+        type=str,
+        default="cpu",
+        help="Computation device ('cpu', 'mps' or 'cuda'). Default is 'cpu'.",
+    )
+    parser.add_argument(
+        "--confidence_threshold",
+        type=float,
+        default=0.3,
+        help="Confidence level for detections (0 to 1). Default is 0.3.",
+    )
+    parser.add_argument(
+        "--iou_threshold",
+        default=0.7,
+        type=float,
+        help="IOU threshold for non-max suppression. Default is 0.7.",
+    )
+    parser.add_argument(
+        "--classes",
+        nargs="*",
+        type=int,
+        default=[],
+        help="List of class IDs to track. If empty, all classes are tracked.",
+    )
+    args = parser.parse_args()
+
+    main(
+        rtsp_url=args.rtsp_url,
+        zone_configuration_path=args.zone_configuration_path,
+        weights=args.weights,
+        device=args.device,
+        confidence=args.confidence_threshold,
+        iou=args.iou_threshold,
+        classes=args.classes,
+    )
diff --git a/examples/time_in_zone/ultralytics_stream_example.py b/examples/time_in_zone/ultralytics_stream_example.py
new file mode 100644
index 000000000..25dc874f8
--- /dev/null
+++ b/examples/time_in_zone/ultralytics_stream_example.py
@@ -0,0 +1,173 @@
+import argparse
+from typing import List
+
+import cv2
+import numpy as np
+from inference import InferencePipeline
+from inference.core.interfaces.camera.entities import VideoFrame
+from ultralytics import YOLO
+from utils.general import find_in_list, load_zones_config
+from utils.timers import ClockBasedTimer
+
+import supervision as sv
+
+COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
+COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
+LABEL_ANNOTATOR = sv.LabelAnnotator(
+    color=COLORS, text_color=sv.Color.from_hex("#000000")
+)
+
+
+class CustomSink:
+    def __init__(self, zone_configuration_path: str, classes: List[int]):
+        self.classes = classes
+        self.tracker = sv.ByteTrack(minimum_matching_threshold=0.8)
+        self.fps_monitor = sv.FPSMonitor()
+        self.polygons = load_zones_config(file_path=zone_configuration_path)
+        self.timers = [ClockBasedTimer() for _ in self.polygons]
+        self.zones = None
+
+    def on_prediction(self, detections: sv.Detections, frame: VideoFrame) -> None:
+        if self.zones is None:
+            resolution_wh = frame.image.shape[1], frame.image.shape[0]
+            self.zones = [
+                sv.PolygonZone(
+                    polygon=polygon,
+                    frame_resolution_wh=resolution_wh,
+                    triggering_anchors=(sv.Position.CENTER,),
+                )
+                for polygon in self.polygons
+            ]
+
+        self.fps_monitor.tick()
+        fps = self.fps_monitor.fps
+
+        detections = detections[find_in_list(detections.class_id, self.classes)]
+        detections = self.tracker.update_with_detections(detections)
+
+        annotated_frame = frame.image.copy()
+        annotated_frame = sv.draw_text(
+            scene=annotated_frame,
+            text=f"{fps:.1f}",
+            text_anchor=sv.Point(40, 30),
+            background_color=sv.Color.from_hex("#A351FB"),
+            text_color=sv.Color.from_hex("#000000"),
+        )
+
+        for idx, zone in enumerate(self.zones):
+            annotated_frame = sv.draw_polygon(
+                scene=annotated_frame, polygon=zone.polygon, color=COLORS.by_idx(idx)
+            )
+
+            detections_in_zone = detections[zone.trigger(detections)]
+            time_in_zone = self.timers[idx].tick(detections_in_zone)
+            custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
+
+            annotated_frame = COLOR_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                custom_color_lookup=custom_color_lookup,
+            )
+            labels = [
+                f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
+                for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
+            ]
+            annotated_frame = LABEL_ANNOTATOR.annotate(
+                scene=annotated_frame,
+                detections=detections_in_zone,
+                labels=labels,
+                custom_color_lookup=custom_color_lookup,
+            )
+        cv2.imshow("Processed Video", annotated_frame)
+        cv2.waitKey(1)
+
+
+def main(
+    rtsp_url: str,
+    zone_configuration_path: str,
+    weights: str,
+    device: str,
+    confidence: float,
+    iou: float,
+    classes: List[int],
+) -> None:
+    model = YOLO(weights)
+
+    def inference_callback(frame: VideoFrame) -> sv.Detections:
+        results = model(frame.image, verbose=False, conf=confidence, device=device)[0]
+        return sv.Detections.from_ultralytics(results).with_nms(threshold=iou)
+
+    sink = CustomSink(zone_configuration_path=zone_configuration_path, classes=classes)
+
+    pipeline = InferencePipeline.init_with_custom_logic(
+        video_reference=rtsp_url,
+        on_video_frame=inference_callback,
+        on_prediction=sink.on_prediction,
+    )
+
+    pipeline.start()
+
+    try:
+        pipeline.join()
+    except KeyboardInterrupt:
+        pipeline.terminate()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculating detections dwell time in zones, using RTSP stream."
+    )
+    parser.add_argument(
+        "--zone_configuration_path",
+        type=str,
+        required=True,
+        help="Path to the zone configuration JSON file.",
+    )
+    parser.add_argument(
+        "--rtsp_url",
+        type=str,
+        required=True,
+        help="Complete RTSP URL for the video stream.",
+    )
+    parser.add_argument(
+        "--weights",
+        type=str,
+        default="yolov8s.pt",
+        help="Path to the model weights file. Default is 'yolov8s.pt'.",
+    )
+    parser.add_argument(
+        "--device",
+        type=str,
+        default="cpu",
+        help="Computation device ('cpu', 'mps' or 'cuda'). Default is 'cpu'.",
+    )
+    parser.add_argument(
+        "--confidence_threshold",
+        type=float,
+        default=0.3,
+        help="Confidence level for detections (0 to 1). Default is 0.3.",
+    )
+    parser.add_argument(
+        "--iou_threshold",
+        default=0.7,
+        type=float,
+        help="IOU threshold for non-max suppression. Default is 0.7.",
+    )
+    parser.add_argument(
+        "--classes",
+        nargs="*",
+        type=int,
+        default=[],
+        help="List of class IDs to track. If empty, all classes are tracked.",
+    )
+    args = parser.parse_args()
+
+    main(
+        rtsp_url=args.rtsp_url,
+        zone_configuration_path=args.zone_configuration_path,
+        weights=args.weights,
+        device=args.device,
+        confidence=args.confidence_threshold,
+        iou=args.iou_threshold,
+        classes=args.classes,
+    )
diff --git a/examples/time_in_zone/utils/__init__.py b/examples/time_in_zone/utils/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/examples/time_in_zone/utils/general.py b/examples/time_in_zone/utils/general.py
new file mode 100644
index 000000000..803d116aa
--- /dev/null
+++ b/examples/time_in_zone/utils/general.py
@@ -0,0 +1,66 @@
+import json
+from typing import Generator, List
+
+import cv2
+import numpy as np
+
+
+def load_zones_config(file_path: str) -> List[np.ndarray]:
+    """
+    Load polygon zone configurations from a JSON file.
+
+    This function reads a JSON file which contains polygon coordinates, and
+    converts them into a list of NumPy arrays. Each polygon is represented as
+    a NumPy array of coordinates.
+
+    Args:
+        file_path (str): The path to the JSON configuration file.
+
+    Returns:
+        List[np.ndarray]: A list of polygons, each represented as a NumPy array.
+    """
+    with open(file_path, "r") as file:
+        data = json.load(file)
+        return [np.array(polygon, np.int32) for polygon in data]
+
+
+def find_in_list(array: np.ndarray, search_list: List[int]) -> np.ndarray:
+    """Determines if elements of a numpy array are present in a list.
+
+    Args:
+        array (np.ndarray): The numpy array of integers to check.
+        search_list (List[int]): The list of integers to search within.
+
+    Returns:
+        np.ndarray: A numpy array of booleans, where each boolean indicates whether
+        the corresponding element in `array` is found in `search_list`.
+    """
+    if not search_list:
+        return np.ones(array.shape, dtype=bool)
+    else:
+        return np.isin(array, search_list)
+
+
+def get_stream_frames_generator(rtsp_url: str) -> Generator[np.ndarray, None, None]:
+    """
+    Generator function to yield frames from an RTSP stream.
+
+    Args:
+        rtsp_url (str): URL of the RTSP video stream.
+
+    Yields:
+        np.ndarray: The next frame from the video stream.
+    """
+    cap = cv2.VideoCapture(rtsp_url)
+    if not cap.isOpened():
+        raise Exception("Error: Could not open video stream.")
+
+    try:
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                print("End of stream or error reading frame.")
+                break
+            yield frame
+    finally:
+        cap.release()
diff --git a/examples/time_in_zone/utils/timers.py b/examples/time_in_zone/utils/timers.py
new file mode 100644
index 000000000..cb5b471f6
--- /dev/null
+++ b/examples/time_in_zone/utils/timers.py
@@ -0,0 +1,88 @@
+from datetime import datetime
+from typing import Dict
+
+import numpy as np
+
+import supervision as sv
+
+
+class FPSBasedTimer:
+    """
+    A timer that calculates the duration each object has been detected based on frames
+    per second (FPS).
+
+    Attributes:
+        fps (int): The frame rate of the video stream, used to calculate time durations.
+        frame_id (int): The current frame number in the sequence.
+        tracker_id2frame_id (Dict[int, int]): Maps each tracker's ID to the frame number
+            at which it was first detected.
+    """
+
+    def __init__(self, fps: int = 30) -> None:
+        """Initializes the FPSBasedTimer with the specified frames per second rate.
+
+        Args:
+            fps (int, optional): The frame rate of the video stream. Defaults to 30.
+        """
+        self.fps = fps
+        self.frame_id = 0
+        self.tracker_id2frame_id: Dict[int, int] = {}
+
+    def tick(self, detections: sv.Detections) -> np.ndarray:
+        """Processes the current frame, updating time durations for each tracker.
+
+        Args:
+            detections: The detections for the current frame, including tracker IDs.
+
+        Returns:
+            np.ndarray: Time durations (in seconds) for each detected tracker, since
+                their first detection.
+        """
+        self.frame_id += 1
+        times = []
+
+        for tracker_id in detections.tracker_id:
+            self.tracker_id2frame_id.setdefault(tracker_id, self.frame_id)
+
+            start_frame_id = self.tracker_id2frame_id[tracker_id]
+            time_duration = (self.frame_id - start_frame_id) / self.fps
+            times.append(time_duration)
+
+        return np.array(times)
+
+
+class ClockBasedTimer:
+    """
+    A timer that calculates the duration each object has been detected based on the
+    system clock.
+
+    Attributes:
+        tracker_id2start_time (Dict[int, datetime]): Maps each tracker's ID to the
+            datetime when it was first detected.
+    """
+
+    def __init__(self) -> None:
+        """Initializes the ClockBasedTimer."""
+        self.tracker_id2start_time: Dict[int, datetime] = {}
+
+    def tick(self, detections: sv.Detections) -> np.ndarray:
+        """Processes the current frame, updating time durations for each tracker.
+
+        Args:
+            detections: The detections for the current frame, including tracker IDs.
+
+        Returns:
+            np.ndarray: Time durations (in seconds) for each detected tracker, since
+                their first detection.
+        """
+        current_time = datetime.now()
+        times = []
+
+        for tracker_id in detections.tracker_id:
+            self.tracker_id2start_time.setdefault(tracker_id, current_time)
+
+            start_time = self.tracker_id2start_time[tracker_id]
+            time_duration = (current_time - start_time).total_seconds()
+            times.append(time_duration)
+
+        return np.array(times)

From 327697344641f891dcb12ceb77e81f877ff34b6b Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Wed, 27 Mar 2024 00:14:19 +0100
Subject: [PATCH 048/188] Update README.md

---
 examples/README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/examples/README.md b/examples/README.md
index 4afeb5c39..81c8054b9 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -8,6 +8,7 @@ interfaces with diverse applications.
 - [count people in zone](./count_people_in_zone) by [@SkalskiP](https://github.com/SkalskiP)
 - [traffic analysis](./traffic_analysis) by [@SkalskiP](https://github.com/SkalskiP)
 - [speed estimation](./speed_estimation) by [@SkalskiP](https://github.com/SkalskiP)
+- [time in zone](./time_in_zone) by [@SkalskiP](https://github.com/SkalskiP)
 - [heatmap and track](./heatmap_and_track/) by [@HinePo](https://github.com/HinePo)
 
 ## Contributing

From 34b80eb3c0310cff1c6357f0eb980cd3ef613eb3 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 27 Mar 2024 09:12:45 +0100
Subject: [PATCH 049/188] Fix YT videos paths

---
 examples/time_in_zone/README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/examples/time_in_zone/README.md b/examples/time_in_zone/README.md
index 3898c4525..2bfd6c7af 100644
--- a/examples/time_in_zone/README.md
+++ b/examples/time_in_zone/README.md
@@ -43,14 +43,14 @@ This script allows you to download a video from YouTube.
 
 ```bash
 python scripts/download_from_youtube.py \
---url "https://youtu.be/8zyEwAa50Q" \
+--url "https://www.youtube.com/watch?v=-8zyEwAa50Q" \
 --output_path "data/checkout" \
 --file_name "video.mp4"
 ```
 
 ```bash
 python scripts/download_from_youtube.py \
---url "https://youtu.be/MNn9qKG2UFI" \
+--url "https://www.youtube.com/watch?v=MNn9qKG2UFI" \
 --output_path "data/traffic" \
 --file_name "video.mp4"
 ```
@@ -95,7 +95,7 @@ be saved as a JSON file.
 ```bash
 python scripts/draw_zones.py \
 --source_path "data/checkout/video.mp4" \
---zone_configuration_path "data/checkout/custom_config.json"
+--zone_configuration_path "data/checkout/config.json"
 ```
 
 ```bash

From 8fb3ba70b083958ac8c7cda6aa7151631a5377f7 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 28 Mar 2024 00:56:05 +0000
Subject: [PATCH 050/188] :arrow_up: Bump build from 1.1.1 to 1.2.0

Bumps [build](https://github.com/pypa/build) from 1.1.1 to 1.2.0.
- [Release notes](https://github.com/pypa/build/releases)
- [Changelog](https://github.com/pypa/build/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pypa/build/compare/1.1.1...1.2.0)

---
updated-dependencies:
- dependency-name: build
  dependency-type: direct:development
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock    | 19 ++++++++++---------
 pyproject.toml |  2 +-
 2 files changed, 11 insertions(+), 10 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index a553dd2a5..0bc8e6211 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
 [[package]]
 name = "anyio"
@@ -244,26 +244,27 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "build"
-version = "1.1.1"
+version = "1.2.0"
 description = "A simple, correct Python build frontend"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "build-1.1.1-py3-none-any.whl", hash = "sha256:8ed0851ee76e6e38adce47e4bee3b51c771d86c64cf578d0c2245567ee200e73"},
-    {file = "build-1.1.1.tar.gz", hash = "sha256:8eea65bb45b1aac2e734ba2cc8dad3a6d97d97901a395bd0ed3e7b46953d2a31"},
+    {file = "build-1.2.0-py3-none-any.whl", hash = "sha256:6105465d9b233433ce8ffa151c760f674446ba766af0290fc14bfa32aef92a04"},
+    {file = "build-1.2.0.tar.gz", hash = "sha256:49df7f8e1e74d345fe71e54f5d56423b2111eda89e3da53a2c18392954dade1d"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "os_name == \"nt\""}
 importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
-packaging = ">=19.0"
+packaging = ">=19.1"
 pyproject_hooks = "*"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
-test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
-typing = ["importlib-metadata (>=5.1)", "mypy (>=1.5.0,<1.6.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
+typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+uv = ["uv (>=0.1.18)"]
 virtualenv = ["virtualenv (>=20.0.35)"]
 
 [[package]]
@@ -4252,4 +4253,4 @@ desktop = ["opencv-python"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.8"
-content-hash = "30b2e5864f20c0b0cf5ddff7658427a18e18c9d387da86725e8e9288f795086a"
+content-hash = "56ddae6824a9f28c9954badd4c642c57f687b099c6169f97fa0372e294500c17"
diff --git a/pyproject.toml b/pyproject.toml
index 6a2477cbb..b02c638e1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -54,7 +54,7 @@ assets = ["requests","tqdm"]
 twine = ">=4.0.2,<6.0.0"
 pytest = ">=7.2.2,<9.0.0"
 wheel = ">=0.40,<0.44"
-build = ">=0.10,<1.2"
+build = ">=0.10,<1.3"
 ruff = ">=0.1.0"
 mypy = "^1.4.1"
 pre-commit = "^3.3.3"

From ad24d3811b35150665b9f6b40ed7e88f4c5b97a5 Mon Sep 17 00:00:00 2001
From: Raif Olson <raif.t.olson.24@dartmouth.edu>
Date: Wed, 27 Mar 2024 23:38:55 -0400
Subject: [PATCH 051/188] Refactor update_with_detections for simplicity.
 Credit to @SkalskiP for the code. (had to change a few lines for bug fixes)

---
 supervision/tracker/byte_tracker/core.py | 37 +++++++-----------------
 1 file changed, 11 insertions(+), 26 deletions(-)

diff --git a/supervision/tracker/byte_tracker/core.py b/supervision/tracker/byte_tracker/core.py
index 4d6416e89..1b2e2489e 100644
--- a/supervision/tracker/byte_tracker/core.py
+++ b/supervision/tracker/byte_tracker/core.py
@@ -272,11 +272,8 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
         """
 
         tensors = detections2boxes(detections=detections)
-
         tracks = self.update_with_tensors(tensors=tensors)
-
-        final_detections = Detections.empty()
-
+        
         if len(tracks) > 0:
             detection_bounding_boxes = np.asarray([det[:4] for det in tensors])
             track_bounding_boxes = np.asarray([track.tlbr for track in tracks])
@@ -286,30 +283,18 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
             iou_costs = 1 - ious
 
             matches, _, _ = matching.linear_assignment(iou_costs, 0.5)
-            for i, (idet, itrack) in enumerate(matches):
-                if i == 0:
-                    final_detections = detections[[idet]]
-                    if final_detections.tracker_id is None:
-                        final_detections.tracker_id = np.asarray(
-                            [int(tracks[itrack].track_id)]
-                        )
-                    else:
-                        final_detections.tracker_id[0] = int(tracks[itrack].track_id)
-                else:
-                    current_detection = detections[[idet]]
-                    if current_detection.tracker_id is None:
-                        current_detection.tracker_id = np.asarray(
-                            [int(tracks[itrack].track_id)]
-                        )
-                    else:
-                        current_detection.tracker_id[0] = int(tracks[itrack].track_id)
-                    final_detections = Detections.merge(
-                        [final_detections, current_detection]
-                    )
+            detections.tracker_id = np.full(len(detections), -1, dtype=int)
+            for i_detection, i_track in matches:
+                detections.tracker_id[i_detection] = int(tracks[i_track].track_id)
+            
+            invalid_tracks = [i for i in range(len(detections.tracker_id)) if detections.tracker_id[i] != -1]
+            
+            return detections[invalid_tracks]
+
         else:
-            final_detections.tracker_id = np.array([], dtype=int)
+            detections.tracker_id = np.array([], dtype=int)
 
-        return final_detections
+            return detections
 
     def reset(self):
         """

From e9edc2fb1d1724382d9a764234378d2c019ceb07 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 28 Mar 2024 03:39:20 +0000
Subject: [PATCH 052/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/tracker/byte_tracker/core.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/supervision/tracker/byte_tracker/core.py b/supervision/tracker/byte_tracker/core.py
index 1b2e2489e..eb94e55ab 100644
--- a/supervision/tracker/byte_tracker/core.py
+++ b/supervision/tracker/byte_tracker/core.py
@@ -273,7 +273,7 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
 
         tensors = detections2boxes(detections=detections)
         tracks = self.update_with_tensors(tensors=tensors)
-        
+
         if len(tracks) > 0:
             detection_bounding_boxes = np.asarray([det[:4] for det in tensors])
             track_bounding_boxes = np.asarray([track.tlbr for track in tracks])
@@ -286,9 +286,13 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
             detections.tracker_id = np.full(len(detections), -1, dtype=int)
             for i_detection, i_track in matches:
                 detections.tracker_id[i_detection] = int(tracks[i_track].track_id)
-            
-            invalid_tracks = [i for i in range(len(detections.tracker_id)) if detections.tracker_id[i] != -1]
-            
+
+            invalid_tracks = [
+                i
+                for i in range(len(detections.tracker_id))
+                if detections.tracker_id[i] != -1
+            ]
+
             return detections[invalid_tracks]
 
         else:

From 089594f72d987a9010c61cf3c063f88f0d712af3 Mon Sep 17 00:00:00 2001
From: Raif Olson <raif.t.olson.24@dartmouth.edu>
Date: Wed, 27 Mar 2024 23:50:02 -0400
Subject: [PATCH 053/188] fix Detections.get_data_item() bug

---
 supervision/detection/utils.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/supervision/detection/utils.py b/supervision/detection/utils.py
index 3302d5f30..762f06c7f 100644
--- a/supervision/detection/utils.py
+++ b/supervision/detection/utils.py
@@ -845,8 +845,13 @@ def get_data_item(
         elif isinstance(value, list):
             if isinstance(index, slice):
                 subset_data[key] = value[index]
-            elif isinstance(index, (list, np.ndarray)):
+            elif isinstance(index, list):
                 subset_data[key] = [value[i] for i in index]
+            elif isinstance(index, np.ndarray):
+                if index.dtype == bool:
+                    subset_data[key] = [value[i] for i in range(len(index)) if index[i]]
+                else:
+                    subset_data[key] = [value[i] for i in index]
             elif isinstance(index, int):
                 subset_data[key] = [value[index]]
             else:

From da4404e8750d9a69efd4fb0b33f06f4e341b5a55 Mon Sep 17 00:00:00 2001
From: Raif Olson <raif.t.olson.24@dartmouth.edu>
Date: Thu, 28 Mar 2024 08:38:50 -0400
Subject: [PATCH 054/188] More pythonic version of change

---
 supervision/detection/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/detection/utils.py b/supervision/detection/utils.py
index 762f06c7f..25a2a37ce 100644
--- a/supervision/detection/utils.py
+++ b/supervision/detection/utils.py
@@ -849,7 +849,7 @@ def get_data_item(
                 subset_data[key] = [value[i] for i in index]
             elif isinstance(index, np.ndarray):
                 if index.dtype == bool:
-                    subset_data[key] = [value[i] for i in range(len(index)) if index[i]]
+                    subset_data[key] = [value[i] for i, index_value in enumerate(index) if index_value]
                 else:
                     subset_data[key] = [value[i] for i in index]
             elif isinstance(index, int):

From 29ba24f89a76def71d178da22db54be123279437 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 28 Mar 2024 12:39:11 +0000
Subject: [PATCH 055/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/utils.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/supervision/detection/utils.py b/supervision/detection/utils.py
index 25a2a37ce..b3928fdb5 100644
--- a/supervision/detection/utils.py
+++ b/supervision/detection/utils.py
@@ -849,7 +849,9 @@ def get_data_item(
                 subset_data[key] = [value[i] for i in index]
             elif isinstance(index, np.ndarray):
                 if index.dtype == bool:
-                    subset_data[key] = [value[i] for i, index_value in enumerate(index) if index_value]
+                    subset_data[key] = [
+                        value[i] for i, index_value in enumerate(index) if index_value
+                    ]
                 else:
                     subset_data[key] = [value[i] for i in index]
             elif isinstance(index, int):

From 64eef66b543c54dad0d9ea623dcada04f1edfd13 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 14:04:21 +0100
Subject: [PATCH 056/188] `get_data_item` unit tests

---
 test/detection/test_utils.py | 93 +++++++++++++++++++++++++++++++-----
 1 file changed, 82 insertions(+), 11 deletions(-)

diff --git a/test/detection/test_utils.py b/test/detection/test_utils.py
index d09348ff5..899cb8589 100644
--- a/test/detection/test_utils.py
+++ b/test/detection/test_utils.py
@@ -1035,7 +1035,12 @@ def test_merge_data(
 @pytest.mark.parametrize(
     "data, index, expected_result, exception",
     [
-        ({}, 0, {}, DoesNotRaise()),  # empty data dict
+        (
+            {},
+            0,
+            {},
+            DoesNotRaise()
+        ),  # empty data dict
         (
             {
                 "test_1": [1, 2, 3],
@@ -1045,7 +1050,7 @@ def test_merge_data(
                 "test_1": [1],
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and list values
+        ),  # data dict with a single list field and integer index
         (
             {
                 "test_1": np.array([1, 2, 3]),
@@ -1055,7 +1060,7 @@ def test_merge_data(
                 "test_1": np.array([1]),
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and np.array values as 1D arrays
+        ),  # data dict with a single np.array field and integer index
         (
             {
                 "test_1": [1, 2, 3],
@@ -1065,7 +1070,7 @@ def test_merge_data(
                 "test_1": [1, 2],
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and list values
+        ),  # data dict with a single list field and slice index
         (
             {
                 "test_1": np.array([1, 2, 3]),
@@ -1075,7 +1080,7 @@ def test_merge_data(
                 "test_1": np.array([1, 2]),
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and np.array values as 1D arrays
+        ),  # data dict with a single np.array field and slice index
         (
             {
                 "test_1": [1, 2, 3],
@@ -1085,7 +1090,7 @@ def test_merge_data(
                 "test_1": [3],
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and list values
+        ),  # data dict with a single list field and negative integer index
         (
             {
                 "test_1": np.array([1, 2, 3]),
@@ -1095,7 +1100,7 @@ def test_merge_data(
                 "test_1": np.array([3]),
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and np.array values as 1D arrays
+        ),  # data dict with a single np.array field and negative integer index
         (
             {
                 "test_1": [1, 2, 3],
@@ -1105,7 +1110,7 @@ def test_merge_data(
                 "test_1": [1, 3],
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and list values
+        ),  # data dict with a single list field and integer list index
         (
             {
                 "test_1": np.array([1, 2, 3]),
@@ -1115,7 +1120,7 @@ def test_merge_data(
                 "test_1": np.array([1, 3]),
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and np.array values as 1D arrays
+        ),  # data dict with a single np.array field and integer list index
         (
             {
                 "test_1": [1, 2, 3],
@@ -1125,7 +1130,7 @@ def test_merge_data(
                 "test_1": [1, 3],
             },
             DoesNotRaise(),
-        ),  # single data dict with a single field name and list values
+        ),  # data dict with a single list field and integer np.array index
         (
             {
                 "test_1": np.array([1, 2, 3]),
@@ -1135,7 +1140,73 @@ def test_merge_data(
                 "test_1": np.array([1, 3]),
             },
             DoesNotRaise(),
-        ),
+        ),  # data dict with a single np.array field and integer np.array index
+        (
+            {
+                "test_1": np.array([1, 2, 3]),
+            },
+            np.array([True, True, True]),
+            {
+                "test_1": np.array([1, 2, 3]),
+            },
+            DoesNotRaise(),
+        ),  # data dict with a single np.array field and all-true bool np.array index
+        (
+            {
+                "test_1": np.array([1, 2, 3]),
+            },
+            np.array([False, False, False]),
+            {
+                "test_1": np.array([]),
+            },
+            DoesNotRaise(),
+        ),  # data dict with a single np.array field and all-false bool np.array index
+        (
+            {
+                "test_1": np.array([1, 2, 3]),
+            },
+            np.array([False, True, False]),
+            {
+                "test_1": np.array([2]),
+            },
+            DoesNotRaise(),
+        ),  # data dict with a single np.array field and mixed bool np.array index
+        (
+            {
+                "test_1": np.array([1, 2, 3]),
+                "test_2": ['a', 'b', 'c']
+            },
+            0,
+            {
+                "test_1": np.array([1]),
+                "test_2": ['a']
+            },
+            DoesNotRaise(),
+        ),  # data dict with two fields and integer index
+        (
+            {
+                "test_1": np.array([1, 2, 3]),
+                "test_2": ['a', 'b', 'c']
+            },
+            -1,
+            {
+                "test_1": np.array([3]),
+                "test_2": ['c']
+            },
+            DoesNotRaise(),
+        ),  # data dict with two fields and negative integer index
+        (
+            {
+                "test_1": np.array([1, 2, 3]),
+                "test_2": ['a', 'b', 'c']
+            },
+            np.array([False, True, False]),
+            {
+                "test_1": np.array([2]),
+                "test_2": ['b']
+            },
+            DoesNotRaise(),
+        ),  # data dict with two fields and mixed bool np.array index
     ],
 )
 def test_get_data_item(

From dc5f841baef5eec6f318374cc295666dac3362c4 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 28 Mar 2024 13:06:45 +0000
Subject: [PATCH 057/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 test/detection/test_utils.py | 37 +++++++-----------------------------
 1 file changed, 7 insertions(+), 30 deletions(-)

diff --git a/test/detection/test_utils.py b/test/detection/test_utils.py
index 899cb8589..1c4a1d349 100644
--- a/test/detection/test_utils.py
+++ b/test/detection/test_utils.py
@@ -1035,12 +1035,7 @@ def test_merge_data(
 @pytest.mark.parametrize(
     "data, index, expected_result, exception",
     [
-        (
-            {},
-            0,
-            {},
-            DoesNotRaise()
-        ),  # empty data dict
+        ({}, 0, {}, DoesNotRaise()),  # empty data dict
         (
             {
                 "test_1": [1, 2, 3],
@@ -1172,39 +1167,21 @@ def test_merge_data(
             DoesNotRaise(),
         ),  # data dict with a single np.array field and mixed bool np.array index
         (
-            {
-                "test_1": np.array([1, 2, 3]),
-                "test_2": ['a', 'b', 'c']
-            },
+            {"test_1": np.array([1, 2, 3]), "test_2": ["a", "b", "c"]},
             0,
-            {
-                "test_1": np.array([1]),
-                "test_2": ['a']
-            },
+            {"test_1": np.array([1]), "test_2": ["a"]},
             DoesNotRaise(),
         ),  # data dict with two fields and integer index
         (
-            {
-                "test_1": np.array([1, 2, 3]),
-                "test_2": ['a', 'b', 'c']
-            },
+            {"test_1": np.array([1, 2, 3]), "test_2": ["a", "b", "c"]},
             -1,
-            {
-                "test_1": np.array([3]),
-                "test_2": ['c']
-            },
+            {"test_1": np.array([3]), "test_2": ["c"]},
             DoesNotRaise(),
         ),  # data dict with two fields and negative integer index
         (
-            {
-                "test_1": np.array([1, 2, 3]),
-                "test_2": ['a', 'b', 'c']
-            },
+            {"test_1": np.array([1, 2, 3]), "test_2": ["a", "b", "c"]},
             np.array([False, True, False]),
-            {
-                "test_1": np.array([2]),
-                "test_2": ['b']
-            },
+            {"test_1": np.array([2]), "test_2": ["b"]},
             DoesNotRaise(),
         ),  # data dict with two fields and mixed bool np.array index
     ],

From a2aca62ecb19397ed141d0399e3f8778907d2bd3 Mon Sep 17 00:00:00 2001
From: Raif Olson <raif.t.olson.24@dartmouth.edu>
Date: Thu, 28 Mar 2024 09:27:54 -0400
Subject: [PATCH 058/188] merge develop branch and change back to using boolean
 indexing

---
 supervision/tracker/byte_tracker/core.py | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/supervision/tracker/byte_tracker/core.py b/supervision/tracker/byte_tracker/core.py
index eb94e55ab..c77878cf9 100644
--- a/supervision/tracker/byte_tracker/core.py
+++ b/supervision/tracker/byte_tracker/core.py
@@ -287,13 +287,7 @@ def callback(frame: np.ndarray, index: int) -> np.ndarray:
             for i_detection, i_track in matches:
                 detections.tracker_id[i_detection] = int(tracks[i_track].track_id)
 
-            invalid_tracks = [
-                i
-                for i in range(len(detections.tracker_id))
-                if detections.tracker_id[i] != -1
-            ]
-
-            return detections[invalid_tracks]
+            return detections[detections.tracker_id != -1]
 
         else:
             detections.tracker_id = np.array([], dtype=int)

From 7e283d4eeb31b785de3cdab014504d5fb53601c9 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Thu, 28 Mar 2024 16:28:21 +0300
Subject: [PATCH 059/188] =?UTF-8?q?fix:=20=F0=9F=90=9E=20ci=20trigger=20er?=
 =?UTF-8?q?ror=20fix?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 .github/workflows/publish-test.yml | 16 ++++++++--------
 .github/workflows/publish.yml      |  1 -
 2 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/.github/workflows/publish-test.yml b/.github/workflows/publish-test.yml
index a07af1d3f..ec120e94f 100644
--- a/.github/workflows/publish-test.yml
+++ b/.github/workflows/publish-test.yml
@@ -5,25 +5,25 @@ on:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+a[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+b[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+rc[0-9]'
-    branches:
-      - develop
 
-  # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:
   build-n-publish:
     name: Build and publish to PyPI
     runs-on: ubuntu-latest
-
+    strategy:
+      matrix:
+        python-version: [3.10]
     steps:
-      - name: Checkout source
+      - name: 🛎️ Checkout
         uses: actions/checkout@v4
-
-      - name: 🐍 Set up Python 3.8 environment for build
+        with:
+          ref: ${{ github.head_ref }}
+      - name: 🐍 Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
-          python-version: "3.8"
+          python-version: ${{ matrix.python-version }}
 
       - name: 🏗️ Build source and wheel distributions
         run: |
diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
index 76d1c67c1..a97497905 100644
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@@ -4,7 +4,6 @@ on:
     tags:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]'
 
-  # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:

From 81c2a09430a68462a3d9fa3580c8cf69466c4257 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 15:09:23 +0100
Subject: [PATCH 060/188] bump version from `0.19.0` to `0.20.0rc1`

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index b02c638e1..bc62679dc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "supervision"
-version = "0.19.0"
+version = "0.20.0rc1"
 description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
 authors = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
 maintainers = ["Piotr Skalski <piotr.skalski92@gmail.com>"]

From 16c41d9d5db44f01d177052dfc05c19bf6ca6988 Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 15:19:24 +0100
Subject: [PATCH 061/188] =?UTF-8?q?Revert=20"fix:=20=F0=9F=90=9E=20ci=20tr?=
 =?UTF-8?q?igger=20error=20fix"?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .github/workflows/publish-test.yml | 16 ++++++++--------
 .github/workflows/publish.yml      |  1 +
 2 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/.github/workflows/publish-test.yml b/.github/workflows/publish-test.yml
index ec120e94f..a07af1d3f 100644
--- a/.github/workflows/publish-test.yml
+++ b/.github/workflows/publish-test.yml
@@ -5,25 +5,25 @@ on:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+a[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+b[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+rc[0-9]'
+    branches:
+      - develop
 
+  # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:
   build-n-publish:
     name: Build and publish to PyPI
     runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version: [3.10]
+
     steps:
-      - name: 🛎️ Checkout
+      - name: Checkout source
         uses: actions/checkout@v4
-        with:
-          ref: ${{ github.head_ref }}
-      - name: 🐍 Set up Python ${{ matrix.python-version }}
+
+      - name: 🐍 Set up Python 3.8 environment for build
         uses: actions/setup-python@v5
         with:
-          python-version: ${{ matrix.python-version }}
+          python-version: "3.8"
 
       - name: 🏗️ Build source and wheel distributions
         run: |
diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
index a97497905..76d1c67c1 100644
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@@ -4,6 +4,7 @@ on:
     tags:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]'
 
+  # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:

From 93584cbb8917b8d4ad7f574191f6c35ad539f3e0 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Thu, 28 Mar 2024 16:28:21 +0300
Subject: [PATCH 062/188] =?UTF-8?q?fix:=20=F0=9F=90=9E=20ci=20trigger=20er?=
 =?UTF-8?q?ror=20fix?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 .github/workflows/publish-test.yml | 16 ++++++++--------
 .github/workflows/publish.yml      |  3 +--
 2 files changed, 9 insertions(+), 10 deletions(-)

diff --git a/.github/workflows/publish-test.yml b/.github/workflows/publish-test.yml
index a07af1d3f..f201b7c41 100644
--- a/.github/workflows/publish-test.yml
+++ b/.github/workflows/publish-test.yml
@@ -5,25 +5,25 @@ on:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+a[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+b[0-9]'
       - '[0-9]+.[0-9]+[0-9]+.[0-9]+rc[0-9]'
-    branches:
-      - develop
 
-  # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:
   build-n-publish:
     name: Build and publish to PyPI
     runs-on: ubuntu-latest
-
+    strategy:
+      matrix:
+        python-version: ["3.10"]
     steps:
-      - name: Checkout source
+      - name: 🛎️ Checkout
         uses: actions/checkout@v4
-
-      - name: 🐍 Set up Python 3.8 environment for build
+        with:
+          ref: ${{ github.head_ref }}
+      - name: 🐍 Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
-          python-version: "3.8"
+          python-version: ${{ matrix.python-version }}
 
       - name: 🏗️ Build source and wheel distributions
         run: |
diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml
index 76d1c67c1..4de06532e 100644
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@@ -4,7 +4,6 @@ on:
     tags:
       - '[0-9]+.[0-9]+[0-9]+.[0-9]'
 
-  # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:
@@ -12,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.10]
+        python-version: ["3.10"]
     steps:
       - name: 🛎️ Checkout
         uses: actions/checkout@v4

From ccc7118bcbc053a7686867379617672494d28188 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 15:41:16 +0100
Subject: [PATCH 063/188] bump version from `0.20.0rc1` to `0.20.0rc2`

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index bc62679dc..7be53b6c2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "supervision"
-version = "0.20.0rc1"
+version = "0.20.0rc2"
 description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
 authors = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
 maintainers = ["Piotr Skalski <piotr.skalski92@gmail.com>"]

From f9fd88fb011f4a7acb6b82dd14de663f4efaed60 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Thu, 28 Mar 2024 17:55:11 +0300
Subject: [PATCH 064/188] =?UTF-8?q?docs:=20=F0=9F=93=9A=20conda=20and=20ma?=
 =?UTF-8?q?mba=20installation=20methods=20added?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 docs/index.md | 101 +++++++++++++++++++++++++++++++-------------------
 1 file changed, 62 insertions(+), 39 deletions(-)

diff --git a/docs/index.md b/docs/index.md
index 17151f5e7..e69ca201c 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -33,60 +33,83 @@ We write your reusable computer vision tools. Whether you need to load your data
 You can install `supervision` with pip in a
 [**Python>=3.8**](https://www.python.org/) environment.
 
-!!! example "pip install (recommended)"
+!!! success "Installation"
 
-    === "headless"
-        The headless installation of `supervision` is designed for environments where graphical user interfaces (GUI) are not needed, making it more lightweight and suitable for server-side applications.
+    !!! example "Pip installation (recommended)"
 
-        ```bash
-        pip install supervision
-        ```
+        === "Headless"
+            The headless installation of `supervision` is designed for environments where graphical user interfaces (GUI) are not needed, making it more lightweight and suitable for server-side applications.
 
-    === "desktop"
-        If you require the full version of `supervision` with GUI support you can install the desktop version. This version includes the GUI components of OpenCV, allowing you to display images and videos on the screen.
+            ```bash
+            pip install supervision
+            ```
 
-        ```bash
-        pip install "supervision[desktop]"
-        ```
+        === "Desktop"
+            The desktop installation of `supervision` is designed with GUI support. This version includes the GUI components of OpenCV, allowing you to display images and videos on the screen.
 
-!!! example "git clone (for development)"
+            ```bash
+            pip install "supervision[desktop]"
+            ```
 
-    === "virtualenv"
+    !!! example "Conda/Mamba installation"
 
-        ```bash
-        # clone repository and navigate to root directory
-        git clone https://github.com/roboflow/supervision.git
-        cd supervision
+        === "conda"
+            The Conda installation of `supervision` is designed for those who prefer using Conda as their package manager. It's especially useful for managing complex dependencies and environments.
 
-        # setup python environment and activate it
-        python3 -m venv venv
-        source venv/bin/activate
-        pip install --upgrade pip
+            [![Conda Recipe](https://img.shields.io/badge/recipe-supervision-green.svg)](https://anaconda.org/conda-forge/supervision) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Conda Version](https://img.shields.io/conda/vn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Conda Platforms](https://img.shields.io/conda/pn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision)
 
-        # headless install
-        pip install -e "."
 
-        # desktop install
-        pip install -e ".[desktop]"
-        ```
+            ```bash
+            conda install -c conda-forge supervision
+            ```
 
-    === "poetry"
+        === "mamba"
+            The Mamba installation of `supervision` is ideal for those who prefer using Mamba as their package manager.
 
-        ```bash
-        # clone repository and navigate to root directory
-        git clone https://github.com/roboflow/supervision.git
-        cd supervision
+            [![Mamba Recipe](https://img.shields.io/badge/recipe-supervision-green.svg)](https://anaconda.org/conda-forge/supervision) [![Mamba Downloads](https://img.shields.io/conda/dn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Mamba Version](https://img.shields.io/conda/vn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Mamba Platforms](https://img.shields.io/conda/pn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision)
 
-        # setup python environment and activate it
-        poetry env use python3.10
-        poetry shell
+            ```bash
+            mamba install -c conda-forge supervision
+            ```
 
-        # headless install
-        poetry install
+    !!! example "git clone (for development)"
 
-        # desktop install
-        poetry install --extras "desktop"
-        ```
+        === "virtualenv"
+
+            ```bash
+            # clone repository and navigate to root directory
+            git clone https://github.com/roboflow/supervision.git
+            cd supervision
+
+            # setup python environment and activate it
+            python3 -m venv venv
+            source venv/bin/activate
+            pip install --upgrade pip
+
+            # headless install
+            pip install -e "."
+
+            # desktop install
+            pip install -e ".[desktop]"
+            ```
+
+        === "poetry"
+
+            ```bash
+            # clone repository and navigate to root directory
+            git clone https://github.com/roboflow/supervision.git
+            cd supervision
+
+            # setup python environment and activate it
+            poetry env use python3.10
+            poetry shell
+
+            # headless install
+            poetry install
+
+            # desktop install
+            poetry install --extras "desktop"
+            ```
 
 
 ## 🚀 Quickstart

From 4ad78becb674c9c0d82b0961a64aa9d3fefeb455 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 16:08:05 +0100
Subject: [PATCH 065/188] initial comment

---
 docs/how_to/detect_and_annotate.md | 38 ++++++++++++++++++++++
 supervision/detection/core.py      | 51 ++++++++++++++++++++----------
 2 files changed, 73 insertions(+), 16 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 45d0487a9..6aaabff30 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -362,4 +362,42 @@ that will allow you to draw masks instead of boxes.
         scene=annotated_image, detections=detections)
     ```
 
+=== "Transformers"
+
+    ```python
+    import torch
+    import supervision as sv
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForSegmentation
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForSegmentation.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<SOURCE_IMAGE_PATH>)
+    inputs = processor(images=image, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    detections = sv.Detections.from_transformers(results)
+
+    mask_annotator = sv.MaskAnnotator()
+    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+
+    labels = [
+        f"{model.config.id2label[class_id]} {confidence:.2f}"
+        for class_id, confidence
+        in zip(detections.class_id, detections.confidence)
+    ]
+
+    annotated_image = mask_annotator.annotate(
+        scene=image, detections=detections)
+    annotated_image = label_annotator.annotate(
+        scene=annotated_image, detections=detections)
+    ```
+
 ![segmentation-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_3.png)
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 60ff07f33..51616335b 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -396,25 +396,44 @@ def from_transformers(cls, transformers_results: dict) -> Detections:
 
         Returns:
             Detections: A new Detections object.
-        """
-        boxes = transformers_results.get("boxes")
 
-        # If the boxes key is in the transformers_results then we know it's an
-        # object detection result. Else, we can assume it's a segmentation model
-        if boxes:
-            return cls(
-                xyxy=transformers_results["boxes"].cpu().numpy(),
-                confidence=transformers_results["scores"].cpu().numpy(),
-                class_id=transformers_results["labels"].cpu().numpy().astype(int),
-            )
-        else:
-            masks = transformers_results["masks"].cpu().numpy().astype(bool)
+        Example:
+            ```python
+            import torch
+            import supervision as sv
+            from PIL import Image
+            from transformers import DetrImageProcessor, DetrForObjectDetection
+        
+            processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+            model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+        
+            image = Image.open(<SOURCE_IMAGE_PATH>)
+            inputs = processor(images=image, return_tensors="pt")
+        
+            with torch.no_grad():
+                outputs = model(**inputs)
+        
+            width, height = image.size
+            target_size = torch.tensor([[height, width]])
+            results = processor.post_process_object_detection(
+                outputs=outputs, target_sizes=target_size)[0]
+            detections = sv.Detections.from_transformers(results)
+            ```
+        """  # noqa: E501 // docs
+
+        if "boxes" in transformers_results:
             return cls(
-                xyxy=mask_to_xyxy(masks),
-                mask=masks,
-                confidence=transformers_results["scores"].cpu().numpy(),
-                class_id=transformers_results["labels"].cpu().numpy().astype(int),
+                xyxy=transformers_results["boxes"].cpu().detach().numpy(),
+                confidence=transformers_results["scores"].cpu().detach().numpy(),
+                class_id=transformers_results["labels"].cpu().detach().numpy().astype(int),
             )
+        masks = transformers_results["masks"].cpu().detach().numpy().astype(bool)
+        return cls(
+            xyxy=mask_to_xyxy(masks),
+            mask=masks,
+            confidence=transformers_results["scores"].cpu().detach().numpy(),
+            class_id=transformers_results["labels"].cpu().detach().numpy().astype(int),
+        )
 
     @classmethod
     def from_detectron2(cls, detectron2_results) -> Detections:

From 0c7c746f15c1ed39f691b606d2cdb6c7ca0015f4 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 28 Mar 2024 15:10:28 +0000
Subject: [PATCH 066/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/core.py | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 51616335b..8c29cfc48 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -403,16 +403,16 @@ def from_transformers(cls, transformers_results: dict) -> Detections:
             import supervision as sv
             from PIL import Image
             from transformers import DetrImageProcessor, DetrForObjectDetection
-        
+
             processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
             model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
-        
+
             image = Image.open(<SOURCE_IMAGE_PATH>)
             inputs = processor(images=image, return_tensors="pt")
-        
+
             with torch.no_grad():
                 outputs = model(**inputs)
-        
+
             width, height = image.size
             target_size = torch.tensor([[height, width]])
             results = processor.post_process_object_detection(
@@ -425,7 +425,11 @@ def from_transformers(cls, transformers_results: dict) -> Detections:
             return cls(
                 xyxy=transformers_results["boxes"].cpu().detach().numpy(),
                 confidence=transformers_results["scores"].cpu().detach().numpy(),
-                class_id=transformers_results["labels"].cpu().detach().numpy().astype(int),
+                class_id=transformers_results["labels"]
+                .cpu()
+                .detach()
+                .numpy()
+                .astype(int),
             )
         masks = transformers_results["masks"].cpu().detach().numpy().astype(bool)
         return cls(

From afc31e42a5b8b2dab2fd544233587231ce1bbcf8 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 16:34:05 +0100
Subject: [PATCH 067/188] few more improvements

---
 docs/how_to/detect_and_annotate.md | 26 +++++++++++++-------------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 6aaabff30..7bc2f9708 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -27,7 +27,7 @@ model.
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
     results = model.infer(image)[0]
     ```
 
@@ -38,7 +38,7 @@ model.
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
     results = model(image)[0]
     ```
 
@@ -52,7 +52,7 @@ model.
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<PATH TO IMAGE>)
+    image = Image.open(<SOURCE_IMAGE_APTH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -78,7 +78,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
     ```
@@ -93,7 +93,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
     ```
@@ -111,7 +111,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<PATH TO IMAGE>)
+    image = Image.open(<SOURCE_IMAGE_APTH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -144,7 +144,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
@@ -165,7 +165,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
 
@@ -189,7 +189,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<PATH TO IMAGE>)
+    image = Image.open(<SOURCE_IMAGE_APTH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -370,8 +370,8 @@ that will allow you to draw masks instead of boxes.
     from PIL import Image
     from transformers import DetrImageProcessor, DetrForSegmentation
 
-    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
-    model = DetrForSegmentation.from_pretrained("facebook/detr-resnet-50")
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50-panoptic")
+    model = DetrForSegmentation.from_pretrained("facebook/detr-resnet-50-panoptic")
 
     image = Image.open(<SOURCE_IMAGE_PATH>)
     inputs = processor(images=image, return_tensors="pt")
@@ -381,7 +381,7 @@ that will allow you to draw masks instead of boxes.
 
     width, height = image.size
     target_size = torch.tensor([[height, width]])
-    results = processor.post_process_object_detection(
+    results = processor.post_process_segmentation(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(results)
 
@@ -397,7 +397,7 @@ that will allow you to draw masks instead of boxes.
     annotated_image = mask_annotator.annotate(
         scene=image, detections=detections)
     annotated_image = label_annotator.annotate(
-        scene=annotated_image, detections=detections)
+        scene=annotated_image, detections=detections, labels=labels)
     ```
 
 ![segmentation-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_3.png)

From e88ab7c125c309a14f152e0fbef3603fed8a4f97 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Thu, 28 Mar 2024 18:53:39 +0100
Subject: [PATCH 068/188] small update

---
 README.md     |  10 ++---
 docs/index.md | 108 ++++++++++++++++++++++++--------------------------
 2 files changed, 56 insertions(+), 62 deletions(-)

diff --git a/README.md b/README.md
index 7196a6538..7d280b575 100644
--- a/README.md
+++ b/README.md
@@ -18,10 +18,10 @@
 [![downloads](https://img.shields.io/pypi/dm/supervision)](https://pypistats.org/packages/supervision)
 [![license](https://img.shields.io/pypi/l/supervision)](https://github.com/roboflow/supervision/blob/main/LICENSE.md)
 [![python-version](https://img.shields.io/pypi/pyversions/supervision)](https://badge.fury.io/py/supervision)
-[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/supervision/blob/main/demo.ipynb)
-[![Gradio](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/Roboflow/Annotators)
-[![Discord](https://img.shields.io/discord/1159501506232451173)](https://discord.gg/GbfgXGJ8Bk)
-[![Built with Material for MkDocs](https://img.shields.io/badge/Material_for_MkDocs-526CFE?logo=MaterialForMkDocs&logoColor=white)](https://squidfunk.github.io/mkdocs-material/)
+[![colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/supervision/blob/main/demo.ipynb)
+[![gradio](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/Roboflow/Annotators)
+[![discord](https://img.shields.io/discord/1159501506232451173)](https://discord.gg/GbfgXGJ8Bk)
+[![built-with-material-for-mkdocs](https://img.shields.io/badge/Material_for_MkDocs-526CFE?logo=MaterialForMkDocs&logoColor=white)](https://squidfunk.github.io/mkdocs-material/)
 </div>
 
 ## 👋 hello
@@ -39,7 +39,7 @@ Pip install the supervision package in a
 pip install supervision
 ```
 
-Read more about desktop, headless, and local installation in our [guide](https://roboflow.github.io/supervision/).
+Read more about conda, mamba, and installing from source in our [guide](https://roboflow.github.io/supervision/).
 
 ## 🔥 quickstart
 
diff --git a/docs/index.md b/docs/index.md
index e69ca201c..62768b676 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -30,87 +30,81 @@ We write your reusable computer vision tools. Whether you need to load your data
 
 ## 💻 Install
 
-You can install `supervision` with pip in a
+You can install `supervision` in a 
 [**Python>=3.8**](https://www.python.org/) environment.
 
-!!! success "Installation"
+!!! example "pip install (recommended)"
 
-    !!! example "Pip installation (recommended)"
+    === "headless"
+        The headless installation of `supervision` is designed for environments where graphical user interfaces (GUI) are not needed, making it more lightweight and suitable for server-side applications.
 
-        === "Headless"
-            The headless installation of `supervision` is designed for environments where graphical user interfaces (GUI) are not needed, making it more lightweight and suitable for server-side applications.
+        ```bash
+        pip install supervision
+        ```
 
-            ```bash
-            pip install supervision
-            ```
+    === "desktop"
+        If you require the full version of `supervision` with GUI support you can install the desktop version. This version includes the GUI components of OpenCV, allowing you to display images and videos on the screen.
 
-        === "Desktop"
-            The desktop installation of `supervision` is designed with GUI support. This version includes the GUI components of OpenCV, allowing you to display images and videos on the screen.
+        ```bash
+        pip install "supervision[desktop]"
+        ```
 
-            ```bash
-            pip install "supervision[desktop]"
-            ```
+!!! example "conda/mamba install"
 
-    !!! example "Conda/Mamba installation"
+    === "conda"
 
-        === "conda"
-            The Conda installation of `supervision` is designed for those who prefer using Conda as their package manager. It's especially useful for managing complex dependencies and environments.
+        [![conda-recipe](https://img.shields.io/badge/recipe-supervision-green.svg)](https://anaconda.org/conda-forge/supervision) [![conda-downloads](https://img.shields.io/conda/dn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![conda-version](https://img.shields.io/conda/vn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![conda-platforms](https://img.shields.io/conda/pn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision)
 
-            [![Conda Recipe](https://img.shields.io/badge/recipe-supervision-green.svg)](https://anaconda.org/conda-forge/supervision) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Conda Version](https://img.shields.io/conda/vn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Conda Platforms](https://img.shields.io/conda/pn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision)
+        ```bash
+        conda install -c conda-forge supervision
+        ```
 
+    === "mamba"
 
-            ```bash
-            conda install -c conda-forge supervision
-            ```
+        [![mamba-recipe](https://img.shields.io/badge/recipe-supervision-green.svg)](https://anaconda.org/conda-forge/supervision) [![mamba-downloads](https://img.shields.io/conda/dn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![mamba-version](https://img.shields.io/conda/vn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![mamba-platforms](https://img.shields.io/conda/pn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision)
 
-        === "mamba"
-            The Mamba installation of `supervision` is ideal for those who prefer using Mamba as their package manager.
+        ```bash
+        mamba install -c conda-forge supervision
+        ```
 
-            [![Mamba Recipe](https://img.shields.io/badge/recipe-supervision-green.svg)](https://anaconda.org/conda-forge/supervision) [![Mamba Downloads](https://img.shields.io/conda/dn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Mamba Version](https://img.shields.io/conda/vn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision) [![Mamba Platforms](https://img.shields.io/conda/pn/conda-forge/supervision.svg)](https://anaconda.org/conda-forge/supervision)
+!!! example "git clone (for development)"
 
-            ```bash
-            mamba install -c conda-forge supervision
-            ```
+    === "virtualenv"
 
-    !!! example "git clone (for development)"
+        ```bash
+        # clone repository and navigate to root directory
+        git clone https://github.com/roboflow/supervision.git
+        cd supervision
 
-        === "virtualenv"
+        # setup python environment and activate it
+        python3 -m venv venv
+        source venv/bin/activate
+        pip install --upgrade pip
 
-            ```bash
-            # clone repository and navigate to root directory
-            git clone https://github.com/roboflow/supervision.git
-            cd supervision
+        # headless install
+        pip install -e "."
 
-            # setup python environment and activate it
-            python3 -m venv venv
-            source venv/bin/activate
-            pip install --upgrade pip
+        # desktop install
+        pip install -e ".[desktop]"
+        ```
 
-            # headless install
-            pip install -e "."
+    === "poetry"
 
-            # desktop install
-            pip install -e ".[desktop]"
-            ```
+        ```bash
+        # clone repository and navigate to root directory
+        git clone https://github.com/roboflow/supervision.git
+        cd supervision
 
-        === "poetry"
+        # setup python environment and activate it
+        poetry env use python3.10
+        poetry shell
 
-            ```bash
-            # clone repository and navigate to root directory
-            git clone https://github.com/roboflow/supervision.git
-            cd supervision
-
-            # setup python environment and activate it
-            poetry env use python3.10
-            poetry shell
-
-            # headless install
-            poetry install
-
-            # desktop install
-            poetry install --extras "desktop"
-            ```
+        # headless install
+        poetry install
 
+        # desktop install
+        poetry install --extras "desktop"
+        ```
 
 ## 🚀 Quickstart
 

From 719af725b1751c99713983587dc5c5f9b6a30622 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 28 Mar 2024 17:53:55 +0000
Subject: [PATCH 069/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/index.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/index.md b/docs/index.md
index 62768b676..fc7cda423 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -30,7 +30,7 @@ We write your reusable computer vision tools. Whether you need to load your data
 
 ## 💻 Install
 
-You can install `supervision` in a 
+You can install `supervision` in a
 [**Python>=3.8**](https://www.python.org/) environment.
 
 !!! example "pip install (recommended)"

From a8988d1d4daf531bcf447b33ef5c0b5481af0d0c Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Fri, 29 Mar 2024 01:05:49 +0530
Subject: [PATCH 070/188] Enhance from_transformers to support class name
 extraction for Transformers

---
 supervision/detection/core.py | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 628808629..ef69ea75b 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -424,14 +424,16 @@ def from_transformers(
         """  # noqa: E501 // docs
 
         if "boxes" in transformers_results:
+            class_ids = transformers_results["labels"].cpu().detach().numpy().astype(int)
+            data ={}
+            if id2label is not None:
+                class_names = np.array([id2label[class_id] for class_id in class_ids])
+                data[CLASS_NAME_DATA_FIELD] = class_names
             return cls(
                 xyxy=transformers_results["boxes"].cpu().detach().numpy(),
                 confidence=transformers_results["scores"].cpu().detach().numpy(),
-                class_id=transformers_results["labels"]
-                .cpu()
-                .detach()
-                .numpy()
-                .astype(int),
+                class_id=class_ids,
+                data = data
             )
         masks = transformers_results["masks"].cpu().detach().numpy().astype(bool)
         return cls(

From e6a1d58500e4965b9a042bd136bfad0353a48c60 Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Fri, 29 Mar 2024 01:11:17 +0530
Subject: [PATCH 071/188] Update documentation for from_transformers function

---
 supervision/detection/core.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index ef69ea75b..c8a884f33 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -396,6 +396,11 @@ def from_transformers(
         Creates a Detections instance from object detection or segmentation
         [transformer](https://github.com/huggingface/transformers) inference result.
 
+        Args:
+            transformers_results (dict): A dictionary containing the scores, labels, and boxes for an image
+                as predicted by the Transformers model.
+            id2label (Dict[int, str]): A dictionary mapping class IDs to class names.
+
         Returns:
             Detections: A new Detections object.
 

From 767f9a71482bb94b46a8ee7da8e91f64342a84c7 Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Fri, 29 Mar 2024 01:14:10 +0530
Subject: [PATCH 072/188] formatted code

---
 supervision/detection/core.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index c8a884f33..591bfb9b1 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -429,8 +429,10 @@ def from_transformers(
         """  # noqa: E501 // docs
 
         if "boxes" in transformers_results:
-            class_ids = transformers_results["labels"].cpu().detach().numpy().astype(int)
-            data ={}
+            class_ids = (
+                transformers_results["labels"].cpu().detach().numpy().astype(int)
+            )
+            data = {}
             if id2label is not None:
                 class_names = np.array([id2label[class_id] for class_id in class_ids])
                 data[CLASS_NAME_DATA_FIELD] = class_names
@@ -438,7 +440,7 @@ def from_transformers(
                 xyxy=transformers_results["boxes"].cpu().detach().numpy(),
                 confidence=transformers_results["scores"].cpu().detach().numpy(),
                 class_id=class_ids,
-                data = data
+                data=data,
             )
         masks = transformers_results["masks"].cpu().detach().numpy().astype(bool)
         return cls(

From 7dedc452b70a9b7849ee4841f7815b0b1732c351 Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Fri, 29 Mar 2024 01:44:37 +0530
Subject: [PATCH 073/188] Added missing data field

---
 supervision/detection/core.py | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 591bfb9b1..d34797676 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -428,14 +428,12 @@ def from_transformers(
             ```
         """  # noqa: E501 // docs
 
+        class_ids = transformers_results["labels"].cpu().detach().numpy().astype(int)
+        data = {}
+        if id2label is not None:
+            class_names = np.array([id2label[class_id] for class_id in class_ids])
+            data[CLASS_NAME_DATA_FIELD] = class_names
         if "boxes" in transformers_results:
-            class_ids = (
-                transformers_results["labels"].cpu().detach().numpy().astype(int)
-            )
-            data = {}
-            if id2label is not None:
-                class_names = np.array([id2label[class_id] for class_id in class_ids])
-                data[CLASS_NAME_DATA_FIELD] = class_names
             return cls(
                 xyxy=transformers_results["boxes"].cpu().detach().numpy(),
                 confidence=transformers_results["scores"].cpu().detach().numpy(),
@@ -447,7 +445,8 @@ def from_transformers(
             xyxy=mask_to_xyxy(masks),
             mask=masks,
             confidence=transformers_results["scores"].cpu().detach().numpy(),
-            class_id=transformers_results["labels"].cpu().detach().numpy().astype(int),
+            class_id=class_ids,
+            data=data,
         )
 
     @classmethod

From 90ad1c2c9a95ff753d6fc98fae75849a09516fa1 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 29 Mar 2024 00:38:59 +0000
Subject: [PATCH 074/188] :arrow_up: Bump build from 1.2.0 to 1.2.1

Bumps [build](https://github.com/pypa/build) from 1.2.0 to 1.2.1.
- [Release notes](https://github.com/pypa/build/releases)
- [Changelog](https://github.com/pypa/build/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pypa/build/compare/1.2.0...1.2.1)

---
updated-dependencies:
- dependency-name: build
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 0bc8e6211..16bb568db 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -244,13 +244,13 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "build"
-version = "1.2.0"
+version = "1.2.1"
 description = "A simple, correct Python build frontend"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "build-1.2.0-py3-none-any.whl", hash = "sha256:6105465d9b233433ce8ffa151c760f674446ba766af0290fc14bfa32aef92a04"},
-    {file = "build-1.2.0.tar.gz", hash = "sha256:49df7f8e1e74d345fe71e54f5d56423b2111eda89e3da53a2c18392954dade1d"},
+    {file = "build-1.2.1-py3-none-any.whl", hash = "sha256:75e10f767a433d9a86e50d83f418e83efc18ede923ee5ff7df93b6cb0306c5d4"},
+    {file = "build-1.2.1.tar.gz", hash = "sha256:526263f4870c26f26c433545579475377b2b7588b6f1eac76a001e873ae3e19d"},
 ]
 
 [package.dependencies]

From 8fc541339440be84875a5cd24bfd19536cf3520e Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Mon, 1 Apr 2024 00:32:35 +0300
Subject: [PATCH 075/188] =?UTF-8?q?ci:=20=F0=9F=91=B7=20supervision=20docu?=
 =?UTF-8?q?mentation=20=F0=9F=93=9A=20release=20CI=20added?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 .../{docs.yml => publish-dev-docs.yml}        |  0
 .github/workflows/publish-release-docs.yml    | 55 +++++++++++++++++++
 2 files changed, 55 insertions(+)
 rename .github/workflows/{docs.yml => publish-dev-docs.yml} (100%)
 create mode 100644 .github/workflows/publish-release-docs.yml

diff --git a/.github/workflows/docs.yml b/.github/workflows/publish-dev-docs.yml
similarity index 100%
rename from .github/workflows/docs.yml
rename to .github/workflows/publish-dev-docs.yml
diff --git a/.github/workflows/publish-release-docs.yml b/.github/workflows/publish-release-docs.yml
new file mode 100644
index 000000000..227100332
--- /dev/null
+++ b/.github/workflows/publish-release-docs.yml
@@ -0,0 +1,55 @@
+name: Supervision Release Documentation Workflow 📚
+on:
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event_name == 'push' && github.ref}}
+  cancel-in-progress: true
+
+permissions:
+  contents: write
+  pages: write
+  pull-requests: write
+
+
+jobs:
+  doc-build-deploy:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.10"]
+    steps:
+      - name: 🛎️ Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ github.head_ref }}
+
+      - name: 🐍 Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+      - name: 📦 Install mkdocs-material
+        run: pip install "mkdocs-material"
+      - name: 📦 Install mkdocstrings[python]
+        run: pip install "mkdocstrings[python]"
+      - name: 📦 Install mkdocs-material[imaging]
+        run: pip install "mkdocs-material[imaging]"
+      - name: 📦 Install mike
+        run: pip install "mike"
+      - name: 📦 Install mkdocs-git-revision-date-localized-plugin
+        run: pip install "mkdocs-git-revision-date-localized-plugin"
+      - name: 📦 Install JupyterLab
+        run: pip install jupyterlab
+      - name: 📦 Install mkdocs-jupyter
+        run: pip install mkdocs-jupyter
+      - name: 📦 Install mkdocs-git-committers-plugin-2
+        run: pip install mkdocs-git-committers-plugin-2
+      - name: ⚙️ Configure git for github-actions 👷
+        run: |
+          git config --global user.name "github-actions[bot]"
+          git config --global user.email "41898282+github-actions[bot]@users.noreply.github.com"
+      - name: 🚀 Deploy MkDoc-Material 📚
+        run: |
+            latest_tag=$(git describe --tags `git rev-list --tags --max-count=1`)
+            MKDOCS_GIT_COMMITTERS_APIKEY=${{ secrets.GITHUB_TOKEN }} mike deploy --push --update-aliases $latest_tag latest

From cbc5aa49f549e96d13fb008bd9d4e158da6c808d Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Apr 2024 00:50:45 +0000
Subject: [PATCH 076/188] :arrow_up: Bump mkdocs-material from 9.5.15 to 9.5.16

Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 9.5.15 to 9.5.16.
- [Release notes](https://github.com/squidfunk/mkdocs-material/releases)
- [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG)
- [Commits](https://github.com/squidfunk/mkdocs-material/compare/9.5.15...9.5.16)

---
updated-dependencies:
- dependency-name: mkdocs-material
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 16bb568db..2c1f87fef 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2184,13 +2184,13 @@ test = ["coverage[toml]", "pymdown-extensions", "pytest", "pytest-cov"]
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.15"
+version = "9.5.16"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.15-py3-none-any.whl", hash = "sha256:e5c96dec3d19491de49ca643fc1dbb92b278e43cdb816c775bc47db77d9b62fb"},
-    {file = "mkdocs_material-9.5.15.tar.gz", hash = "sha256:39f03cca45e82bf54eb7456b5a18bd252eabfdd67f237a229471484a0a4d4635"},
+    {file = "mkdocs_material-9.5.16-py3-none-any.whl", hash = "sha256:32fce3cd8ecbd5dca6e5887cc0cf5bc78707a36f7d0f6f1bbbe9edaf428b8055"},
+    {file = "mkdocs_material-9.5.16.tar.gz", hash = "sha256:8b89b639592660f24657bb058de4aff0060cd0383148f8f51711201730f17503"},
 ]
 
 [package.dependencies]

From da5dfef2edb8c21175b805c622c0f56d36731160 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 2 Apr 2024 00:45:56 +0000
Subject: [PATCH 077/188] :arrow_up: Bump ruff from 0.3.4 to 0.3.5

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.3.4 to 0.3.5.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.3.4...v0.3.5)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 2c1f87fef..03d804586 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3646,28 +3646,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.3.4"
+version = "0.3.5"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "ruff-0.3.4-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:60c870a7d46efcbc8385d27ec07fe534ac32f3b251e4fc44b3cbfd9e09609ef4"},
-    {file = "ruff-0.3.4-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:6fc14fa742e1d8f24910e1fff0bd5e26d395b0e0e04cc1b15c7c5e5fe5b4af91"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d3ee7880f653cc03749a3bfea720cf2a192e4f884925b0cf7eecce82f0ce5854"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:cf133dd744f2470b347f602452a88e70dadfbe0fcfb5fd46e093d55da65f82f7"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3f3860057590e810c7ffea75669bdc6927bfd91e29b4baa9258fd48b540a4365"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:986f2377f7cf12efac1f515fc1a5b753c000ed1e0a6de96747cdf2da20a1b369"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c4fd98e85869603e65f554fdc5cddf0712e352fe6e61d29d5a6fe087ec82b76c"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64abeed785dad51801b423fa51840b1764b35d6c461ea8caef9cf9e5e5ab34d9"},
-    {file = "ruff-0.3.4-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:df52972138318bc7546d92348a1ee58449bc3f9eaf0db278906eb511889c4b50"},
-    {file = "ruff-0.3.4-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:98e98300056445ba2cc27d0b325fd044dc17fcc38e4e4d2c7711585bd0a958ed"},
-    {file = "ruff-0.3.4-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:519cf6a0ebed244dce1dc8aecd3dc99add7a2ee15bb68cf19588bb5bf58e0488"},
-    {file = "ruff-0.3.4-py3-none-musllinux_1_2_i686.whl", hash = "sha256:bb0acfb921030d00070539c038cd24bb1df73a2981e9f55942514af8b17be94e"},
-    {file = "ruff-0.3.4-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:cf187a7e7098233d0d0c71175375c5162f880126c4c716fa28a8ac418dcf3378"},
-    {file = "ruff-0.3.4-py3-none-win32.whl", hash = "sha256:af27ac187c0a331e8ef91d84bf1c3c6a5dea97e912a7560ac0cef25c526a4102"},
-    {file = "ruff-0.3.4-py3-none-win_amd64.whl", hash = "sha256:de0d5069b165e5a32b3c6ffbb81c350b1e3d3483347196ffdf86dc0ef9e37dd6"},
-    {file = "ruff-0.3.4-py3-none-win_arm64.whl", hash = "sha256:6810563cc08ad0096b57c717bd78aeac888a1bfd38654d9113cb3dc4d3f74232"},
-    {file = "ruff-0.3.4.tar.gz", hash = "sha256:f0f4484c6541a99862b693e13a151435a279b271cff20e37101116a21e2a1ad1"},
+    {file = "ruff-0.3.5-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:aef5bd3b89e657007e1be6b16553c8813b221ff6d92c7526b7e0227450981eac"},
+    {file = "ruff-0.3.5-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:89b1e92b3bd9fca249153a97d23f29bed3992cff414b222fcd361d763fc53f12"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5e55771559c89272c3ebab23326dc23e7f813e492052391fe7950c1a5a139d89"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:dabc62195bf54b8a7876add6e789caae0268f34582333cda340497c886111c39"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3a05f3793ba25f194f395578579c546ca5d83e0195f992edc32e5907d142bfa3"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:dfd3504e881082959b4160ab02f7a205f0fadc0a9619cc481982b6837b2fd4c0"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:87258e0d4b04046cf1d6cc1c56fadbf7a880cc3de1f7294938e923234cf9e498"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:712e71283fc7d9f95047ed5f793bc019b0b0a29849b14664a60fd66c23b96da1"},
+    {file = "ruff-0.3.5-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a532a90b4a18d3f722c124c513ffb5e5eaff0cc4f6d3aa4bda38e691b8600c9f"},
+    {file = "ruff-0.3.5-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:122de171a147c76ada00f76df533b54676f6e321e61bd8656ae54be326c10296"},
+    {file = "ruff-0.3.5-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:d80a6b18a6c3b6ed25b71b05eba183f37d9bc8b16ace9e3d700997f00b74660b"},
+    {file = "ruff-0.3.5-py3-none-musllinux_1_2_i686.whl", hash = "sha256:a7b6e63194c68bca8e71f81de30cfa6f58ff70393cf45aab4c20f158227d5936"},
+    {file = "ruff-0.3.5-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:a759d33a20c72f2dfa54dae6e85e1225b8e302e8ac655773aff22e542a300985"},
+    {file = "ruff-0.3.5-py3-none-win32.whl", hash = "sha256:9d8605aa990045517c911726d21293ef4baa64f87265896e491a05461cae078d"},
+    {file = "ruff-0.3.5-py3-none-win_amd64.whl", hash = "sha256:dc56bb16a63c1303bd47563c60482a1512721053d93231cf7e9e1c6954395a0e"},
+    {file = "ruff-0.3.5-py3-none-win_arm64.whl", hash = "sha256:faeeae9905446b975dcf6d4499dc93439b131f1443ee264055c5716dd947af55"},
+    {file = "ruff-0.3.5.tar.gz", hash = "sha256:a067daaeb1dc2baf9b82a32dae67d154d95212080c80435eb052d95da647763d"},
 ]
 
 [[package]]

From f21597446bc6b66f8fb6b51545af03c625432197 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 2 Apr 2024 00:47:42 +0000
Subject: [PATCH 078/188] :arrow_up: Bump pillow from 10.2.0 to 10.3.0

Bumps [pillow](https://github.com/python-pillow/Pillow) from 10.2.0 to 10.3.0.
- [Release notes](https://github.com/python-pillow/Pillow/releases)
- [Changelog](https://github.com/python-pillow/Pillow/blob/main/CHANGES.rst)
- [Commits](https://github.com/python-pillow/Pillow/compare/10.2.0...10.3.0)

---
updated-dependencies:
- dependency-name: pillow
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 139 ++++++++++++++++++++++++++--------------------------
 1 file changed, 70 insertions(+), 69 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 2c1f87fef..289d5399e 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2693,79 +2693,80 @@ files = [
 
 [[package]]
 name = "pillow"
-version = "10.2.0"
+version = "10.3.0"
 description = "Python Imaging Library (Fork)"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pillow-10.2.0-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:7823bdd049099efa16e4246bdf15e5a13dbb18a51b68fa06d6c1d4d8b99a796e"},
-    {file = "pillow-10.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:83b2021f2ade7d1ed556bc50a399127d7fb245e725aa0113ebd05cfe88aaf588"},
-    {file = "pillow-10.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6fad5ff2f13d69b7e74ce5b4ecd12cc0ec530fcee76356cac6742785ff71c452"},
-    {file = "pillow-10.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da2b52b37dad6d9ec64e653637a096905b258d2fc2b984c41ae7d08b938a67e4"},
-    {file = "pillow-10.2.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:47c0995fc4e7f79b5cfcab1fc437ff2890b770440f7696a3ba065ee0fd496563"},
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+    {file = "pillow-10.3.0-cp39-cp39-win_arm64.whl", hash = "sha256:50fd3f6b26e3441ae07b7c979309638b72abc1a25da31a81a7fbd9495713ef4f"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-macosx_10_10_x86_64.whl", hash = "sha256:6b02471b72526ab8a18c39cb7967b72d194ec53c1fd0a70b050565a0f366d355"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:8ab74c06ffdab957d7670c2a5a6e1a70181cd10b727cd788c4dd9005b6a8acd9"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:048eeade4c33fdf7e08da40ef402e748df113fd0b4584e32c4af74fe78baaeb2"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9e2ec1e921fd07c7cda7962bad283acc2f2a9ccc1b971ee4b216b75fad6f0463"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:4c8e73e99da7db1b4cad7f8d682cf6abad7844da39834c288fbfa394a47bbced"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:16563993329b79513f59142a6b02055e10514c1a8e86dca8b48a893e33cf91e3"},
+    {file = "pillow-10.3.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:dd78700f5788ae180b5ee8902c6aea5a5726bac7c364b202b4b3e3ba2d293170"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-macosx_10_10_x86_64.whl", hash = "sha256:aff76a55a8aa8364d25400a210a65ff59d0168e0b4285ba6bf2bd83cf675ba32"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:b7bc2176354defba3edc2b9a777744462da2f8e921fbaf61e52acb95bafa9828"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:793b4e24db2e8742ca6423d3fde8396db336698c55cd34b660663ee9e45ed37f"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d93480005693d247f8346bc8ee28c72a2191bdf1f6b5db469c096c0c867ac015"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:c83341b89884e2b2e55886e8fbbf37c3fa5efd6c8907124aeb72f285ae5696e5"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:1a1d1915db1a4fdb2754b9de292642a39a7fb28f1736699527bb649484fb966a"},
+    {file = "pillow-10.3.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:a0eaa93d054751ee9964afa21c06247779b90440ca41d184aeb5d410f20ff591"},
+    {file = "pillow-10.3.0.tar.gz", hash = "sha256:9d2455fbf44c914840c793e89aa82d0e1763a14253a000743719ae5946814b2d"},
 ]
 
 [package.extras]

From a38ae3f840955f6409bc06af1bc4a064089a9145 Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Tue, 2 Apr 2024 16:54:34 +1000
Subject: [PATCH 079/188] Change the method of finding polygon center and
 create test for new function

---
 test/geometry/test_utils.py | 24 ++++++++++++++++++++++++
 1 file changed, 24 insertions(+)
 create mode 100644 test/geometry/test_utils.py

diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
new file mode 100644
index 000000000..39c45216c
--- /dev/null
+++ b/test/geometry/test_utils.py
@@ -0,0 +1,24 @@
+import pytest
+
+import numpy as np
+from supervision.geometry.core import Point, Vector
+from supervision.geometry.utils import get_polygon_center
+
+
+@pytest.mark.parametrize(
+	"polygon, expected_result",
+	[
+		(np.array([[0, 0], [0, 2], [2, 2], [2, 0]]), Point(x=1, y=1)),
+		(np.array([[0, 0], [3, 4], [6, 0]]), Point(x=3, y=1)),
+		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [5, 2]]), Point(x=2, y=2)),
+		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [4, 4], [4, 0]]), Point(x=2, y=2)),
+		(np.array([[0, 2], [2, 4], [4, 2], [2, 0]]), Point(x=2, y=2)),
+		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 1000]]), Point(x=0, y=500)),
+		(np.array([[0, 0], [13, 200], [0, 150]]), Point(x=4, y=100)),
+		(np.array([[0, 0], [0, 1], [1, 1], [1, 2], [2, 2], [2, 3], [3, 3], [3, 0]]), Point(x=2, y=1)),
+	],
+)
+def test_get_polygon_center(polygon: np.ndarray, expected_result: Point) -> None:
+	result = get_polygon_center(polygon)
+	assert result == expected_result
+	
\ No newline at end of file

From 7ded0bd49329af30558025637097730d9db72714 Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Tue, 2 Apr 2024 16:55:03 +1000
Subject: [PATCH 080/188] Change the method of finding polygon center and
 create test for new function

---
 supervision/geometry/utils.py | 19 +++++++++++++------
 1 file changed, 13 insertions(+), 6 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index dd4e64dbe..3d5668fb0 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -9,8 +9,10 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
 
     This function takes in a polygon as a 2-dimensional numpy ndarray and
     returns the center of the polygon as a Point object.
-    The center is calculated as the mean of the polygon's vertices along each axis,
-    and is rounded down to the nearest integer.
+    
+    The center is calculated as center of frame.
+    polygon -> polygon, where p[i] = p[i + 1] + p[i] / 2,
+     with mass = length of vector p[i + 1] - p[i]
 
     Parameters:
         polygon (np.ndarray): A 2-dimensional numpy ndarray representing the
@@ -25,10 +27,15 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         from supervision.geometry.utils import get_polygon_center
         import numpy as np
 
-        vertices = np.array([[0, 0], [0, 1], [1, 1], [1, 0]])
-        get_center(vertices)
-        Point(x=0.5, y=0.5)
+        vertices = np.array([[0, 0], [0, 2], [2, 2], [2, 0]])
+        get_polygon_center(vertices)
+        Point(x=1, y=1)
         ```
     """
-    center = np.mean(polygon, axis=0).astype(int)
+    shifted_polygon = np.roll(polygon, 1, axis=0)
+    points = (shifted_polygon + polygon) / 2
+    vectors = shifted_polygon - polygon
+    mass = (vectors[:, 0] ** 2 + vectors[:, 1] ** 2) ** 0.5
+    mass = np.array([mass, mass]).T
+    center = (np.sum(points * mass, axis=0) / np.sum(mass) * 2).round()
     return Point(x=center[0], y=center[1])

From dcad812c5c923252d2f8860dfebeb042e7fd3305 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 2 Apr 2024 07:15:13 +0000
Subject: [PATCH 081/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/geometry/utils.py |  2 +-
 test/geometry/test_utils.py   | 40 +++++++++++++++++++++--------------
 2 files changed, 25 insertions(+), 17 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 3d5668fb0..5748cfa08 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -9,7 +9,7 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
 
     This function takes in a polygon as a 2-dimensional numpy ndarray and
     returns the center of the polygon as a Point object.
-    
+
     The center is calculated as center of frame.
     polygon -> polygon, where p[i] = p[i + 1] + p[i] / 2,
      with mass = length of vector p[i + 1] - p[i]
diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index 39c45216c..5457463bd 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -1,24 +1,32 @@
+import numpy as np
 import pytest
 
-import numpy as np
-from supervision.geometry.core import Point, Vector
+from supervision.geometry.core import Point
 from supervision.geometry.utils import get_polygon_center
 
 
 @pytest.mark.parametrize(
-	"polygon, expected_result",
-	[
-		(np.array([[0, 0], [0, 2], [2, 2], [2, 0]]), Point(x=1, y=1)),
-		(np.array([[0, 0], [3, 4], [6, 0]]), Point(x=3, y=1)),
-		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [5, 2]]), Point(x=2, y=2)),
-		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [4, 4], [4, 0]]), Point(x=2, y=2)),
-		(np.array([[0, 2], [2, 4], [4, 2], [2, 0]]), Point(x=2, y=2)),
-		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 1000]]), Point(x=0, y=500)),
-		(np.array([[0, 0], [13, 200], [0, 150]]), Point(x=4, y=100)),
-		(np.array([[0, 0], [0, 1], [1, 1], [1, 2], [2, 2], [2, 3], [3, 3], [3, 0]]), Point(x=2, y=1)),
-	],
+    "polygon, expected_result",
+    [
+        (np.array([[0, 0], [0, 2], [2, 2], [2, 0]]), Point(x=1, y=1)),
+        (np.array([[0, 0], [3, 4], [6, 0]]), Point(x=3, y=1)),
+        (np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [5, 2]]), Point(x=2, y=2)),
+        (
+            np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [4, 4], [4, 0]]),
+            Point(x=2, y=2),
+        ),
+        (np.array([[0, 2], [2, 4], [4, 2], [2, 0]]), Point(x=2, y=2)),
+        (
+            np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 1000]]),
+            Point(x=0, y=500),
+        ),
+        (np.array([[0, 0], [13, 200], [0, 150]]), Point(x=4, y=100)),
+        (
+            np.array([[0, 0], [0, 1], [1, 1], [1, 2], [2, 2], [2, 3], [3, 3], [3, 0]]),
+            Point(x=2, y=1),
+        ),
+    ],
 )
 def test_get_polygon_center(polygon: np.ndarray, expected_result: Point) -> None:
-	result = get_polygon_center(polygon)
-	assert result == expected_result
-	
\ No newline at end of file
+    result = get_polygon_center(polygon)
+    assert result == expected_result

From b02e8664a11413d82d5b42c91bdbc7264fea5c9b Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Tue, 2 Apr 2024 18:39:24 +0530
Subject: [PATCH 082/188] mark id2label as Optional in from_transformers docs

---
 supervision/detection/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index d34797676..a4bdb7dcf 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -399,7 +399,7 @@ def from_transformers(
         Args:
             transformers_results (dict): A dictionary containing the scores, labels, and boxes for an image
                 as predicted by the Transformers model.
-            id2label (Dict[int, str]): A dictionary mapping class IDs to class names.
+            id2label (Optional[Dict[int, str]]): A dictionary mapping class IDs to class names. If None, class names will not be included.
 
         Returns:
             Detections: A new Detections object.

From b6b72eddcea48d71fd3d809355d701c749487820 Mon Sep 17 00:00:00 2001
From: jeslinpjames <jeslinpjames007@gmail.com>
Date: Tue, 2 Apr 2024 18:53:42 +0530
Subject: [PATCH 083/188] add defensive checks to from_transformers

---
 supervision/detection/core.py | 21 +++++++++++++--------
 1 file changed, 13 insertions(+), 8 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index a4bdb7dcf..554495ab1 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -440,14 +440,19 @@ def from_transformers(
                 class_id=class_ids,
                 data=data,
             )
-        masks = transformers_results["masks"].cpu().detach().numpy().astype(bool)
-        return cls(
-            xyxy=mask_to_xyxy(masks),
-            mask=masks,
-            confidence=transformers_results["scores"].cpu().detach().numpy(),
-            class_id=class_ids,
-            data=data,
-        )
+        elif "masks" in transformers_results:
+            masks = transformers_results["masks"].cpu().detach().numpy().astype(bool)
+            return cls(
+                xyxy=mask_to_xyxy(masks),
+                mask=masks,
+                confidence=transformers_results["scores"].cpu().detach().numpy(),
+                class_id=class_ids,
+                data=data,
+            )
+        else:
+            raise NotImplementedError(
+                "Only object detection and semantic segmentation results are supported."
+            )
 
     @classmethod
     def from_detectron2(cls, detectron2_results) -> Detections:

From f15a6224ff642eaee8b42352b0366c470023f1f6 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 3 Apr 2024 00:30:06 +0000
Subject: [PATCH 084/188] :arrow_up: Bump mkdocstrings from 0.24.1 to 0.24.2

Bumps [mkdocstrings](https://github.com/mkdocstrings/mkdocstrings) from 0.24.1 to 0.24.2.
- [Release notes](https://github.com/mkdocstrings/mkdocstrings/releases)
- [Changelog](https://github.com/mkdocstrings/mkdocstrings/blob/main/CHANGELOG.md)
- [Commits](https://github.com/mkdocstrings/mkdocstrings/compare/0.24.1...0.24.2)

---
updated-dependencies:
- dependency-name: mkdocstrings
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 4e0d724b8..1a98292c5 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2226,13 +2226,13 @@ files = [
 
 [[package]]
 name = "mkdocstrings"
-version = "0.24.1"
+version = "0.24.2"
 description = "Automatic documentation from sources, for MkDocs."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocstrings-0.24.1-py3-none-any.whl", hash = "sha256:b4206f9a2ca8a648e222d5a0ca1d36ba7dee53c88732818de183b536f9042b5d"},
-    {file = "mkdocstrings-0.24.1.tar.gz", hash = "sha256:cc83f9a1c8724fc1be3c2fa071dd73d91ce902ef6a79710249ec8d0ee1064401"},
+    {file = "mkdocstrings-0.24.2-py3-none-any.whl", hash = "sha256:61440b77542170238099a7d87882c3417897771950e3aafe6e22abff3d1c51fb"},
+    {file = "mkdocstrings-0.24.2.tar.gz", hash = "sha256:b91b9cdd9490ef2e8957000bff1d34a4b308b9cd57b10f26169f085def4c6a92"},
 ]
 
 [package.dependencies]

From 79c731b431ba794aeadddbb807db3c4ea2a9d42d Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 3 Apr 2024 00:35:04 +0000
Subject: [PATCH 085/188] :arrow_up: Bump mkdocs-material from 9.5.16 to 9.5.17

Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 9.5.16 to 9.5.17.
- [Release notes](https://github.com/squidfunk/mkdocs-material/releases)
- [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG)
- [Commits](https://github.com/squidfunk/mkdocs-material/compare/9.5.16...9.5.17)

---
updated-dependencies:
- dependency-name: mkdocs-material
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 4e0d724b8..2cbee4dd3 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2184,13 +2184,13 @@ test = ["coverage[toml]", "pymdown-extensions", "pytest", "pytest-cov"]
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.16"
+version = "9.5.17"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.16-py3-none-any.whl", hash = "sha256:32fce3cd8ecbd5dca6e5887cc0cf5bc78707a36f7d0f6f1bbbe9edaf428b8055"},
-    {file = "mkdocs_material-9.5.16.tar.gz", hash = "sha256:8b89b639592660f24657bb058de4aff0060cd0383148f8f51711201730f17503"},
+    {file = "mkdocs_material-9.5.17-py3-none-any.whl", hash = "sha256:14a2a60119a785e70e765dd033e6211367aca9fc70230e577c1cf6a326949571"},
+    {file = "mkdocs_material-9.5.17.tar.gz", hash = "sha256:06ae1275a72db1989cf6209de9e9ecdfbcfdbc24c58353877b2bb927dbe413e4"},
 ]
 
 [package.dependencies]

From cd81c1cef4ac53cdecff7d554a813d3d90362f61 Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Wed, 3 Apr 2024 20:40:54 +1000
Subject: [PATCH 086/188] Updated algorithm

---
 supervision/geometry/utils.py |  9 ++++----
 test/geometry/test_utils.py   | 40 +++++++++++++++++++++--------------
 2 files changed, 29 insertions(+), 20 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 3d5668fb0..401f672e0 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -9,7 +9,7 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
 
     This function takes in a polygon as a 2-dimensional numpy ndarray and
     returns the center of the polygon as a Point object.
-    
+
     The center is calculated as center of frame.
     polygon -> polygon, where p[i] = p[i + 1] + p[i] / 2,
      with mass = length of vector p[i + 1] - p[i]
@@ -32,10 +32,11 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         Point(x=1, y=1)
         ```
     """
+    polygon = polygon.astype(np.float32)
     shifted_polygon = np.roll(polygon, 1, axis=0)
     points = (shifted_polygon + polygon) / 2
     vectors = shifted_polygon - polygon
-    mass = (vectors[:, 0] ** 2 + vectors[:, 1] ** 2) ** 0.5
-    mass = np.array([mass, mass]).T
-    center = (np.sum(points * mass, axis=0) / np.sum(mass) * 2).round()
+    mass = np.sum(vectors ** 2, axis=1) ** 0.5
+    center = ((mass @ points) / np.sum(mass)).round()
+    
     return Point(x=center[0], y=center[1])
diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index 39c45216c..5457463bd 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -1,24 +1,32 @@
+import numpy as np
 import pytest
 
-import numpy as np
-from supervision.geometry.core import Point, Vector
+from supervision.geometry.core import Point
 from supervision.geometry.utils import get_polygon_center
 
 
 @pytest.mark.parametrize(
-	"polygon, expected_result",
-	[
-		(np.array([[0, 0], [0, 2], [2, 2], [2, 0]]), Point(x=1, y=1)),
-		(np.array([[0, 0], [3, 4], [6, 0]]), Point(x=3, y=1)),
-		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [5, 2]]), Point(x=2, y=2)),
-		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [4, 4], [4, 0]]), Point(x=2, y=2)),
-		(np.array([[0, 2], [2, 4], [4, 2], [2, 0]]), Point(x=2, y=2)),
-		(np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 1000]]), Point(x=0, y=500)),
-		(np.array([[0, 0], [13, 200], [0, 150]]), Point(x=4, y=100)),
-		(np.array([[0, 0], [0, 1], [1, 1], [1, 2], [2, 2], [2, 3], [3, 3], [3, 0]]), Point(x=2, y=1)),
-	],
+    "polygon, expected_result",
+    [
+        (np.array([[0, 0], [0, 2], [2, 2], [2, 0]]), Point(x=1, y=1)),
+        (np.array([[0, 0], [3, 4], [6, 0]]), Point(x=3, y=1)),
+        (np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [5, 2]]), Point(x=2, y=2)),
+        (
+            np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [4, 4], [4, 0]]),
+            Point(x=2, y=2),
+        ),
+        (np.array([[0, 2], [2, 4], [4, 2], [2, 0]]), Point(x=2, y=2)),
+        (
+            np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 1000]]),
+            Point(x=0, y=500),
+        ),
+        (np.array([[0, 0], [13, 200], [0, 150]]), Point(x=4, y=100)),
+        (
+            np.array([[0, 0], [0, 1], [1, 1], [1, 2], [2, 2], [2, 3], [3, 3], [3, 0]]),
+            Point(x=2, y=1),
+        ),
+    ],
 )
 def test_get_polygon_center(polygon: np.ndarray, expected_result: Point) -> None:
-	result = get_polygon_center(polygon)
-	assert result == expected_result
-	
\ No newline at end of file
+    result = get_polygon_center(polygon)
+    assert result == expected_result

From 960e2529b152b4fd8a96830d3e3a8628da771de8 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 3 Apr 2024 10:44:24 +0000
Subject: [PATCH 087/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/geometry/utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 401f672e0..48a19b2dc 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -36,7 +36,7 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
     shifted_polygon = np.roll(polygon, 1, axis=0)
     points = (shifted_polygon + polygon) / 2
     vectors = shifted_polygon - polygon
-    mass = np.sum(vectors ** 2, axis=1) ** 0.5
+    mass = np.sum(vectors**2, axis=1) ** 0.5
     center = ((mass @ points) / np.sum(mass)).round()
-    
+
     return Point(x=center[0], y=center[1])

From eb3317694eacb958596371303c11da28513e30c8 Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Thu, 4 Apr 2024 14:57:57 +1000
Subject: [PATCH 088/188] Include all three algorithms

---
 supervision/geometry/utils.py | 60 +++++++++++++++++++++++++++++++----
 test/geometry/test_utils.py   | 54 +++++++++++++++++++++----------
 2 files changed, 90 insertions(+), 24 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 401f672e0..6e2932145 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -3,6 +3,50 @@
 from supervision.geometry.core import Point
 
 
+class PolygonCenterGetter:
+    
+    @staticmethod
+    def mean_algo(polygon: np.ndarray) -> Point:
+        """
+        Calculate the center of the polygon as the center of mass
+        of the points.
+        """
+        center = np.mean(polygon, axis=0).astype(int)
+        
+        return Point(x=center[0], y=center[1])
+    
+    @staticmethod
+    def frame_algo(polygon: np.ndarray) -> Point:
+        """
+        Calculate the center of the polygon as the center of mass
+        of the frame formed by the points of this polygon.
+        """
+        polygon = polygon.astype(np.float32)
+        shifted_polygon = np.roll(polygon, 1, axis=0)
+        points = (shifted_polygon + polygon) / 2
+        vectors = shifted_polygon - polygon
+        mass = np.sum(vectors ** 2, axis=1) ** 0.5
+        center = np.dot(mass, points) / np.sum(mass)
+        center = center.astype(int)
+        
+        return Point(x=center[0], y=center[1])
+    
+    @staticmethod
+    def solid_algo(polygon: np.ndarray) -> Point:
+        """
+        Calculate the center of the polygon as the center of mass
+        of a solid homogeneous figure
+        """
+        shift_polygon = np.roll(polygon, -1, axis=0)
+        signed_areas = np.cross(polygon, shift_polygon) / 2
+        if signed_areas.sum() == 0:
+            center = np.mean(polygon, axis=0).astype(int)
+            return Point(x=center[0], y=center[1])
+        centroids = (polygon + shift_polygon) / 3.0
+        center = np.average(centroids, axis=0, weights=signed_areas).astype(int)
+        return Point(x=center[0], y=center[1])
+
+
 def get_polygon_center(polygon: np.ndarray) -> Point:
     """
     Calculate the center of a polygon.
@@ -32,11 +76,13 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         Point(x=1, y=1)
         ```
     """
-    polygon = polygon.astype(np.float32)
-    shifted_polygon = np.roll(polygon, 1, axis=0)
-    points = (shifted_polygon + polygon) / 2
-    vectors = shifted_polygon - polygon
-    mass = np.sum(vectors ** 2, axis=1) ** 0.5
-    center = ((mass @ points) / np.sum(mass)).round()
     
-    return Point(x=center[0], y=center[1])
+    n: int = polygon.shape[0]  # amount of points
+    
+    if n <= 10 ** 2:
+        return PolygonCenterGetter.mean_algo(polygon)
+    
+    if n <= 10 ** 4:
+        return PolygonCenterGetter.solid_algo(polygon)
+    
+    return PolygonCenterGetter.frame_algo(polygon)
diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index 5457463bd..bb6ec60b8 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -5,26 +5,46 @@
 from supervision.geometry.utils import get_polygon_center
 
 
+def generate_test_polygon(n: int) -> np.ndarray:
+    """
+    Generate a semicircle with a given number of points.
+    
+    Parameters:
+        n (int): amount of points in polygon
+
+    Returns:
+        Polygon: test polygon in the form of a semicircle.
+        
+   Examples:
+        ```python
+        from supervision.geometry.utils import get_polygon_center
+        import numpy as np
+    
+        test_polygon = generate_test_data(1000)
+        
+        get_polygon_center(test_polygon)
+        Point(x=500, y=1212)
+        ```
+    """
+    r: int = n // 2
+    x_axis = np.linspace(0, 2 * r, n)
+    y_axis = (r ** 2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
+    polygon = np.array([x_axis, y_axis]).T
+    
+    return polygon
+    
+
 @pytest.mark.parametrize(
     "polygon, expected_result",
     [
-        (np.array([[0, 0], [0, 2], [2, 2], [2, 0]]), Point(x=1, y=1)),
-        (np.array([[0, 0], [3, 4], [6, 0]]), Point(x=3, y=1)),
-        (np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [5, 2]]), Point(x=2, y=2)),
-        (
-            np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [4, 4], [4, 0]]),
-            Point(x=2, y=2),
-        ),
-        (np.array([[0, 2], [2, 4], [4, 2], [2, 0]]), Point(x=2, y=2)),
-        (
-            np.array([[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 1000]]),
-            Point(x=0, y=500),
-        ),
-        (np.array([[0, 0], [13, 200], [0, 150]]), Point(x=4, y=100)),
-        (
-            np.array([[0, 0], [0, 1], [1, 1], [1, 2], [2, 2], [2, 3], [3, 3], [3, 0]]),
-            Point(x=2, y=1),
-        ),
+        (generate_test_polygon(10), Point(x=5, y=13)),
+        (generate_test_polygon(50), Point(x=25, y=69)),
+        (generate_test_polygon(100), Point(x=50, y=138)),
+        (generate_test_polygon(1000), Point(x=500, y=1212)),
+        (generate_test_polygon(3000), Point(x=1499, y=3636)),
+        (generate_test_polygon(10000), Point(x=5000, y=12122)),
+        (generate_test_polygon(20000), Point(x=9999, y=23889)),
+        (generate_test_polygon(50000), Point(x=25000, y=59724)),
     ],
 )
 def test_get_polygon_center(polygon: np.ndarray, expected_result: Point) -> None:

From 8de73738c7939cdc22cab62b5cf7b008fde0458b Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 4 Apr 2024 04:59:29 +0000
Subject: [PATCH 089/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/geometry/utils.py |  4 ++--
 test/geometry/test_utils.py   | 42 +++++++++++++++++------------------
 2 files changed, 23 insertions(+), 23 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 401f672e0..48a19b2dc 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -36,7 +36,7 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
     shifted_polygon = np.roll(polygon, 1, axis=0)
     points = (shifted_polygon + polygon) / 2
     vectors = shifted_polygon - polygon
-    mass = np.sum(vectors ** 2, axis=1) ** 0.5
+    mass = np.sum(vectors**2, axis=1) ** 0.5
     center = ((mass @ points) / np.sum(mass)).round()
-    
+
     return Point(x=center[0], y=center[1])
diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index bb6ec60b8..46963716c 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -7,32 +7,32 @@
 
 def generate_test_polygon(n: int) -> np.ndarray:
     """
-    Generate a semicircle with a given number of points.
-    
-    Parameters:
-        n (int): amount of points in polygon
-
-    Returns:
-        Polygon: test polygon in the form of a semicircle.
-        
-   Examples:
-        ```python
-        from supervision.geometry.utils import get_polygon_center
-        import numpy as np
-    
-        test_polygon = generate_test_data(1000)
-        
-        get_polygon_center(test_polygon)
-        Point(x=500, y=1212)
-        ```
+     Generate a semicircle with a given number of points.
+
+     Parameters:
+         n (int): amount of points in polygon
+
+     Returns:
+         Polygon: test polygon in the form of a semicircle.
+
+    Examples:
+         ```python
+         from supervision.geometry.utils import get_polygon_center
+         import numpy as np
+
+         test_polygon = generate_test_data(1000)
+
+         get_polygon_center(test_polygon)
+         Point(x=500, y=1212)
+         ```
     """
     r: int = n // 2
     x_axis = np.linspace(0, 2 * r, n)
-    y_axis = (r ** 2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
+    y_axis = (r**2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
     polygon = np.array([x_axis, y_axis]).T
-    
+
     return polygon
-    
+
 
 @pytest.mark.parametrize(
     "polygon, expected_result",

From c8ea42af6df5084ddccbbbdd9cc18430b90a82a4 Mon Sep 17 00:00:00 2001
From: macc-n <macc.nicola@gmail.com>
Date: Thu, 4 Apr 2024 17:32:41 +0200
Subject: [PATCH 090/188] Fixed obb key check in ultralytics_results

---
 supervision/detection/core.py | 35 +++++++++++++++++++----------------
 1 file changed, 19 insertions(+), 16 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 8c29cfc48..e378e4c82 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -208,22 +208,25 @@ def from_ultralytics(cls, ultralytics_results) -> Detections:
             ```
         """  # noqa: E501 // docs
 
-        if ultralytics_results.obb is not None:
-            class_id = ultralytics_results.obb.cls.cpu().numpy().astype(int)
-            class_names = np.array([ultralytics_results.names[i] for i in class_id])
-            oriented_box_coordinates = ultralytics_results.obb.xyxyxyxy.cpu().numpy()
-            return cls(
-                xyxy=ultralytics_results.obb.xyxy.cpu().numpy(),
-                confidence=ultralytics_results.obb.conf.cpu().numpy(),
-                class_id=class_id,
-                tracker_id=ultralytics_results.obb.id.int().cpu().numpy()
-                if ultralytics_results.obb.id is not None
-                else None,
-                data={
-                    ORIENTED_BOX_COORDINATES: oriented_box_coordinates,
-                    CLASS_NAME_DATA_FIELD: class_names,
-                },
-            )
+        if "obb" in ultralytics_results:
+            if ultralytics_results.obb is not None:
+                class_id = ultralytics_results.obb.cls.cpu().numpy().astype(int)
+                class_names = np.array([ultralytics_results.names[i] for i in class_id])
+                oriented_box_coordinates = (
+                    ultralytics_results.obb.xyxyxyxy.cpu().numpy()
+                )
+                return cls(
+                    xyxy=ultralytics_results.obb.xyxy.cpu().numpy(),
+                    confidence=ultralytics_results.obb.conf.cpu().numpy(),
+                    class_id=class_id,
+                    tracker_id=ultralytics_results.obb.id.int().cpu().numpy()
+                    if ultralytics_results.obb.id is not None
+                    else None,
+                    data={
+                        ORIENTED_BOX_COORDINATES: oriented_box_coordinates,
+                        CLASS_NAME_DATA_FIELD: class_names,
+                    },
+                )
 
         class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
         class_names = np.array([ultralytics_results.names[i] for i in class_id])

From 0b86478417aec5eb5841618882e221fd7c999185 Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Fri, 5 Apr 2024 02:00:54 +1000
Subject: [PATCH 091/188] Only solid algorithm geometry/utils

---
 supervision/geometry/utils.py | 20 ++++++++++----------
 test/geometry/test_utils.py   | 12 ++++++------
 2 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 48a19b2dc..e0fae5b41 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -10,9 +10,8 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
     This function takes in a polygon as a 2-dimensional numpy ndarray and
     returns the center of the polygon as a Point object.
 
-    The center is calculated as center of frame.
-    polygon -> polygon, where p[i] = p[i + 1] + p[i] / 2,
-     with mass = length of vector p[i + 1] - p[i]
+    Еhe center is calculated as the center
+    of the solid figure formed by the points of the polygon
 
     Parameters:
         polygon (np.ndarray): A 2-dimensional numpy ndarray representing the
@@ -32,11 +31,12 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         Point(x=1, y=1)
         ```
     """
-    polygon = polygon.astype(np.float32)
-    shifted_polygon = np.roll(polygon, 1, axis=0)
-    points = (shifted_polygon + polygon) / 2
-    vectors = shifted_polygon - polygon
-    mass = np.sum(vectors**2, axis=1) ** 0.5
-    center = ((mass @ points) / np.sum(mass)).round()
-
+    shift_polygon = np.roll(polygon, -1, axis=0)
+    signed_areas = np.cross(polygon, shift_polygon) / 2
+    if signed_areas.sum() == 0:
+        center = np.mean(polygon, axis=0).round()
+        return Point(x=center[0], y=center[1])
+    centroids = (polygon + shift_polygon) / 3.0
+    center = np.average(centroids, axis=0, weights=signed_areas).round()
+    
     return Point(x=center[0], y=center[1])
diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index 46963716c..c98e1128f 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -28,7 +28,7 @@ def generate_test_polygon(n: int) -> np.ndarray:
     """
     r: int = n // 2
     x_axis = np.linspace(0, 2 * r, n)
-    y_axis = (r**2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
+    y_axis = (r ** 2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
     polygon = np.array([x_axis, y_axis]).T
 
     return polygon
@@ -37,14 +37,14 @@ def generate_test_polygon(n: int) -> np.ndarray:
 @pytest.mark.parametrize(
     "polygon, expected_result",
     [
-        (generate_test_polygon(10), Point(x=5, y=13)),
-        (generate_test_polygon(50), Point(x=25, y=69)),
-        (generate_test_polygon(100), Point(x=50, y=138)),
+        (generate_test_polygon(10), Point(x=4, y=12)),
+        (generate_test_polygon(50), Point(x=24, y=60)),
+        (generate_test_polygon(100), Point(x=49, y=121)),
         (generate_test_polygon(1000), Point(x=500, y=1212)),
         (generate_test_polygon(3000), Point(x=1499, y=3636)),
         (generate_test_polygon(10000), Point(x=5000, y=12122)),
-        (generate_test_polygon(20000), Point(x=9999, y=23889)),
-        (generate_test_polygon(50000), Point(x=25000, y=59724)),
+        (generate_test_polygon(20000), Point(x=10000, y=24244)),
+        (generate_test_polygon(50000), Point(x=24999, y=60610)),
     ],
 )
 def test_get_polygon_center(polygon: np.ndarray, expected_result: Point) -> None:

From 5f0082048c9e80e01a672012fd2f9fdfea9c9d2f Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 4 Apr 2024 16:01:19 +0000
Subject: [PATCH 092/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/geometry/utils.py | 2 +-
 test/geometry/test_utils.py   | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index e0fae5b41..69547751e 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -38,5 +38,5 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         return Point(x=center[0], y=center[1])
     centroids = (polygon + shift_polygon) / 3.0
     center = np.average(centroids, axis=0, weights=signed_areas).round()
-    
+
     return Point(x=center[0], y=center[1])
diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index c98e1128f..49e850524 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -28,7 +28,7 @@ def generate_test_polygon(n: int) -> np.ndarray:
     """
     r: int = n // 2
     x_axis = np.linspace(0, 2 * r, n)
-    y_axis = (r ** 2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
+    y_axis = (r**2 - (x_axis - r) ** 2) ** 0.5 + 2 * r
     polygon = np.array([x_axis, y_axis]).T
 
     return polygon

From 761fb89241af459f5d84fbcaa459b2993ab595bf Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Fri, 5 Apr 2024 02:03:53 +1000
Subject: [PATCH 093/188] Fixed test/geometry/test_utils

---
 test/geometry/test_utils.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/test/geometry/test_utils.py b/test/geometry/test_utils.py
index c98e1128f..2daba3914 100644
--- a/test/geometry/test_utils.py
+++ b/test/geometry/test_utils.py
@@ -37,14 +37,14 @@ def generate_test_polygon(n: int) -> np.ndarray:
 @pytest.mark.parametrize(
     "polygon, expected_result",
     [
-        (generate_test_polygon(10), Point(x=4, y=12)),
-        (generate_test_polygon(50), Point(x=24, y=60)),
-        (generate_test_polygon(100), Point(x=49, y=121)),
-        (generate_test_polygon(1000), Point(x=500, y=1212)),
-        (generate_test_polygon(3000), Point(x=1499, y=3636)),
-        (generate_test_polygon(10000), Point(x=5000, y=12122)),
-        (generate_test_polygon(20000), Point(x=10000, y=24244)),
-        (generate_test_polygon(50000), Point(x=24999, y=60610)),
+        (generate_test_polygon(10), Point(x=5.0, y=12.0)),
+        (generate_test_polygon(50), Point(x=25.0, y=61.0)),
+        (generate_test_polygon(100), Point(x=50.0, y=121.0)),
+        (generate_test_polygon(1000), Point(x=500.0, y=1212.0)),
+        (generate_test_polygon(3000), Point(x=1500.0, y=3637.0)),
+        (generate_test_polygon(10000), Point(x=5000.0, y=12122.0)),
+        (generate_test_polygon(20000), Point(x=10000.0, y=24244.0)),
+        (generate_test_polygon(50000), Point(x=25000.0, y=60610.0)),
     ],
 )
 def test_get_polygon_center(polygon: np.ndarray, expected_result: Point) -> None:

From c605687f82e5c44bc7763759f28800879e893f60 Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Fri, 5 Apr 2024 02:06:03 +1000
Subject: [PATCH 094/188] Ehe fix :)

---
 supervision/geometry/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 69547751e..9a49e1854 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -10,7 +10,7 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
     This function takes in a polygon as a 2-dimensional numpy ndarray and
     returns the center of the polygon as a Point object.
 
-    Еhe center is calculated as the center
+    The center is calculated as the center
     of the solid figure formed by the points of the polygon
 
     Parameters:

From 57335ef98614a3b2ebd10cf07f4a66674d45ff5c Mon Sep 17 00:00:00 2001
From: sharingan000 <sharingan202@yandex.ru>
Date: Fri, 5 Apr 2024 02:14:44 +1000
Subject: [PATCH 095/188] just comments

---
 supervision/geometry/utils.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 9a49e1854..e13541708 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -31,6 +31,10 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         Point(x=1, y=1)
         ```
     """
+    
+    # This is one of the 3 candidate algorithms considered for centroid calculation.
+    # For a more detailed discussion, see PR #1084 and commit eb33176
+    
     shift_polygon = np.roll(polygon, -1, axis=0)
     signed_areas = np.cross(polygon, shift_polygon) / 2
     if signed_areas.sum() == 0:

From 7e21aaaa1abcae53226bce5ec89356393237f840 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 4 Apr 2024 16:16:33 +0000
Subject: [PATCH 096/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/geometry/utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index e13541708..9cf717e49 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -31,10 +31,10 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
         Point(x=1, y=1)
         ```
     """
-    
+
     # This is one of the 3 candidate algorithms considered for centroid calculation.
     # For a more detailed discussion, see PR #1084 and commit eb33176
-    
+
     shift_polygon = np.roll(polygon, -1, axis=0)
     signed_areas = np.cross(polygon, shift_polygon) / 2
     if signed_areas.sum() == 0:

From 79da48fc49e479389cbae91f1b40828a523b9512 Mon Sep 17 00:00:00 2001
From: macc-n <macc.nicola@gmail.com>
Date: Thu, 4 Apr 2024 18:45:42 +0200
Subject: [PATCH 097/188] If conditions merged

---
 supervision/detection/core.py | 35 ++++++++++++++++-------------------
 1 file changed, 16 insertions(+), 19 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index e378e4c82..1605a7d28 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -208,25 +208,22 @@ def from_ultralytics(cls, ultralytics_results) -> Detections:
             ```
         """  # noqa: E501 // docs
 
-        if "obb" in ultralytics_results:
-            if ultralytics_results.obb is not None:
-                class_id = ultralytics_results.obb.cls.cpu().numpy().astype(int)
-                class_names = np.array([ultralytics_results.names[i] for i in class_id])
-                oriented_box_coordinates = (
-                    ultralytics_results.obb.xyxyxyxy.cpu().numpy()
-                )
-                return cls(
-                    xyxy=ultralytics_results.obb.xyxy.cpu().numpy(),
-                    confidence=ultralytics_results.obb.conf.cpu().numpy(),
-                    class_id=class_id,
-                    tracker_id=ultralytics_results.obb.id.int().cpu().numpy()
-                    if ultralytics_results.obb.id is not None
-                    else None,
-                    data={
-                        ORIENTED_BOX_COORDINATES: oriented_box_coordinates,
-                        CLASS_NAME_DATA_FIELD: class_names,
-                    },
-                )
+        if "obb" in ultralytics_results and ultralytics_results.obb is not None:
+            class_id = ultralytics_results.obb.cls.cpu().numpy().astype(int)
+            class_names = np.array([ultralytics_results.names[i] for i in class_id])
+            oriented_box_coordinates = ultralytics_results.obb.xyxyxyxy.cpu().numpy()
+            return cls(
+                xyxy=ultralytics_results.obb.xyxy.cpu().numpy(),
+                confidence=ultralytics_results.obb.conf.cpu().numpy(),
+                class_id=class_id,
+                tracker_id=ultralytics_results.obb.id.int().cpu().numpy()
+                if ultralytics_results.obb.id is not None
+                else None,
+                data={
+                    ORIENTED_BOX_COORDINATES: oriented_box_coordinates,
+                    CLASS_NAME_DATA_FIELD: class_names,
+                },
+            )
 
         class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
         class_names = np.array([ultralytics_results.names[i] for i in class_id])

From ee38ba36c4ce698f599daf6d58195a031c4e86df Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 5 Apr 2024 11:49:43 +0200
Subject: [PATCH 098/188] docs improvements

---
 docs/how_to/detect_and_annotate.md | 34 ++++++++++++++++++------------
 supervision/detection/core.py      | 25 ++++++++++++++++------
 2 files changed, 39 insertions(+), 20 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 7bc2f9708..cdd13030a 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -102,7 +102,7 @@ Now that we have predictions from a model, we can load them into Supervision.
 
     We can do so using the [`sv.Detections.from_transformers`](detection/core/#supervision.detection.core.Detections.from_transformers) method, which accepts model results from both detection and segmentation models.
 
-    ```{ .py hl_lines="2 19" }
+    ```{ .py hl_lines="2 19-21" }
     import torch
     import supervision as sv
     from PIL import Image
@@ -121,7 +121,9 @@ Now that we have predictions from a model, we can load them into Supervision.
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
-    detections = sv.Detections.from_transformers(results)
+    detections = sv.Detections.from_transformers(
+        transformers_results=results, 
+        id2label=model.config.id2label)
     ```
 
 You can load predictions from other computer vision frameworks and libraries using:
@@ -180,7 +182,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
 
 === "Transformers"
 
-    ```{ .py hl_lines="21-27" }
+    ```{ .py hl_lines="23-30" }
     import torch
     import supervision as sv
     from PIL import Image
@@ -199,7 +201,9 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
-    detections = sv.Detections.from_transformers(results)
+    detections = sv.Detections.from_transformers(
+        transformers_results=results, 
+        id2label=model.config.id2label)
 
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
@@ -274,7 +278,7 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
 
 === "Transformers"
 
-    ```{ .py hl_lines="24-28 33" }
+    ```{ .py hl_lines="26-30 35" }
     import torch
     import supervision as sv
     from PIL import Image
@@ -293,15 +297,17 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
-    detections = sv.Detections.from_transformers(results)
+    detections = sv.Detections.from_transformers(
+        transformers_results=results, 
+        id2label=model.config.id2label)
 
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
 
     labels = [
-        f"{model.config.id2label[class_id]} {confidence:.2f}"
-        for class_id, confidence
-        in zip(detections.class_id, detections.confidence)
+        f"{class_name} {confidence:.2f}"
+        for class_name, confidence
+        in zip(detections['class_name'], detections.confidence)
     ]
 
     annotated_image = bounding_box_annotator.annotate(
@@ -383,15 +389,17 @@ that will allow you to draw masks instead of boxes.
     target_size = torch.tensor([[height, width]])
     results = processor.post_process_segmentation(
         outputs=outputs, target_sizes=target_size)[0]
-    detections = sv.Detections.from_transformers(results)
+    detections = sv.Detections.from_transformers(
+        transformers_results=results, 
+        id2label=model.config.id2label)
 
     mask_annotator = sv.MaskAnnotator()
     label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
 
     labels = [
-        f"{model.config.id2label[class_id]} {confidence:.2f}"
-        for class_id, confidence
-        in zip(detections.class_id, detections.confidence)
+        f"{class_name} {confidence:.2f}"
+        for class_name, confidence
+        in zip(detections['class_name'], detections.confidence)
     ]
 
     annotated_image = mask_annotator.annotate(
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 554495ab1..016426b4f 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -189,7 +189,7 @@ def from_ultralytics(cls, ultralytics_results) -> Detections:
 
         Args:
             ultralytics_results (ultralytics.yolo.engine.results.Results):
-                The output Results instance from YOLOv8
+                The output Results instance from Ultralytics
 
         Returns:
             Detections: A new Detections object.
@@ -394,12 +394,19 @@ def from_transformers(
     ) -> Detections:
         """
         Creates a Detections instance from object detection or segmentation
-        [transformer](https://github.com/huggingface/transformers) inference result.
+        [Transformer](https://github.com/huggingface/transformers) inference result.
+        
+        !!! note
+
+            Class names can be accessed using the key `class_name` in the returned
+            object's data attribute.
 
         Args:
-            transformers_results (dict): A dictionary containing the scores, labels, and boxes for an image
-                as predicted by the Transformers model.
-            id2label (Optional[Dict[int, str]]): A dictionary mapping class IDs to class names. If None, class names will not be included.
+            transformers_results (dict): The output of Transformers model inference. A 
+                dictionary containing the `scores`, `labels`, `boxes` and `masks` keys.
+            id2label (Optional[Dict[int, str]]): A dictionary mapping class IDs to 
+                class names. If provided, the resulting Detections object will contain
+                `class_name` data field with the class names.
 
         Returns:
             Detections: A new Detections object.
@@ -424,7 +431,11 @@ def from_transformers(
             target_size = torch.tensor([[height, width]])
             results = processor.post_process_object_detection(
                 outputs=outputs, target_sizes=target_size)[0]
-            detections = sv.Detections.from_transformers(results)
+                
+            detections = sv.Detections.from_transformers(
+                transformers_results=results, 
+                id2label=model.config.id2label
+            )
             ```
         """  # noqa: E501 // docs
 
@@ -507,7 +518,7 @@ def from_inference(cls, roboflow_result: Union[dict, Any]) -> Detections:
 
         !!! note
 
-            Class names can be accessed using the key 'class_name' in the returned
+            Class names can be accessed using the key `class_name` in the returned
             object's data attribute.
 
         Args:

From dd7fddb4f5cbe0c181e7493e11a959416b9009a4 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 5 Apr 2024 09:49:58 +0000
Subject: [PATCH 099/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/detect_and_annotate.md |  8 ++++----
 supervision/detection/core.py      | 10 +++++-----
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index cdd13030a..0bec93efc 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -122,7 +122,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(
-        transformers_results=results, 
+        transformers_results=results,
         id2label=model.config.id2label)
     ```
 
@@ -202,7 +202,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(
-        transformers_results=results, 
+        transformers_results=results,
         id2label=model.config.id2label)
 
     bounding_box_annotator = sv.BoundingBoxAnnotator()
@@ -298,7 +298,7 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
     results = processor.post_process_object_detection(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(
-        transformers_results=results, 
+        transformers_results=results,
         id2label=model.config.id2label)
 
     bounding_box_annotator = sv.BoundingBoxAnnotator()
@@ -390,7 +390,7 @@ that will allow you to draw masks instead of boxes.
     results = processor.post_process_segmentation(
         outputs=outputs, target_sizes=target_size)[0]
     detections = sv.Detections.from_transformers(
-        transformers_results=results, 
+        transformers_results=results,
         id2label=model.config.id2label)
 
     mask_annotator = sv.MaskAnnotator()
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 016426b4f..0004dfd04 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -395,16 +395,16 @@ def from_transformers(
         """
         Creates a Detections instance from object detection or segmentation
         [Transformer](https://github.com/huggingface/transformers) inference result.
-        
+
         !!! note
 
             Class names can be accessed using the key `class_name` in the returned
             object's data attribute.
 
         Args:
-            transformers_results (dict): The output of Transformers model inference. A 
+            transformers_results (dict): The output of Transformers model inference. A
                 dictionary containing the `scores`, `labels`, `boxes` and `masks` keys.
-            id2label (Optional[Dict[int, str]]): A dictionary mapping class IDs to 
+            id2label (Optional[Dict[int, str]]): A dictionary mapping class IDs to
                 class names. If provided, the resulting Detections object will contain
                 `class_name` data field with the class names.
 
@@ -431,9 +431,9 @@ class names. If provided, the resulting Detections object will contain
             target_size = torch.tensor([[height, width]])
             results = processor.post_process_object_detection(
                 outputs=outputs, target_sizes=target_size)[0]
-                
+
             detections = sv.Detections.from_transformers(
-                transformers_results=results, 
+                transformers_results=results,
                 id2label=model.config.id2label
             )
             ```

From e2f1d5812ea1ce209dded7564b51f11b6053b1f1 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 5 Apr 2024 12:10:10 +0200
Subject: [PATCH 100/188] docs improvements

---
 docs/how_to/detect_and_annotate.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 0bec93efc..221d9ca1b 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -339,7 +339,7 @@ that will allow you to draw masks instead of boxes.
     detections = sv.Detections.from_inference(results)
 
     mask_annotator = sv.MaskAnnotator()
-    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER_OF_MASS)
 
     annotated_image = mask_annotator.annotate(
         scene=image, detections=detections)
@@ -360,7 +360,7 @@ that will allow you to draw masks instead of boxes.
     detections = sv.Detections.from_ultralytics(results)
 
     mask_annotator = sv.MaskAnnotator()
-    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER_OF_MASS)
 
     annotated_image = mask_annotator.annotate(
         scene=image, detections=detections)
@@ -394,7 +394,7 @@ that will allow you to draw masks instead of boxes.
         id2label=model.config.id2label)
 
     mask_annotator = sv.MaskAnnotator()
-    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+    label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER_OF_MASS)
 
     labels = [
         f"{class_name} {confidence:.2f}"

From c9095881ae4f4808a56339e4c208ac5f96705ac3 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 5 Apr 2024 17:33:52 +0200
Subject: [PATCH 101/188] docs updates

---
 docs/utils/image.md        |  6 +++++
 supervision/draw/color.py  | 46 ++++++++++++++++++++++++++++++++++++--
 supervision/utils/image.py | 18 +++++++--------
 3 files changed, 59 insertions(+), 11 deletions(-)

diff --git a/docs/utils/image.md b/docs/utils/image.md
index 8a6768d74..087aebd73 100644
--- a/docs/utils/image.md
+++ b/docs/utils/image.md
@@ -17,6 +17,12 @@ status: new
 
 :::supervision.utils.image.crop_image
 
+<div class="md-typeset">
+  <h2>letterbox_image</h2>
+</div>
+
+:::supervision.utils.image.letterbox_image
+
 <div class="md-typeset">
   <h2>resize_image</h2>
 </div>
diff --git a/supervision/draw/color.py b/supervision/draw/color.py
index 825b0da5e..debb46f3b 100644
--- a/supervision/draw/color.py
+++ b/supervision/draw/color.py
@@ -104,10 +104,13 @@ def from_hex(cls, color_hex: str) -> Color:
         Create a Color instance from a hex string.
 
         Args:
-            color_hex (str): Hex string of the color.
+            color_hex (str): The hex string representing the color. This string can
+                start with '#' followed by either 3 or 6 hexadecimal characters. In
+                case of 3 characters, each character is repeated to form the full
+                6-character hex code.
 
         Returns:
-            Color: Instance representing the color.
+            Color: An instance representing the color.
 
         Example:
             ```python
@@ -115,6 +118,9 @@ def from_hex(cls, color_hex: str) -> Color:
 
             sv.Color.from_hex('#ff00ff')
             # Color(r=255, g=0, b=255)
+
+            sv.Color.from_hex('#f0f')
+            # Color(r=255, g=0, b=255)
             ```
         """
         _validate_color_hex(color_hex)
@@ -126,11 +132,47 @@ def from_hex(cls, color_hex: str) -> Color:
 
     @classmethod
     def from_rgb_tuple(cls, color_tuple: Tuple[int, int, int]) -> Color:
+        """
+        Create a Color instance from an RGB tuple.
+
+        Args:
+            color_tuple (Tuple[int, int, int]): A tuple representing the color in RGB
+                format, where each element is an integer in the range 0-255.
+
+        Returns:
+            Color: An instance representing the color.
+
+        Example:
+            ```python
+            import supervision as sv
+
+            sv.Color.from_rgb_tuple((255, 255, 0))
+            # Color(r=255, g=255, b=0)
+            ```
+        """
         r, g, b = color_tuple
         return cls(r=r, g=g, b=b)
 
     @classmethod
     def from_bgr_tuple(cls, color_tuple: Tuple[int, int, int]) -> Color:
+        """
+        Create a Color instance from a BGR tuple.
+
+        Args:
+            color_tuple (Tuple[int, int, int]): A tuple representing the color in BGR
+                format, where each element is an integer in the range 0-255.
+
+        Returns:
+            Color: An instance representing the color.
+
+        Example:
+            ```python
+            import supervision as sv
+
+            sv.Color.from_bgr_tuple((0, 255, 255))
+            # Color(r=255, g=255, b=0)
+            ```
+        """
         b, g, r = color_tuple
         return cls(r=r, g=g, b=b)
 
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index c1c6b1cfa..305359325 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -79,8 +79,8 @@ def resize_image(image: np.ndarray, scale_factor: float) -> np.ndarray:
 
     Args:
         image (np.ndarray): The input image to be resized.
-        scale_factor (float): The factor by which the image will be scaled. Scale factor
-            > 1.0 zooms in, < 1.0 zooms out.
+        scale_factor (float): The factor by which the image will be scaled. Scale
+            factor > 1.0 zooms in, < 1.0 zooms out.
 
     Returns:
         np.ndarray: The resized image.
@@ -571,13 +571,13 @@ def letterbox_image(
     Resize and pad image to fit the desired size, preserving its aspect
     ratio, adding padding of given color if needed to maintain aspect ratio.
 
-    Parameters:
-    - image (np.ndarray): Input image (type will be adjusted by decorator,
-        you can provide PIL.Image)
-    - desired_size (Tuple[int, int]): image size (width, height) representing
-        the target dimensions.
-    - color (Union[Tuple[int, int, int], Color]): the color to pad with - If
-        tuple provided - should be BGR.
+    Args:
+        image (np.ndarray): Input image (type will be adjusted by decorator,
+            you can provide PIL.Image)
+        desired_size (Tuple[int, int]): image size (width, height) representing
+            the target dimensions.
+        color (Union[Tuple[int, int, int], Color]): the color to pad with - If
+            tuple provided - should be BGR.
 
     Returns:
         np.ndarray: letterboxed image (type may be adjusted to PIL.Image by

From b76f864f70d533578067c32c46171147105c6b01 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20P=C4=99czek?= <pawel@roboflow.com>
Date: Fri, 5 Apr 2024 17:45:49 +0200
Subject: [PATCH 102/188] Rename decorators to convert images to acceptable
 format

---
 supervision/annotators/core.py    | 46 ++++++++---------
 supervision/annotators/utils.py   | 26 ----------
 supervision/detection/annotate.py |  4 +-
 supervision/utils/conversion.py   | 44 ++++++++++++++++
 supervision/utils/image.py        | 38 ++++----------
 test/utils/test_conversion.py     | 83 ++++++++++++++++++++++++++++++-
 test/utils/test_image.py          | 77 ----------------------------
 7 files changed, 159 insertions(+), 159 deletions(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 2be2562ee..bdf7e9b2f 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -5,18 +5,14 @@
 import numpy as np
 
 from supervision.annotators.base import BaseAnnotator, ImageType
-from supervision.annotators.utils import (
-    ColorLookup,
-    Trace,
-    resolve_color,
-    scene_to_annotator_img_type,
-)
+from supervision.annotators.utils import ColorLookup, Trace, resolve_color
 from supervision.config import CLASS_NAME_DATA_FIELD, ORIENTED_BOX_COORDINATES
 from supervision.detection.core import Detections
 from supervision.detection.utils import clip_boxes, mask_to_polygons
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import draw_polygon
 from supervision.geometry.core import Position
+from supervision.utils.conversion import convert_for_annotation_method
 from supervision.utils.image import crop_image, place_image, resize_image
 
 
@@ -43,7 +39,7 @@ def __init__(
         self.thickness: int = thickness
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -124,7 +120,7 @@ def __init__(
         self.thickness: int = thickness
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -212,7 +208,7 @@ def __init__(
         self.opacity = opacity
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -299,7 +295,7 @@ def __init__(
         self.thickness: int = thickness
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -385,7 +381,7 @@ def __init__(
         self.color_lookup: ColorLookup = color_lookup
         self.opacity = opacity
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -479,7 +475,7 @@ def __init__(
         self.color_lookup: ColorLookup = color_lookup
         self.kernel_size: int = kernel_size
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -577,7 +573,7 @@ def __init__(
         self.end_angle: int = end_angle
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -668,7 +664,7 @@ def __init__(
         self.corner_length: int = corner_length
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -756,7 +752,7 @@ def __init__(
         self.thickness: int = thickness
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -846,7 +842,7 @@ def __init__(
         self.position: Position = position
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -989,7 +985,7 @@ def resolve_text_background_xyxy(
                 center_y + text_h // 2,
             )
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1112,7 +1108,7 @@ def __init__(self, kernel_size: int = 15):
         """
         self.kernel_size: int = kernel_size
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1197,7 +1193,7 @@ def __init__(
         self.thickness = thickness
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1304,7 +1300,7 @@ def __init__(
         self.top_hue = top_hue
         self.low_hue = low_hue
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(self, scene: ImageType, detections: Detections) -> ImageType:
         """
         Annotates the scene with a heatmap based on the provided detections.
@@ -1380,7 +1376,7 @@ def __init__(self, pixel_size: int = 20):
         """
         self.pixel_size: int = pixel_size
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1468,7 +1464,7 @@ def __init__(
         self.position: Position = position
         self.color_lookup: ColorLookup = color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1564,7 +1560,7 @@ def __init__(
             raise ValueError("roundness attribute must be float between (0, 1.0]")
         self.roundness: float = roundness
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1701,7 +1697,7 @@ def __init__(
         if border_thickness is None:
             self.border_thickness = int(0.15 * self.height)
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
@@ -1874,7 +1870,7 @@ def __init__(
         self.border_thickness: int = border_thickness
         self.border_color_lookup: ColorLookup = border_color_lookup
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
diff --git a/supervision/annotators/utils.py b/supervision/annotators/utils.py
index 385380ee8..e206c8cbb 100644
--- a/supervision/annotators/utils.py
+++ b/supervision/annotators/utils.py
@@ -1,15 +1,11 @@
 from enum import Enum
-from functools import wraps
 from typing import Optional, Union
 
 import numpy as np
-from PIL import Image
 
-from supervision.annotators.base import ImageType
 from supervision.detection.core import Detections
 from supervision.draw.color import Color, ColorPalette
 from supervision.geometry.core import Position
-from supervision.utils.conversion import cv2_to_pillow, pillow_to_cv2
 
 
 class ColorLookup(Enum):
@@ -123,25 +119,3 @@ def put(self, detections: Detections) -> None:
 
     def get(self, tracker_id: int) -> np.ndarray:
         return self.xy[self.tracker_id == tracker_id]
-
-
-def scene_to_annotator_img_type(annotate_func):
-    """
-    Decorates `BaseAnnotator.annotate` implementations, converts scene to
-    an image type used internally by the annotators, converts back when annotation
-    is complete.
-    """
-
-    @wraps(annotate_func)
-    def wrapper(self, scene: ImageType, *args, **kwargs):
-        if isinstance(scene, np.ndarray):
-            return annotate_func(self, scene, *args, **kwargs)
-
-        if isinstance(scene, Image.Image):
-            scene = pillow_to_cv2(scene)
-            annotated = annotate_func(self, scene, *args, **kwargs)
-            return cv2_to_pillow(image=annotated)
-
-        raise ValueError(f"Unsupported image type: {type(scene)}")
-
-    return wrapper
diff --git a/supervision/detection/annotate.py b/supervision/detection/annotate.py
index a8df0a573..f32c73440 100644
--- a/supervision/detection/annotate.py
+++ b/supervision/detection/annotate.py
@@ -3,9 +3,9 @@
 import cv2
 
 from supervision.annotators.base import ImageType
-from supervision.annotators.utils import scene_to_annotator_img_type
 from supervision.detection.core import Detections
 from supervision.draw.color import Color, ColorPalette
+from supervision.utils.conversion import convert_for_annotation_method
 from supervision.utils.internal import deprecated
 
 
@@ -46,7 +46,7 @@ def __init__(
         self.text_thickness: int = text_thickness
         self.text_padding: int = text_padding
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(
         self,
         scene: ImageType,
diff --git a/supervision/utils/conversion.py b/supervision/utils/conversion.py
index 6e7b03c3d..608104bcd 100644
--- a/supervision/utils/conversion.py
+++ b/supervision/utils/conversion.py
@@ -1,3 +1,4 @@
+from functools import wraps
 from typing import List
 
 import cv2
@@ -7,6 +8,49 @@
 from supervision.annotators.base import ImageType
 
 
+def convert_for_annotation_method(annotate_func):
+    """
+    Decorates `BaseAnnotator.annotate` implementations, converts scene to
+    an image type used internally by the annotators, converts back when annotation
+    is complete.
+    """
+
+    @wraps(annotate_func)
+    def wrapper(self, scene: ImageType, *args, **kwargs):
+        if isinstance(scene, np.ndarray):
+            return annotate_func(self, scene, *args, **kwargs)
+
+        if isinstance(scene, Image.Image):
+            scene = pillow_to_cv2(scene)
+            annotated = annotate_func(self, scene, *args, **kwargs)
+            return cv2_to_pillow(image=annotated)
+
+        raise ValueError(f"Unsupported image type: {type(scene)}")
+
+    return wrapper
+
+
+def convert_for_image_processing(image_processing_fun):
+    """
+    Decorates image processing functions that accept np.ndarray, converting `image` to
+    np.ndarray, converts back when processing is complete.
+    """
+
+    @wraps(image_processing_fun)
+    def wrapper(image: ImageType, *args, **kwargs):
+        if isinstance(image, np.ndarray):
+            return image_processing_fun(image, *args, **kwargs)
+
+        if isinstance(image, Image.Image):
+            scene = pillow_to_cv2(image)
+            annotated = image_processing_fun(scene, *args, **kwargs)
+            return cv2_to_pillow(image=annotated)
+
+        raise ValueError(f"Unsupported image type: {type(image)}")
+
+    return wrapper
+
+
 def images_to_cv2(images: List[ImageType]) -> List[np.ndarray]:
     """
     Converts images provided either as Pillow images or OpenCV
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 305359325..d79da8d6f 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -2,18 +2,21 @@
 import math
 import os
 import shutil
-from functools import partial, wraps
+from functools import partial
 from typing import Callable, List, Literal, Optional, Tuple, Union
 
 import cv2
 import numpy as np
-from PIL import Image
 
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color
 from supervision.draw.utils import calculate_optimal_text_scale, draw_text
 from supervision.geometry.core import Point
-from supervision.utils.conversion import cv2_to_pillow, images_to_cv2, pillow_to_cv2
+from supervision.utils.conversion import (
+    convert_for_image_processing,
+    cv2_to_pillow,
+    images_to_cv2,
+)
 from supervision.utils.iterables import create_batches, fill
 
 RelativePosition = Literal["top", "bottom"]
@@ -21,28 +24,7 @@
 MAX_COLUMNS_FOR_SINGLE_ROW_GRID = 3
 
 
-def adjust_image_to_cv2_processing(image_processing_fun):
-    """
-    Decorates image processing functions that accept np.ndarray, converting `image` to
-    np.ndarray, converts back when processing is complete.
-    """
-
-    @wraps(image_processing_fun)
-    def wrapper(image: ImageType, *args, **kwargs):
-        if isinstance(image, np.ndarray):
-            return image_processing_fun(image, *args, **kwargs)
-
-        if isinstance(image, Image.Image):
-            scene = pillow_to_cv2(image)
-            annotated = image_processing_fun(scene, *args, **kwargs)
-            return cv2_to_pillow(image=annotated)
-
-        raise ValueError(f"Unsupported image type: {type(image)}")
-
-    return wrapper
-
-
-@adjust_image_to_cv2_processing
+@convert_for_image_processing
 def crop_image(image: np.ndarray, xyxy: np.ndarray) -> np.ndarray:
     """
     Crops the given image based on the given bounding box.
@@ -72,7 +54,7 @@ def crop_image(image: np.ndarray, xyxy: np.ndarray) -> np.ndarray:
     return image[y1:y2, x1:x2]
 
 
-@adjust_image_to_cv2_processing
+@convert_for_image_processing
 def resize_image(image: np.ndarray, scale_factor: float) -> np.ndarray:
     """
     Resizes an image by a given scale factor using cv2.INTER_LINEAR interpolation.
@@ -561,7 +543,7 @@ def _generate_color_image(
     return np.ones(shape[::-1] + (3,), dtype=np.uint8) * color
 
 
-@adjust_image_to_cv2_processing
+@convert_for_image_processing
 def letterbox_image(
     image: np.ndarray,
     desired_size: Tuple[int, int],
@@ -604,7 +586,7 @@ def letterbox_image(
     )
 
 
-@adjust_image_to_cv2_processing
+@convert_for_image_processing
 def resize_image_keeping_aspect_ratio(
     image: np.ndarray,
     desired_size: Tuple[int, int],
diff --git a/test/utils/test_conversion.py b/test/utils/test_conversion.py
index 0ce46db0d..fb3d8faff 100644
--- a/test/utils/test_conversion.py
+++ b/test/utils/test_conversion.py
@@ -1,7 +1,88 @@
 import numpy as np
 from PIL import Image, ImageChops
 
-from supervision.utils.conversion import cv2_to_pillow, images_to_cv2, pillow_to_cv2
+from supervision.utils.conversion import (
+    convert_for_image_processing,
+    cv2_to_pillow,
+    images_to_cv2,
+    pillow_to_cv2,
+)
+
+
+def test_convert_for_image_processing_when_pillow_image_submitted(
+    empty_opencv_image: np.ndarray, empty_pillow_image: Image.Image
+) -> None:
+    # given
+    param_a_value = 3
+    param_b_value = "some"
+
+    @convert_for_image_processing
+    def my_custom_processing_function(
+        image: np.ndarray,
+        param_a: int,
+        param_b: str,
+    ) -> np.ndarray:
+        assert np.allclose(
+            image, empty_opencv_image
+        ), "Expected conversion to OpenCV image to happen"
+        assert (
+            param_a == param_a_value
+        ), f"Parameter a expected to be {param_a_value} in target function"
+        assert (
+            param_b == param_b_value
+        ), f"Parameter b expected to be {param_b_value} in target function"
+        return image
+
+    # when
+    result = my_custom_processing_function(
+        empty_pillow_image,
+        param_a_value,
+        param_b=param_b_value,
+    )
+
+    # then
+    difference = ImageChops.difference(result, empty_pillow_image)
+    assert difference.getbbox() is None, (
+        "Wrapper is expected to convert-back the OpenCV image "
+        "into Pillow format without changes to content"
+    )
+
+
+def test_convert_for_image_processing_when_opencv_image_submitted(
+    empty_opencv_image: np.ndarray,
+) -> None:
+    # given
+    param_a_value = 3
+    param_b_value = "some"
+
+    @convert_for_image_processing
+    def my_custom_processing_function(
+        image: np.ndarray,
+        param_a: int,
+        param_b: str,
+    ) -> np.ndarray:
+        assert np.allclose(
+            image, empty_opencv_image
+        ), "Expected conversion to OpenCV image to happen"
+        assert (
+            param_a == param_a_value
+        ), f"Parameter a expected to be {param_a_value} in target function"
+        assert (
+            param_b == param_b_value
+        ), f"Parameter b expected to be {param_b_value} in target function"
+        return image
+
+    # when
+    result = my_custom_processing_function(
+        empty_opencv_image,
+        param_a_value,
+        param_b=param_b_value,
+    )
+
+    # then
+    assert (
+        result is empty_opencv_image
+    ), "Expected to return OpenCV image without changes"
 
 
 def test_cv2_to_pillow(
diff --git a/test/utils/test_image.py b/test/utils/test_image.py
index 66bb6689a..e50f2e574 100644
--- a/test/utils/test_image.py
+++ b/test/utils/test_image.py
@@ -6,89 +6,12 @@
 
 from supervision import Color, Point
 from supervision.utils.image import (
-    adjust_image_to_cv2_processing,
     create_tiles,
     letterbox_image,
     resize_image_keeping_aspect_ratio,
 )
 
 
-def test_adjust_image_to_cv2_processing_when_pillow_image_submitted(
-    empty_opencv_image: np.ndarray, empty_pillow_image: Image.Image
-) -> None:
-    # given
-    param_a_value = 3
-    param_b_value = "some"
-
-    @adjust_image_to_cv2_processing
-    def my_custom_processing_function(
-        image: np.ndarray,
-        param_a: int,
-        param_b: str,
-    ) -> np.ndarray:
-        assert np.allclose(
-            image, empty_opencv_image
-        ), "Expected conversion to OpenCV image to happen"
-        assert (
-            param_a == param_a_value
-        ), f"Parameter a expected to be {param_a_value} in target function"
-        assert (
-            param_b == param_b_value
-        ), f"Parameter b expected to be {param_b_value} in target function"
-        return image
-
-    # when
-    result = my_custom_processing_function(
-        empty_pillow_image,
-        param_a_value,
-        param_b=param_b_value,
-    )
-
-    # then
-    difference = ImageChops.difference(result, empty_pillow_image)
-    assert difference.getbbox() is None, (
-        "Wrapper is expected to convert-back the OpenCV image "
-        "into Pillow format without changes to content"
-    )
-
-
-def test_adjust_image_to_cv2_processing_when_opencv_image_submitted(
-    empty_opencv_image: np.ndarray,
-) -> None:
-    # given
-    param_a_value = 3
-    param_b_value = "some"
-
-    @adjust_image_to_cv2_processing
-    def my_custom_processing_function(
-        image: np.ndarray,
-        param_a: int,
-        param_b: str,
-    ) -> np.ndarray:
-        assert np.allclose(
-            image, empty_opencv_image
-        ), "Expected conversion to OpenCV image to happen"
-        assert (
-            param_a == param_a_value
-        ), f"Parameter a expected to be {param_a_value} in target function"
-        assert (
-            param_b == param_b_value
-        ), f"Parameter b expected to be {param_b_value} in target function"
-        return image
-
-    # when
-    result = my_custom_processing_function(
-        empty_opencv_image,
-        param_a_value,
-        param_b=param_b_value,
-    )
-
-    # then
-    assert (
-        result is empty_opencv_image
-    ), "Expected to return OpenCV image without changes"
-
-
 def test_resize_image_keeping_aspect_ratio_for_opencv_image() -> None:
     # given
     image = np.zeros((480, 640, 3), dtype=np.uint8)

From 5e9c3fdfa51220bcb9ac829e47d097b12a173716 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 5 Apr 2024 17:51:08 +0200
Subject: [PATCH 103/188] refactor tests to use `@pytest.mark.parametrize`

---
 test/utils/test_iterables.py | 151 +++++++++--------------------------
 1 file changed, 37 insertions(+), 114 deletions(-)

diff --git a/test/utils/test_iterables.py b/test/utils/test_iterables.py
index 313b2baf1..4868f1839 100644
--- a/test/utils/test_iterables.py
+++ b/test/utils/test_iterables.py
@@ -1,127 +1,50 @@
+import pytest
 from supervision.utils.iterables import create_batches, fill
 
 
-def test_create_batches_when_empty_sequence_given() -> None:
-    # when
-    result = list(create_batches(sequence=[], batch_size=4))
+@pytest.mark.parametrize(
+    "sequence, batch_size, expected",
+    [
+        # Empty sequence, non-zero batch size. Expect empty list.
+        ([], 4, []),
 
-    # then
-    assert result == [], "Expected empty generator"
+        # Non-zero size sequence, batch size of 0. Each item is its own batch.
+        ([1, 2, 3], 0, [[1], [2], [3]]),
 
+        # Batch size larger than sequence. All items in a single batch.
+        ([1, 2], 4, [[1, 2]]),
 
-def test_create_batches_when_not_allowed_batch_size_given() -> None:
-    # when
-    result = list(create_batches(sequence=[1, 2, 3], batch_size=0))
+        # Batch size evenly divides the sequence. Equal size batches.
+        ([1, 2, 3, 4], 2, [[1, 2], [3, 4]]),
 
-    # then
-    assert result == [[1], [2], [3]], (
-        "Expected min_batch_size to be established and each element of input "
-        "list provided in separate batch"
-    )
+        # Batch size doesn't evenly divide sequence. Last batch smaller.
+        ([1, 2, 3, 4], 3, [[1, 2, 3], [4]]),
+    ],
+)
+def test_create_batches(sequence, batch_size, expected) -> None:
+    result = list(create_batches(sequence=sequence, batch_size=batch_size))
+    assert result == expected
 
 
-def test_create_batches_when_batch_size_larger_than_sequence() -> None:
-    # when
-    result = list(create_batches(sequence=[1, 2], batch_size=4))
+@pytest.mark.parametrize(
+    "sequence, desired_size, content, expected",
+    [
+        # Empty sequence, desired size 0. Expect empty list.
+        ([], 0, 1, []),
 
-    # then
-    assert result == [[1, 2]], (
-        "Expected whole content to be returned in single batch as input sequence "
-        "is smaller than batch size"
-    )
+        # Empty sequence, non-zero desired size. Filled with padding.
+        ([], 3, 1, [1, 1, 1]),
 
+        # Sequence at desired size. No changes.
+        ([2, 2, 2], 3, 1, [2, 2, 2]),
 
-def test_create_batches_when_batch_size_multiplier_fits_sequence_length() -> None:
-    # when
-    result = list(create_batches(sequence=[1, 2, 3, 4], batch_size=2))
+        # Sequence exceeds desired size. No changes.
+        ([2, 2, 2, 2], 3, 1, [2, 2, 2, 2]),
 
-    # then
-    assert result == [[1, 2], [3, 4]], (
-        "Expected input sequence to be returned in two chunks as batch size "
-        "is half of sequence length"
-    )
-
-
-def test_create_batches_when_batch_size_multiplier_does_not_fir_sequence_length() -> (
-    None
-):
-    # when
-    result = list(create_batches(sequence=[1, 2, 3, 4], batch_size=3))
-
-    # then
-    assert result == [[1, 2, 3], [4]], (
-        "Expected first batch to be of size 3 and last one to be not "
-        "full, with only one element"
-    )
-
-
-def test_fill_when_empty_sequence_given_and_padding_not_needed() -> None:
-    # given
-    sequence = []
-
-    # when
-    result = fill(sequence=sequence, desired_size=0, content=1)
-
-    # then
-    assert result == [], "Expected no elements to be added into sequence"
-
-
-def test_fill_when_empty_sequence_given_and_padding_needed() -> None:
-    # given
-    sequence = []
-
-    # when
-    result = fill(sequence=sequence, desired_size=3, content=1)
-
-    # then
-    assert result == [1, 1, 1], "Expected three padding element to be added"
-
-
-def test_fill_when_non_empty_sequence_given_and_sequence_equal_to_desired_size() -> (
-    None
-):
-    # given
-    sequence = [2, 2, 2]
-
-    # when
-    result = fill(sequence=sequence, desired_size=3, content=1)
-
-    # then
-    assert result == [
-        2,
-        2,
-        2,
-    ], "Expected nothing to be added to sequence, as it is already " "in desired size"
-
-
-def test_fill_when_non_empty_sequence_given_and_sequence_longer_then_desired_size() -> (
-    None
-):
-    # given
-    sequence = [2, 2, 2, 2]
-
-    # when
-    result = fill(sequence=sequence, desired_size=3, content=1)
-
-    # then
-    assert result == [
-        2,
-        2,
-        2,
-        2,
-    ], "Expected nothing to be added to sequence, as it already " "exceeds desired size"
-
-
-def test_fill_when_non_empty_sequence_given_and_padding_needed() -> None:
-    # given
-    sequence = [2]
-
-    # when
-    result = fill(sequence=sequence, desired_size=3, content=1)
-
-    # then
-    assert result == [
-        2,
-        1,
-        1,
-    ], "Expected 2 padding elements to be added to fit desired size"
+        # Non-empty sequence, shorter than desired. Padding added.
+        ([2], 3, 1, [2, 1, 1]),
+    ],
+)
+def test_fill(sequence, desired_size, content, expected) -> None:
+    result = fill(sequence=sequence, desired_size=desired_size, content=content)
+    assert result == expected

From e93224570f48885ae15c3dbcb9699204d738abd5 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 5 Apr 2024 15:51:32 +0000
Subject: [PATCH 104/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 test/utils/test_iterables.py | 9 +--------
 1 file changed, 1 insertion(+), 8 deletions(-)

diff --git a/test/utils/test_iterables.py b/test/utils/test_iterables.py
index 4868f1839..2d34605c0 100644
--- a/test/utils/test_iterables.py
+++ b/test/utils/test_iterables.py
@@ -1,4 +1,5 @@
 import pytest
+
 from supervision.utils.iterables import create_batches, fill
 
 
@@ -7,16 +8,12 @@
     [
         # Empty sequence, non-zero batch size. Expect empty list.
         ([], 4, []),
-
         # Non-zero size sequence, batch size of 0. Each item is its own batch.
         ([1, 2, 3], 0, [[1], [2], [3]]),
-
         # Batch size larger than sequence. All items in a single batch.
         ([1, 2], 4, [[1, 2]]),
-
         # Batch size evenly divides the sequence. Equal size batches.
         ([1, 2, 3, 4], 2, [[1, 2], [3, 4]]),
-
         # Batch size doesn't evenly divide sequence. Last batch smaller.
         ([1, 2, 3, 4], 3, [[1, 2, 3], [4]]),
     ],
@@ -31,16 +28,12 @@ def test_create_batches(sequence, batch_size, expected) -> None:
     [
         # Empty sequence, desired size 0. Expect empty list.
         ([], 0, 1, []),
-
         # Empty sequence, non-zero desired size. Filled with padding.
         ([], 3, 1, [1, 1, 1]),
-
         # Sequence at desired size. No changes.
         ([2, 2, 2], 3, 1, [2, 2, 2]),
-
         # Sequence exceeds desired size. No changes.
         ([2, 2, 2, 2], 3, 1, [2, 2, 2, 2]),
-
         # Non-empty sequence, shorter than desired. Padding added.
         ([2], 3, 1, [2, 1, 1]),
     ],

From 473f14013337c2e9ae2c6c9566842bee97283e90 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 5 Apr 2024 18:01:17 +0200
Subject: [PATCH 105/188] `create_batches` and `fill` docs added

---
 docs/utils/iterables.md        | 18 +++++++++
 mkdocs.yml                     |  1 +
 supervision/utils/iterables.py | 70 ++++++++++++++++++++--------------
 3 files changed, 60 insertions(+), 29 deletions(-)
 create mode 100644 docs/utils/iterables.md

diff --git a/docs/utils/iterables.md b/docs/utils/iterables.md
new file mode 100644
index 000000000..cde710f15
--- /dev/null
+++ b/docs/utils/iterables.md
@@ -0,0 +1,18 @@
+---
+comments: true
+status: new
+---
+
+# Iterables Utils
+
+<div class="md-typeset">
+  <h2>create_batches</h2>
+</div>
+
+:::supervision.utils.iterables.create_batches
+
+<div class="md-typeset">
+  <h2>fill</h2>
+</div>
+
+:::supervision.utils.iterables.fill
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
index 5444290b9..2afadfa55 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -65,6 +65,7 @@ nav:
     - Utils:
         - Video: utils/video.md
         - Image: utils/image.md
+        - Iterables: utils/iterables.md
         - Notebook: utils/notebook.md
         - File: utils/file.md
     - Assets: assets.md
diff --git a/supervision/utils/iterables.py b/supervision/utils/iterables.py
index 529ceadb1..70b658b06 100644
--- a/supervision/utils/iterables.py
+++ b/supervision/utils/iterables.py
@@ -1,25 +1,33 @@
 from typing import Generator, Iterable, List, TypeVar
 
-SequenceElement = TypeVar("SequenceElement")
+V = TypeVar("V")
 
 
 def create_batches(
-    sequence: Iterable[SequenceElement], batch_size: int
-) -> Generator[List[SequenceElement], None, None]:
+        sequence: Iterable[V], batch_size: int
+) -> Generator[List[V], None, None]:
     """
-    Provides a generator that yields chunks of input sequence
-    of size specified by `batch_size` parameter. Last
-    chunk may be smaller batch.
+    Provides a generator that yields chunks of the input sequence
+    of the size specified by the `batch_size` parameter. The last
+    chunk may be a smaller batch.
 
     Args:
-        sequence (Iterable[SequenceElement]): Sequence to be
-            split into batches.
-        batch_size (int): Expected size of a batch
+        sequence (Iterable[V]): The sequence to be split into batches.
+        batch_size (int): The expected size of a batch.
 
     Returns:
-        Generator[List[SequenceElement], None, None]: Generator
-            to yield chinks of `sequence` of size `batch_size`,
-            up to the length of input `sequence`.
+        Generator[List[V], None, None]: A generator that yields chunks
+            of `sequence` of size `batch_size`, up to the length of
+            the input `sequence`.
+
+    Examples:
+        ```python
+        list(create_batches([1, 2, 3, 4, 5], 2))
+        # [[1, 2], [3, 4], [5]]
+
+        list(create_batches("abcde", 3))
+        # [['a', 'b', 'c'], ['d', 'e']]
+        ```
     """
     batch_size = max(batch_size, 1)
     current_batch = []
@@ -28,31 +36,35 @@ def create_batches(
             yield current_batch
             current_batch = []
         current_batch.append(element)
-    if len(current_batch) > 0:
+    if current_batch:
         yield current_batch
 
 
-def fill(
-    sequence: List[SequenceElement],
-    desired_size: int,
-    content: SequenceElement,
-) -> List[SequenceElement]:
+def fill(sequence: List[V], desired_size: int, content: V) -> List[V]:
     """
-    Fill the sequence with padding elements until sequence reaches
-    desired size.
+    Fill the sequence with padding elements until the sequence reaches
+    the desired size.
 
     Args:
-        sequence (List[SequenceElement]): Input sequence.
-        desired_size (int): Expected size of output list - difference
-            between this value and actual `sequence` length (if positive)
-            dictates how many elements will be added as padding.
-        content (SequenceElement): Element to be placed at the end of
-            input `sequence` as padding.
+        sequence (List[V]): The input sequence.
+        desired_size (int): The expected size of the output list. The
+            difference between this value and the actual length of `sequence`
+            (if positive) dictates how many elements will be added as padding.
+        content (V): The element to be placed at the end of the input
+            `sequence` as padding.
 
     Returns:
-        List[SequenceElement]: Padded version of input `sequence` (if needed)
+        List[V]: A padded version of the input `sequence` (if needed).
+
+    Examples:
+        ```python
+        fill([1, 2], 4, 0)
+        # [1, 2, 0, 0]
+
+        fill(['a', 'b'], 3, 'c')
+        # ['a', 'b', 'c']
+        ```
     """
     missing_size = max(0, desired_size - len(sequence))
-    required_padding = [content] * missing_size
-    sequence.extend(required_padding)
+    sequence.extend([content] * missing_size)
     return sequence

From 0a919db9fd7fe4019daa9f7cc7ea9b98d749f0bd Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 5 Apr 2024 16:02:55 +0000
Subject: [PATCH 106/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/utils/iterables.md        | 2 +-
 supervision/utils/iterables.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/utils/iterables.md b/docs/utils/iterables.md
index cde710f15..3ccf98e59 100644
--- a/docs/utils/iterables.md
+++ b/docs/utils/iterables.md
@@ -15,4 +15,4 @@ status: new
   <h2>fill</h2>
 </div>
 
-:::supervision.utils.iterables.fill
\ No newline at end of file
+:::supervision.utils.iterables.fill
diff --git a/supervision/utils/iterables.py b/supervision/utils/iterables.py
index 70b658b06..ad570379c 100644
--- a/supervision/utils/iterables.py
+++ b/supervision/utils/iterables.py
@@ -4,7 +4,7 @@
 
 
 def create_batches(
-        sequence: Iterable[V], batch_size: int
+    sequence: Iterable[V], batch_size: int
 ) -> Generator[List[V], None, None]:
     """
     Provides a generator that yields chunks of the input sequence

From 0ae2c1206f9efe683a760a2b04b778ab654d66b5 Mon Sep 17 00:00:00 2001
From: Jonas Pirner <48887249+pirnerjonas@users.noreply.github.com>
Date: Sat, 6 Apr 2024 21:40:19 +0200
Subject: [PATCH 107/188] fix: formatting in notebook.md

---
 docs/utils/notebook.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/utils/notebook.md b/docs/utils/notebook.md
index d58bbcfcd..d09b9bbd8 100644
--- a/docs/utils/notebook.md
+++ b/docs/utils/notebook.md
@@ -11,7 +11,7 @@ comments: true
 :::supervision.utils.notebook.plot_image
 
 <div class="md-typeset">
-  <h2>## plot_images_grid
+  <h2>plot_images_grid
 </h2>
 </div>
 

From b5ccc99537075e34485cd35e468746e5d5cb0661 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 8 Apr 2024 01:11:06 +0000
Subject: [PATCH 108/188] :arrow_up: Bump mkdocstrings from 0.24.2 to 0.24.3

Bumps [mkdocstrings](https://github.com/mkdocstrings/mkdocstrings) from 0.24.2 to 0.24.3.
- [Release notes](https://github.com/mkdocstrings/mkdocstrings/releases)
- [Changelog](https://github.com/mkdocstrings/mkdocstrings/blob/main/CHANGELOG.md)
- [Commits](https://github.com/mkdocstrings/mkdocstrings/compare/0.24.2...0.24.3)

---
updated-dependencies:
- dependency-name: mkdocstrings
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 5fa0fbb25..65a9122fe 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2226,13 +2226,13 @@ files = [
 
 [[package]]
 name = "mkdocstrings"
-version = "0.24.2"
+version = "0.24.3"
 description = "Automatic documentation from sources, for MkDocs."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocstrings-0.24.2-py3-none-any.whl", hash = "sha256:61440b77542170238099a7d87882c3417897771950e3aafe6e22abff3d1c51fb"},
-    {file = "mkdocstrings-0.24.2.tar.gz", hash = "sha256:b91b9cdd9490ef2e8957000bff1d34a4b308b9cd57b10f26169f085def4c6a92"},
+    {file = "mkdocstrings-0.24.3-py3-none-any.whl", hash = "sha256:5c9cf2a32958cd161d5428699b79c8b0988856b0d4a8c5baf8395fc1bf4087c3"},
+    {file = "mkdocstrings-0.24.3.tar.gz", hash = "sha256:f327b234eb8d2551a306735436e157d0a22d45f79963c60a8b585d5f7a94c1d2"},
 ]
 
 [package.dependencies]

From 6b682f00ae473807d1a07cdda31d3dae89ea35c2 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 8 Apr 2024 17:55:20 +0000
Subject: [PATCH 109/188] =?UTF-8?q?chore(pre=5Fcommit):=20=E2=AC=86=20pre?=
 =?UTF-8?q?=5Fcommit=20autoupdate?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/pre-commit/pre-commit-hooks: v4.5.0 → v4.6.0](https://github.com/pre-commit/pre-commit-hooks/compare/v4.5.0...v4.6.0)
- [github.com/astral-sh/ruff-pre-commit: v0.3.4 → v0.3.5](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.4...v0.3.5)
---
 .pre-commit-config.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index f0515b9e4..4c2b1a7ed 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -7,7 +7,7 @@ ci:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v4.6.0
     hooks:
       - id: end-of-file-fixer
       - id: trailing-whitespace
@@ -45,7 +45,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.3.4
+      rev: v0.3.5
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

From 574c61b6b00bb80f90b6826b404b843b3c1f6bf4 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 14:28:40 +0200
Subject: [PATCH 110/188] initial commit

---
 docs/how_to/detect_and_annotate.md |   2 +-
 docs/how_to/save_detections.md     | 124 +++++++++++++++++++++++++++++
 mkdocs.yml                         |   4 +-
 supervision/draw/color.py          |  18 ++++-
 supervision/utils/image.py         |  51 ++++++------
 test/utils/test_image.py           |   4 +-
 6 files changed, 170 insertions(+), 33 deletions(-)
 create mode 100644 docs/how_to/save_detections.md

diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index 221d9ca1b..adea95cf7 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -15,7 +15,7 @@ source image.
 
 ![basic-annotation](https://media.roboflow.com/supervision_detect_and_annotate_example_1.png)
 
-## Run Inference
+## Run Detection
 
 First, you'll need to obtain predictions from your object detection or segmentation
 model.
diff --git a/docs/how_to/save_detections.md b/docs/how_to/save_detections.md
new file mode 100644
index 000000000..622c504f5
--- /dev/null
+++ b/docs/how_to/save_detections.md
@@ -0,0 +1,124 @@
+---
+comments: true
+status: new
+---
+
+# Save Detections
+
+TODO
+
+## Run Detection
+
+=== "Inference"
+
+    ```python
+    import cv2
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    results = model.infer(image)[0]
+    ```
+
+=== "Ultralytics"
+
+    ```python
+    import cv2
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8n.pt")
+    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    results = model(image)[0]
+    ```
+
+=== "Transformers"
+
+    ```python
+    import torch
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<SOURCE_IMAGE_APTH>)
+    inputs = processor(images=image, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    ```
+
+## Save Detections as CSV
+
+TODO
+
+=== "Inference"
+
+    ```python
+    import supervision as sv
+    from inference import get_model
+    
+    model = get_model(model_id="yolov8n-640")
+    
+    with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
+        for frame in sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>):
+    
+            results = model.infer(image)[0]
+            detections = sv.Detections.from_inference(results)
+            sink.append(detections, {})
+    ```
+
+=== "Ultralytics"
+
+    ```python
+    import supervision as sv
+    from ultralytics import YOLO
+    
+    model = YOLO("yolov8n.pt")
+    
+    with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
+        for frame in sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>):
+    
+            results = model(frame)[0]
+            detections = sv.Detections.from_ultralytics(results)
+            sink.append(detections, {})
+    ```
+
+=== "Transformers"
+
+    ```python
+    import torch
+    from PIL import Image
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+    image = Image.open(<SOURCE_IMAGE_APTH>)
+    inputs = processor(images=image, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    width, height = image.size
+    target_size = torch.tensor([[height, width]])
+    results = processor.post_process_object_detection(
+        outputs=outputs, target_sizes=target_size)[0]
+    ```
+
+## Custom Fields
+
+TODO
+
+## Save Detections as JSON
+
+TODO
+
+## Process Video and Save Detections
+
+TODO
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
index 8bae5d765..dd6feb8db 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -38,9 +38,11 @@ nav:
   - Home: index.md
   - How to:
       - Detect and Annotate: how_to/detect_and_annotate.md
+      - Save Detections: how_to/save_detections.md
+      - Filter Detections: how_to/filter_detections.md
       - Detect Small Objects: how_to/detect_small_objects.md
       - Track Objects: how_to/track_objects.md
-      - Filter Detections: how_to/filter_detections.md
+
   - API:
     - Annotators: annotators.md
     - Classifications:
diff --git a/supervision/draw/color.py b/supervision/draw/color.py
index debb46f3b..b195cffe7 100644
--- a/supervision/draw/color.py
+++ b/supervision/draw/color.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
-from typing import List, Tuple
+from typing import List, Tuple, Union
 
 import matplotlib.pyplot as plt
 
@@ -448,3 +448,19 @@ def by_idx(self, idx: int) -> Color:
             raise ValueError("idx argument should not be negative")
         idx = idx % len(self.colors)
         return self.colors[idx]
+
+
+def unify_to_bgr(color: Union[Tuple[int, int, int], Color]) -> Tuple[int, int, int]:
+    """
+    Converts a color input in multiple formats to a standardized BGR format.
+
+    Args:
+        color (Union[Tuple[int, int, int], Color]): The color input to be converted,
+            which can be either a tuple of RGB values or an instance of a Color class.
+
+    Returns:
+        Tuple[int, int, int]: The color in BGR format as a tuple of three integers.
+    """
+    if issubclass(type(color), Color):
+        return color.as_bgr()
+    return color
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 4e0ba5d76..64fb6de10 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -9,7 +9,7 @@
 import numpy as np
 
 from supervision.annotators.base import ImageType
-from supervision.draw.color import Color
+from supervision.draw.color import Color, unify_to_bgr
 from supervision.draw.utils import calculate_optimal_text_scale, draw_text
 from supervision.geometry.core import Point
 from supervision.utils.conversion import (
@@ -25,17 +25,18 @@
 
 
 @convert_for_image_processing
-def crop_image(image: np.ndarray, xyxy: np.ndarray) -> np.ndarray:
+def crop_image(image: ImageType, xyxy: np.ndarray) -> np.ndarray:
     """
     Crops the given image based on the given bounding box.
 
     Args:
-        image (np.ndarray): The image to be cropped, represented as a numpy array.
+        image (ImageType): The image to be cropped. `ImageType` is a flexible type,
+            accepting either `numpy.ndarray` or `PIL.Image.Image`.
         xyxy (np.ndarray): A numpy array containing the bounding box coordinates
             in the format (x1, y1, x2, y2).
 
     Returns:
-        (np.ndarray): The cropped image as a numpy array.
+        (ImageType): The cropped image.
 
     Examples:
         ```python
@@ -74,10 +75,10 @@ def resize_image(image: np.ndarray, scale_factor: float) -> np.ndarray:
         raise ValueError("Scale factor must be positive.")
 
     old_width, old_height = image.shape[1], image.shape[0]
-    nwe_width = int(old_width * scale_factor)
+    new_width = int(old_width * scale_factor)
     new_height = int(old_height * scale_factor)
 
-    return cv2.resize(image, (nwe_width, new_height), interpolation=cv2.INTER_LINEAR)
+    return cv2.resize(image, (new_width, new_height), interpolation=cv2.INTER_LINEAR)
 
 
 def place_image(
@@ -285,14 +286,14 @@ def create_tiles(
         raise ValueError("Could not create image tiles from empty list of images.")
     if return_type == "auto":
         return_type = _negotiate_tiles_format(images=images)
-    tile_padding_color = _color_to_bgr(color=tile_padding_color)
-    tile_margin_color = _color_to_bgr(color=tile_margin_color)
+    tile_padding_color = unify_to_bgr(color=tile_padding_color)
+    tile_margin_color = unify_to_bgr(color=tile_margin_color)
     images = images_to_cv2(images=images)
     if single_tile_size is None:
         single_tile_size = _aggregate_images_shape(images=images, mode=tile_scaling)
     resized_images = [
         letterbox_image(
-            image=i, desired_size=single_tile_size, color=tile_padding_color
+            image=i, target_resolution_wh=single_tile_size, color=tile_padding_color
         )
         for i in images
     ]
@@ -311,8 +312,8 @@ def create_tiles(
     titles_anchors = fill(
         sequence=titles_anchors, desired_size=len(images), content=None
     )
-    titles_color = _color_to_bgr(color=titles_color)
-    titles_background_color = _color_to_bgr(color=titles_background_color)
+    titles_color = unify_to_bgr(color=titles_color)
+    titles_background_color = unify_to_bgr(color=titles_background_color)
     tiles = _generate_tiles(
         images=resized_images,
         grid_size=grid_size,
@@ -546,8 +547,8 @@ def _generate_color_image(
 
 @convert_for_image_processing
 def letterbox_image(
-    image: np.ndarray,
-    desired_size: Tuple[int, int],
+    image: ImageType,
+    target_resolution_wh: Tuple[int, int],
     color: Union[Tuple[int, int, int], Color] = (0, 0, 0),
 ) -> np.ndarray:
     """
@@ -555,27 +556,27 @@ def letterbox_image(
     ratio, adding padding of given color if needed to maintain aspect ratio.
 
     Args:
-        image (np.ndarray): Input image (type will be adjusted by decorator,
+        image (ImageType): Input image (type will be adjusted by decorator,
             you can provide PIL.Image)
-        desired_size (Tuple[int, int]): image size (width, height) representing
+        target_resolution_wh (Tuple[int, int]): image size (width, height) representing
             the target dimensions.
         color (Union[Tuple[int, int, int], Color]): the color to pad with - If
             tuple provided - should be BGR.
 
     Returns:
-        np.ndarray: letterboxed image (type may be adjusted to PIL.Image by
+        ImageType: letterboxed image (type may be adjusted to PIL.Image by
             decorator if function was called with PIL.Image)
     """
-    color = _color_to_bgr(color=color)
+    color = unify_to_bgr(color=color)
     resized_img = resize_image_keeping_aspect_ratio(
         image=image,
-        desired_size=desired_size,
+        desired_size=target_resolution_wh,
     )
     new_height, new_width = resized_img.shape[:2]
-    top_padding = (desired_size[1] - new_height) // 2
-    bottom_padding = desired_size[1] - new_height - top_padding
-    left_padding = (desired_size[0] - new_width) // 2
-    right_padding = desired_size[0] - new_width - left_padding
+    top_padding = (target_resolution_wh[1] - new_height) // 2
+    bottom_padding = target_resolution_wh[1] - new_height - top_padding
+    left_padding = (target_resolution_wh[0] - new_width) // 2
+    right_padding = target_resolution_wh[0] - new_width - left_padding
     return cv2.copyMakeBorder(
         resized_img,
         top_padding,
@@ -625,9 +626,3 @@ def resize_image_keeping_aspect_ratio(
         new_height = desired_size[1]
         new_width = int(desired_size[1] * img_ratio)
     return cv2.resize(image, (new_width, new_height))
-
-
-def _color_to_bgr(color: Union[Tuple[int, int, int], Color]) -> Tuple[int, int, int]:
-    if issubclass(type(color), Color):
-        return color.as_bgr()
-    return color
diff --git a/test/utils/test_image.py b/test/utils/test_image.py
index e50f2e574..50b6b5c1b 100644
--- a/test/utils/test_image.py
+++ b/test/utils/test_image.py
@@ -62,7 +62,7 @@ def test_letterbox_image_for_opencv_image() -> None:
 
     # when
     result = letterbox_image(
-        image=image, desired_size=(1024, 1024), color=(255, 255, 255)
+        image=image, target_resolution_wh=(1024, 1024), color=(255, 255, 255)
     )
 
     # then
@@ -88,7 +88,7 @@ def test_letterbox_image_for_pillow_image() -> None:
 
     # when
     result = letterbox_image(
-        image=image, desired_size=(1024, 1024), color=(255, 255, 255)
+        image=image, target_resolution_wh=(1024, 1024), color=(255, 255, 255)
     )
 
     # then

From 5b1ee8f870c1c9e091fb84167fbf060ebc9c0cac Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 12:31:30 +0000
Subject: [PATCH 111/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/save_detections.md | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/docs/how_to/save_detections.md b/docs/how_to/save_detections.md
index 622c504f5..81de930ec 100644
--- a/docs/how_to/save_detections.md
+++ b/docs/how_to/save_detections.md
@@ -62,12 +62,12 @@ TODO
     ```python
     import supervision as sv
     from inference import get_model
-    
+
     model = get_model(model_id="yolov8n-640")
-    
+
     with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
         for frame in sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>):
-    
+
             results = model.infer(image)[0]
             detections = sv.Detections.from_inference(results)
             sink.append(detections, {})
@@ -78,12 +78,12 @@ TODO
     ```python
     import supervision as sv
     from ultralytics import YOLO
-    
+
     model = YOLO("yolov8n.pt")
-    
+
     with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
         for frame in sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>):
-    
+
             results = model(frame)[0]
             detections = sv.Detections.from_ultralytics(results)
             sink.append(detections, {})
@@ -121,4 +121,4 @@ TODO
 
 ## Process Video and Save Detections
 
-TODO
\ No newline at end of file
+TODO

From 2115c9a1526dfc8d2d5de5f74651ac48f3f2c585 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 14:50:32 +0200
Subject: [PATCH 112/188] crop_image improvements

---
 supervision/utils/image.py | 16 +++++++++++-----
 1 file changed, 11 insertions(+), 5 deletions(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 64fb6de10..a6466eaa7 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -25,15 +25,19 @@
 
 
 @convert_for_image_processing
-def crop_image(image: ImageType, xyxy: np.ndarray) -> np.ndarray:
+def crop_image(
+    image: ImageType,
+    xyxy: Union[np.ndarray, List[int], Tuple[int, int, int, int]]
+) -> ImageType:
     """
     Crops the given image based on the given bounding box.
 
     Args:
         image (ImageType): The image to be cropped. `ImageType` is a flexible type,
             accepting either `numpy.ndarray` or `PIL.Image.Image`.
-        xyxy (np.ndarray): A numpy array containing the bounding box coordinates
-            in the format (x1, y1, x2, y2).
+        xyxy (Union[np.ndarray, List[int], Tuple[int, int, int, int]]): A bounding box
+            coordinates in the format (x_min, y_min, x_max, y_max), accepted as either
+            a numpy array, a list, or a tuple.
 
     Returns:
         (ImageType): The cropped image.
@@ -50,9 +54,11 @@ def crop_image(image: ImageType, xyxy: np.ndarray) -> np.ndarray:
         ```
     """
 
+    if isinstance(xyxy, (list, tuple)):
+        xyxy = np.array(xyxy)
     xyxy = np.round(xyxy).astype(int)
-    x1, y1, x2, y2 = xyxy
-    return image[y1:y2, x1:x2]
+    x_min, y_min, x_max, y_max = xyxy.flatten()
+    return image[y_min:y_max, x_min:x_max]
 
 
 @convert_for_image_processing

From f2e6d882fbb64f326e179cdd24f5837715982ac8 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 12:50:48 +0000
Subject: [PATCH 113/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/utils/image.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index a6466eaa7..954533a2c 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -26,8 +26,7 @@
 
 @convert_for_image_processing
 def crop_image(
-    image: ImageType,
-    xyxy: Union[np.ndarray, List[int], Tuple[int, int, int, int]]
+    image: ImageType, xyxy: Union[np.ndarray, List[int], Tuple[int, int, int, int]]
 ) -> ImageType:
     """
     Crops the given image based on the given bounding box.

From 7d0cf8a7233aa81b204e57d72de57b59b3e1f994 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Tue, 9 Apr 2024 15:44:53 +0300
Subject: [PATCH 114/188] =?UTF-8?q?feat:=20=F0=9F=9A=80=20initial=20sv.Key?=
 =?UTF-8?q?points=20features=20added?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 supervision/__init__.py            |   1 +
 supervision/detection/core.py      |   2 +-
 supervision/detection/utils.py     |  98 +-----------------
 supervision/keypoints/__init__.py  |   0
 supervision/keypoints/core.py      | 160 +++++++++++++++++++++++++++++
 supervision/keypoints/utils.py     |   0
 supervision/validators/__init__.py | 141 +++++++++++++++++++++++++
 7 files changed, 304 insertions(+), 98 deletions(-)
 create mode 100644 supervision/keypoints/__init__.py
 create mode 100644 supervision/keypoints/core.py
 create mode 100644 supervision/keypoints/utils.py
 create mode 100644 supervision/validators/__init__.py

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 35f525b04..df04534dd 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -69,6 +69,7 @@
 )
 from supervision.geometry.core import Point, Position, Rect
 from supervision.geometry.utils import get_polygon_center
+from supervision.keypoints.core import KeyPoints
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
 from supervision.utils.file import list_files_with_extensions
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 8c29cfc48..bb8775ade 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -17,11 +17,11 @@
     mask_to_xyxy,
     merge_data,
     process_roboflow_result,
-    validate_detections_fields,
     xywh_to_xyxy,
 )
 from supervision.geometry.core import Position
 from supervision.utils.internal import deprecated
+from supervision.validators import validate_detections_fields
 
 
 @dataclass
diff --git a/supervision/detection/utils.py b/supervision/detection/utils.py
index b3928fdb5..3eeba5b44 100644
--- a/supervision/detection/utils.py
+++ b/supervision/detection/utils.py
@@ -1,5 +1,5 @@
 from itertools import chain
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Dict, List, Optional, Tuple, Union
 
 import cv2
 import numpy as np
@@ -656,102 +656,6 @@ def sum_over_mask(indices: np.ndarray, axis: tuple) -> np.ndarray:
     return np.column_stack((centroid_x, centroid_y)).astype(int)
 
 
-def validate_xyxy(xyxy: Any) -> None:
-    expected_shape = "(_, 4)"
-    actual_shape = str(getattr(xyxy, "shape", None))
-    is_valid = isinstance(xyxy, np.ndarray) and xyxy.ndim == 2 and xyxy.shape[1] == 4
-    if not is_valid:
-        raise ValueError(
-            f"xyxy must be a 2D np.ndarray with shape {expected_shape}, but got shape "
-            f"{actual_shape}"
-        )
-
-
-def validate_mask(mask: Any, n: int) -> None:
-    expected_shape = f"({n}, H, W)"
-    actual_shape = str(getattr(mask, "shape", None))
-    is_valid = mask is None or (
-        isinstance(mask, np.ndarray) and len(mask.shape) == 3 and mask.shape[0] == n
-    )
-    if not is_valid:
-        raise ValueError(
-            f"mask must be a 3D np.ndarray with shape {expected_shape}, but got shape "
-            f"{actual_shape}"
-        )
-
-
-def validate_class_id(class_id: Any, n: int) -> None:
-    expected_shape = f"({n},)"
-    actual_shape = str(getattr(class_id, "shape", None))
-    is_valid = class_id is None or (
-        isinstance(class_id, np.ndarray) and class_id.shape == (n,)
-    )
-    if not is_valid:
-        raise ValueError(
-            f"class_id must be a 1D np.ndarray with shape {expected_shape}, but got "
-            f"shape {actual_shape}"
-        )
-
-
-def validate_confidence(confidence: Any, n: int) -> None:
-    expected_shape = f"({n},)"
-    actual_shape = str(getattr(confidence, "shape", None))
-    is_valid = confidence is None or (
-        isinstance(confidence, np.ndarray) and confidence.shape == (n,)
-    )
-    if not is_valid:
-        raise ValueError(
-            f"confidence must be a 1D np.ndarray with shape {expected_shape}, but got "
-            f"shape {actual_shape}"
-        )
-
-
-def validate_tracker_id(tracker_id: Any, n: int) -> None:
-    expected_shape = f"({n},)"
-    actual_shape = str(getattr(tracker_id, "shape", None))
-    is_valid = tracker_id is None or (
-        isinstance(tracker_id, np.ndarray) and tracker_id.shape == (n,)
-    )
-    if not is_valid:
-        raise ValueError(
-            f"tracker_id must be a 1D np.ndarray with shape {expected_shape}, but got "
-            f"shape {actual_shape}"
-        )
-
-
-def validate_data(data: Dict[str, Any], n: int) -> None:
-    for key, value in data.items():
-        if isinstance(value, list):
-            if len(value) != n:
-                raise ValueError(f"Length of list for key '{key}' must be {n}")
-        elif isinstance(value, np.ndarray):
-            if value.ndim == 1 and value.shape[0] != n:
-                raise ValueError(f"Shape of np.ndarray for key '{key}' must be ({n},)")
-            elif value.ndim > 1 and value.shape[0] != n:
-                raise ValueError(
-                    f"First dimension of np.ndarray for key '{key}' must have size {n}"
-                )
-        else:
-            raise ValueError(f"Value for key '{key}' must be a list or np.ndarray")
-
-
-def validate_detections_fields(
-    xyxy: Any,
-    mask: Any,
-    class_id: Any,
-    confidence: Any,
-    tracker_id: Any,
-    data: Dict[str, Any],
-) -> None:
-    validate_xyxy(xyxy)
-    n = len(xyxy)
-    validate_mask(mask, n)
-    validate_class_id(class_id, n)
-    validate_confidence(confidence, n)
-    validate_tracker_id(tracker_id, n)
-    validate_data(data, n)
-
-
 def is_data_equal(data_a: Dict[str, np.ndarray], data_b: Dict[str, np.ndarray]) -> bool:
     """
     Compares the data payloads of two Detections instances.
diff --git a/supervision/keypoints/__init__.py b/supervision/keypoints/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/supervision/keypoints/core.py b/supervision/keypoints/core.py
new file mode 100644
index 000000000..bf2ab8869
--- /dev/null
+++ b/supervision/keypoints/core.py
@@ -0,0 +1,160 @@
+from dataclasses import dataclass, field
+from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
+
+import numpy as np
+import numpy.typing as npt
+
+from supervision.config import CLASS_NAME_DATA_FIELD
+from supervision.detection.utils import get_data_item, is_data_equal
+from supervision.validators import validate_keypoints_fields
+
+
+@dataclass
+class KeyPoints:
+    """
+    The `sv.KeyPoints` allows you to convert results from a variety of keypoint
+    detections models into a single, unified format.
+
+    ```python
+    import cv2
+    import supervision as sv
+    from ultralytics import YOLO
+
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
+    model = YOLO('yolov8s-pose.pt')
+    result = model(image)[0]
+    keypoints = sv.KeyPoints.from_ultralytics(result)
+    ```
+
+    !!! tip
+
+        In `sv.KeyPoints`, detection data is categorized into two main field types:
+        fixed and custom. The fixed fields include `xy`, `confidence`,
+        `class_id`. For any additional data requirements, custom
+        fields come into play, stored in the data field. These custom fields are easily
+        accessible using the `detections[<FIELD_NAME>]` syntax, providing flexibility
+        for diverse data handling needs.
+
+    Attributes:
+        xy (np.ndarray): An array of shape `(n, 2)` containing
+            the bounding boxes coordinates in format `[x1, y1]`
+        confidence (Optional[np.ndarray]): An array of shape
+            `(n,)` containing the confidence scores of the keypoint detections.
+        class_id (Optional[np.ndarray]): An array of shape
+            `(n,)` containing the class ids of the keypoint detections.
+        data (Dict[str, Union[np.ndarray, List]]): A dictionary containing additional
+            data where each key is a string representing the data type, and the value
+            is either a NumPy array or a list of corresponding data.
+
+    !!! warning
+
+        The `data` field in the `sv.KeyPoints` class is currently in an experimental
+        phase. Please be aware that its API and functionality are subject to change in
+        future updates as we continue to refine and improve its capabilities.
+        We encourage users to experiment with this feature and provide feedback, but
+        also to be prepared for potential modifications in upcoming releases.
+    """
+
+    xy: npt.NDArray[np.float32]
+    class_id: Optional[npt.NDArray[np.int_]] = None
+    confidence: Optional[npt.NDArray[np.float32]] = None
+    data: Dict[str, Union[npt.NDArray[Any], List]] = field(default_factory=dict)
+
+    def __post_init__(self):
+        validate_keypoints_fields(
+            xy=self.xy,
+            confidence=self.confidence,
+            class_id=self.class_id,
+            data=self.data,
+        )
+
+    def __len__(self) -> int:
+        """
+        Returns the number of keypoints in the keypoints object.
+        """
+        return len(self.xy)
+
+    def __iter__(
+        self,
+    ) -> Iterator[
+        Tuple[
+            np.ndarray,
+            Optional[np.ndarray],
+            Optional[float],
+            Optional[int],
+            Optional[int],
+            Dict[str, Union[np.ndarray, List]],
+        ]
+    ]:
+        """
+        Iterates over the Keypoint object and yield a tuple of
+        `(xy, confidence, class_id, data)` for each keypoint detection.
+        """
+        for i in range(len(self.xy)):
+            yield (
+                self.xy[i],
+                self.confidence[i] if self.confidence is not None else None,
+                self.class_id[i] if self.class_id is not None else None,
+                get_data_item(self.data, i),
+            )
+
+    def __eq__(self, other: "KeyPoints") -> bool:
+        return all(
+            [
+                np.array_equal(self.xy, other.xy),
+                np.array_equal(self.class_id, other.class_id),
+                np.array_equal(self.confidence, other.confidence),
+                is_data_equal(self.data, other.data),
+            ]
+        )
+
+    @classmethod
+    def from_ultralytics(cls, ultralytics_results) -> "KeyPoints":
+        """
+        Creates a Keypoints instance from a
+            [YOLOv8](https://github.com/ultralytics/ultralytics) inference result.
+
+        Args:
+            ultralytics_results (ultralytics.engine.results.Keypoints):
+                The output Results instance from YOLOv8
+
+        Returns:
+            KeyPoints: A new Keypoints object.
+
+        Example:
+            ```python
+            import cv2
+            import supervision as sv
+            from ultralytics import YOLO
+
+            image = cv2.imread(<SOURCE_IMAGE_PATH>)
+            model = YOLO('yolov8s-pose.pt')
+            result = model(image)[0]
+            keypoints = sv.KeyPoints.from_ultralytics(result)
+            ```
+        """  #
+
+        class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
+        class_names = np.array([ultralytics_results.names[i] for i in class_id])
+
+        xy = ultralytics_results.keypoints.xy.cpu().numpy()
+        confidence = ultralytics_results.keypoints.conf.cpu().numpy()
+        class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
+        data = {CLASS_NAME_DATA_FIELD: class_names}
+        return cls(xy, class_id, confidence, data)
+
+    @classmethod
+    def empty(cls) -> "KeyPoints":
+        """
+        Create an empty Keypoints object with no keypoints.
+
+        Returns:
+            (Keypoints): An empty Keypoints object.
+
+        Example:
+            ```python
+            from supervision import Keypoints
+            empty_keypoints = Keypoints.empty()
+            ```
+        """
+        return cls(xy=np.empty((0, 0, 2), dtype=np.float32))
diff --git a/supervision/keypoints/utils.py b/supervision/keypoints/utils.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/supervision/validators/__init__.py b/supervision/validators/__init__.py
new file mode 100644
index 000000000..9a9fca8ca
--- /dev/null
+++ b/supervision/validators/__init__.py
@@ -0,0 +1,141 @@
+from typing import Any, Dict
+
+import numpy as np
+
+
+def validate_xyxy(xyxy: Any) -> None:
+    expected_shape = "(_, 4)"
+    actual_shape = str(getattr(xyxy, "shape", None))
+    is_valid = isinstance(xyxy, np.ndarray) and xyxy.ndim == 2 and xyxy.shape[1] == 4
+    if not is_valid:
+        raise ValueError(
+            f"xyxy must be a 2D np.ndarray with shape {expected_shape}, but got shape "
+            f"{actual_shape}"
+        )
+
+
+def validate_mask(mask: Any, n: int) -> None:
+    expected_shape = f"({n}, H, W)"
+    actual_shape = str(getattr(mask, "shape", None))
+    is_valid = mask is None or (
+        isinstance(mask, np.ndarray) and len(mask.shape) == 3 and mask.shape[0] == n
+    )
+    if not is_valid:
+        raise ValueError(
+            f"mask must be a 3D np.ndarray with shape {expected_shape}, but got shape "
+            f"{actual_shape}"
+        )
+
+
+def validate_class_id(class_id: Any, n: int) -> None:
+    expected_shape = f"({n},)"
+    actual_shape = str(getattr(class_id, "shape", None))
+    is_valid = class_id is None or (
+        isinstance(class_id, np.ndarray) and class_id.shape == (n,)
+    )
+    if not is_valid:
+        raise ValueError(
+            f"class_id must be a 1D np.ndarray with shape {expected_shape}, but got "
+            f"shape {actual_shape}"
+        )
+
+
+def validate_confidence(confidence: Any, n: int) -> None:
+    expected_shape = f"({n},)"
+    actual_shape = str(getattr(confidence, "shape", None))
+    is_valid = confidence is None or (
+        isinstance(confidence, np.ndarray) and confidence.shape == (n,)
+    )
+    if not is_valid:
+        raise ValueError(
+            f"confidence must be a 1D np.ndarray with shape {expected_shape}, but got "
+            f"shape {actual_shape}"
+        )
+
+
+def validate_keypoint_confidence(confidence: Any, n: int, m: int) -> None:
+    expected_shape = f"({n,m})"
+    actual_shape = str(getattr(confidence, "shape", None))
+
+    if confidence is not None:
+        is_valid = isinstance(confidence, np.ndarray) and confidence.shape == (n, m)
+        if not is_valid:
+            raise ValueError(
+                f"confidence must be a 1D np.ndarray with shape {expected_shape}, but "
+                "got"
+                f"shape {actual_shape}"
+            )
+
+
+def validate_tracker_id(tracker_id: Any, n: int) -> None:
+    expected_shape = f"({n},)"
+    actual_shape = str(getattr(tracker_id, "shape", None))
+    is_valid = tracker_id is None or (
+        isinstance(tracker_id, np.ndarray) and tracker_id.shape == (n,)
+    )
+    if not is_valid:
+        raise ValueError(
+            f"tracker_id must be a 1D np.ndarray with shape {expected_shape}, but got "
+            f"shape {actual_shape}"
+        )
+
+
+def validate_data(data: Dict[str, Any], n: int) -> None:
+    for key, value in data.items():
+        if isinstance(value, list):
+            if len(value) != n:
+                raise ValueError(f"Length of list for key '{key}' must be {n}")
+        elif isinstance(value, np.ndarray):
+            if value.ndim == 1 and value.shape[0] != n:
+                raise ValueError(f"Shape of np.ndarray for key '{key}' must be ({n},)")
+            elif value.ndim > 1 and value.shape[0] != n:
+                raise ValueError(
+                    f"First dimension of np.ndarray for key '{key}' must have size {n}"
+                )
+        else:
+            raise ValueError(f"Value for key '{key}' must be a list or np.ndarray")
+
+
+def validate_xy(xy: Any, n: int, m: int) -> None:
+    expected_shape = f"({n, m},)"
+    actual_shape = str(getattr(xy, "shape", None))
+
+    is_valid = isinstance(xy, np.ndarray) and (
+        xy.shape == (n, m, 2) or xy.shape == (n, m, 3)
+    )
+    if not is_valid:
+        raise ValueError(
+            f"xy must be a 2D np.ndarray with shape {expected_shape}, but got shape "
+            f"{actual_shape}"
+        )
+
+
+def validate_detections_fields(
+    xyxy: Any,
+    mask: Any,
+    class_id: Any,
+    confidence: Any,
+    tracker_id: Any,
+    data: Dict[str, Any],
+) -> None:
+    validate_xyxy(xyxy)
+    n = len(xyxy)
+    validate_mask(mask, n)
+    validate_class_id(class_id, n)
+    validate_confidence(confidence, n)
+    validate_tracker_id(tracker_id, n)
+    validate_data(data, n)
+
+
+def validate_keypoints_fields(
+    xy: Any,
+    class_id: Any,
+    confidence: Any,
+    data: Dict[str, Any],
+) -> None:
+    n = len(xy)
+    m = len(xy[0]) if len(xy) > 0 else 0
+    validate_xy(xy, n, m)
+    validate_class_id(class_id, n)
+    validate_keypoint_confidence(confidence, n, m)
+    validate_data(data, n)

From 5d43e1380d248d2c8db5a3352feea855199d01f6 Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Tue, 9 Apr 2024 17:42:31 +0300
Subject: [PATCH 115/188] =?UTF-8?q?feat(test):=20=F0=9F=9A=80=20mock=20key?=
 =?UTF-8?q?points=20added?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 test/test_utils.py | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/test/test_utils.py b/test/test_utils.py
index b8ef92316..d36248450 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -3,6 +3,7 @@
 import numpy as np
 
 from supervision.detection.core import Detections
+from supervision.keypoints.core import KeyPoints
 
 
 def mock_detections(
@@ -30,5 +31,24 @@ def convert_data(data: Dict[str, List[Any]]):
     )
 
 
+def mock_keypoints(
+    xy: List[List[float]],
+    confidence: Optional[List[float]] = None,
+    class_id: Optional[List[int]] = None,
+    data: Optional[Dict[str, List[Any]]] = None,
+) -> KeyPoints:
+    def convert_data(data: Dict[str, List[Any]]):
+        return {k: np.array(v) for k, v in data.items()}
+
+    return KeyPoints(
+        xy=np.array(xy, dtype=np.float32),
+        confidence=(
+            confidence if confidence is None else np.array(confidence, dtype=np.float32)
+        ),
+        class_id=(class_id if class_id is None else np.array(class_id, dtype=int)),
+        data=convert_data(data) if data else {},
+    )
+
+
 def assert_almost_equal(actual, expected, tolerance=1e-5):
     assert abs(actual - expected) < tolerance, f"Expected {expected}, but got {actual}."

From b63379749e9862846307fcbea99be3d4b7b3b68b Mon Sep 17 00:00:00 2001
From: Onuralp SEZER <thunderbirdtr@gmail.com>
Date: Tue, 9 Apr 2024 17:43:19 +0300
Subject: [PATCH 116/188] =?UTF-8?q?fix(keypoint):=20=F0=9F=9A=80=20getitem?=
 =?UTF-8?q?=20and=20setitem=20funcs=20added?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com>
---
 supervision/keypoints/core.py | 88 +++++++++++++++++++++++++++++++++--
 1 file changed, 84 insertions(+), 4 deletions(-)

diff --git a/supervision/keypoints/core.py b/supervision/keypoints/core.py
index bf2ab8869..646b99db7 100644
--- a/supervision/keypoints/core.py
+++ b/supervision/keypoints/core.py
@@ -13,7 +13,7 @@
 class KeyPoints:
     """
     The `sv.KeyPoints` allows you to convert results from a variety of keypoint
-    detections models into a single, unified format.
+    keypoints models into a single, unified format.
 
     ```python
     import cv2
@@ -32,16 +32,16 @@ class KeyPoints:
         fixed and custom. The fixed fields include `xy`, `confidence`,
         `class_id`. For any additional data requirements, custom
         fields come into play, stored in the data field. These custom fields are easily
-        accessible using the `detections[<FIELD_NAME>]` syntax, providing flexibility
+        accessible using the `keypoints[<FIELD_NAME>]` syntax, providing flexibility
         for diverse data handling needs.
 
     Attributes:
         xy (np.ndarray): An array of shape `(n, 2)` containing
             the bounding boxes coordinates in format `[x1, y1]`
         confidence (Optional[np.ndarray]): An array of shape
-            `(n,)` containing the confidence scores of the keypoint detections.
+            `(n,)` containing the confidence scores of the keypoint keypoints.
         class_id (Optional[np.ndarray]): An array of shape
-            `(n,)` containing the class ids of the keypoint detections.
+            `(n,)` containing the class ids of the keypoint keypoints.
         data (Dict[str, Union[np.ndarray, List]]): A dictionary containing additional
             data where each key is a string representing the data type, and the value
             is either a NumPy array or a list of corresponding data.
@@ -143,6 +143,86 @@ def from_ultralytics(cls, ultralytics_results) -> "KeyPoints":
         data = {CLASS_NAME_DATA_FIELD: class_names}
         return cls(xy, class_id, confidence, data)
 
+    def __getitem__(
+        self, index: Union[int, slice, List[int], np.ndarray, str]
+    ) -> Union["KeyPoints", List, np.ndarray, None]:
+        """
+        Get a subset of the KeyPoints object or access an item from its data field.
+
+        When provided with an integer, slice, list of integers, or a numpy array, this
+        method returns a new KeyPoints object that represents a subset of the original
+        keypoints. When provided with a string, it accesses the corresponding item in
+        the data dictionary.
+
+        Args:
+            index (Union[int, slice, List[int], np.ndarray, str]): The index, indices,
+                or key to access a subset of the KeyPoints or an item from the data.
+
+        Returns:
+            Union[KeyPoints, Any]: A subset of the KeyPoints object or an item from
+                the data field.
+
+        Example:
+            ```python
+            import supervision as sv
+
+            keypoints = sv.KeyPoints()
+
+            first_detection = keypoints[0]
+            first_10_keypoints = keypoints[0:10]
+            some_keypoints = keypoints[[0, 2, 4]]
+            class_0_keypoints = keypoints[keypoints.class_id == 0]
+            high_confidence_keypoints = keypoints[keypoints.confidence > 0.5]
+
+            feature_vector = keypoints['feature_vector']
+            ```
+        """
+        if isinstance(index, str):
+            return self.data.get(index)
+        if isinstance(index, int):
+            index = [index]
+        return KeyPoints(
+            xy=self.xy[index],
+            confidence=self.confidence[index] if self.confidence is not None else None,
+            class_id=self.class_id[index] if self.class_id is not None else None,
+            data=get_data_item(self.data, index),
+        )
+
+    def __setitem__(self, key: str, value: Union[np.ndarray, List]):
+        """
+        Set a value in the data dictionary of the KeyPoints object.
+
+        Args:
+            key (str): The key in the data dictionary to set.
+            value (Union[np.ndarray, List]): The value to set for the key.
+
+        Example:
+            ```python
+            import cv2
+            import supervision as sv
+            from ultralytics import YOLO
+
+            image = cv2.imread(<SOURCE_IMAGE_PATH>)
+            model = YOLO('yolov8s.pt')
+
+            result = model(image)[0]
+            keypoints = sv.KeyPoints.from_ultralytics(result)
+
+            keypoints['names'] = [
+                 model.model.names[class_id]
+                 for class_id
+                 in keypoints.class_id
+             ]
+            ```
+        """
+        if not isinstance(value, (np.ndarray, list)):
+            raise TypeError("Value must be a np.ndarray or a list")
+
+        if isinstance(value, list):
+            value = np.array(value)
+
+        self.data[key] = value
+
     @classmethod
     def empty(cls) -> "KeyPoints":
         """

From 94e06ab0d6b71d87a3839207efe6b23d6bf74186 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 16:46:05 +0200
Subject: [PATCH 117/188] scale_image, resize_image changes

---
 docs/utils/image.md            |  10 +-
 supervision/__init__.py        |   4 +-
 supervision/annotators/core.py |   4 +-
 supervision/utils/image.py     | 167 ++++++++++++++++++++++-----------
 4 files changed, 125 insertions(+), 60 deletions(-)

diff --git a/docs/utils/image.md b/docs/utils/image.md
index 087aebd73..b61cddfce 100644
--- a/docs/utils/image.md
+++ b/docs/utils/image.md
@@ -18,10 +18,10 @@ status: new
 :::supervision.utils.image.crop_image
 
 <div class="md-typeset">
-  <h2>letterbox_image</h2>
+  <h2>scale_image</h2>
 </div>
 
-:::supervision.utils.image.letterbox_image
+:::supervision.utils.image.scale_image
 
 <div class="md-typeset">
   <h2>resize_image</h2>
@@ -29,6 +29,12 @@ status: new
 
 :::supervision.utils.image.resize_image
 
+<div class="md-typeset">
+  <h2>letterbox_image</h2>
+</div>
+
+:::supervision.utils.image.letterbox_image
+
 <div class="md-typeset">
   <h2>place_image</h2>
 </div>
diff --git a/supervision/__init__.py b/supervision/__init__.py
index 8c3acc265..d6aeeab59 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -78,8 +78,8 @@
     crop_image,
     letterbox_image,
     place_image,
-    resize_image,
-    resize_image_keeping_aspect_ratio,
+    scale_image,
+    resize_image
 )
 from supervision.utils.notebook import plot_image, plot_images_grid
 from supervision.utils.video import (
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 9f6cdb367..38ddc4421 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -13,7 +13,7 @@
 from supervision.draw.utils import draw_polygon
 from supervision.geometry.core import Position
 from supervision.utils.conversion import convert_for_annotation_method
-from supervision.utils.image import crop_image, place_image, resize_image
+from supervision.utils.image import crop_image, place_image, scale_image
 
 
 class BoundingBoxAnnotator(BaseAnnotator):
@@ -1965,7 +1965,7 @@ def annotate(
             crop_image(image=scene, xyxy=xyxy) for xyxy in detections.xyxy.astype(int)
         ]
         resized_crops = [
-            resize_image(image=crop, scale_factor=self.scale_factor) for crop in crops
+            scale_image(image=crop, scale_factor=self.scale_factor) for crop in crops
         ]
         anchors = detections.get_anchors_coordinates(anchor=self.position).astype(int)
 
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 954533a2c..99fcb3f24 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -7,6 +7,7 @@
 
 import cv2
 import numpy as np
+import numpy.typing as npt
 
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color, unify_to_bgr
@@ -26,7 +27,8 @@
 
 @convert_for_image_processing
 def crop_image(
-    image: ImageType, xyxy: Union[np.ndarray, List[int], Tuple[int, int, int, int]]
+    image: ImageType,
+    xyxy: Union[npt.NDArray[int], List[int], Tuple[int, int, int, int]]
 ) -> ImageType:
     """
     Crops the given image based on the given bounding box.
@@ -35,23 +37,49 @@ def crop_image(
         image (ImageType): The image to be cropped. `ImageType` is a flexible type,
             accepting either `numpy.ndarray` or `PIL.Image.Image`.
         xyxy (Union[np.ndarray, List[int], Tuple[int, int, int, int]]): A bounding box
-            coordinates in the format (x_min, y_min, x_max, y_max), accepted as either
-            a numpy array, a list, or a tuple.
+            coordinates in the format `(x_min, y_min, x_max, y_max)`, accepted as either
+            a `numpy.ndarray`, a `list`, or a `tuple`.
 
     Returns:
-        (ImageType): The cropped image.
+        (ImageType): The cropped image. The type is determined by the input type and
+            may be either a `numpy.ndarray` or `PIL.Image.Image`.
 
     Examples:
+
+    === "OpenCV"
+
         ```python
+        import cv2
         import supervision as sv
 
-        detection = sv.Detections(...)
-        with sv.ImageSink(target_dir_path='target/directory/path') as sink:
-            for xyxy in detection.xyxy:
-                cropped_image = sv.crop_image(image=image, xyxy=xyxy)
-                sink.save_image(image=cropped_image)
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        image.shape
+        # (1080, 1920, 3)
+
+        xyxy = [200, 400, 600, 800]
+        cropped_image = sv.crop_image(image=image, xyxy=xyxy)
+        cropped_image.shape
+        # (400, 400, 3)
         ```
-    """
+
+    === "Pillow"
+
+        ```python
+        from PIL import Image
+        import supervision as sv
+
+        image = Image.open(<SOURCE_IMAGE_PATH>)
+        image.size
+        # (1920, 1080)
+
+        xyxy = [200, 400, 600, 800]
+        cropped_image = sv.crop_image(image=image, xyxy=xyxy)
+        cropped_image.size
+        # (400, 400)
+        ```
+
+    ![crop_image](https://media.roboflow.com/supervision-docs/crop-image.png){ align=center width="800" }
+    """  # noqa E501 // docs
 
     if isinstance(xyxy, (list, tuple)):
         xyxy = np.array(xyxy)
@@ -61,29 +89,62 @@ def crop_image(
 
 
 @convert_for_image_processing
-def resize_image(image: np.ndarray, scale_factor: float) -> np.ndarray:
+def scale_image(image: ImageType, scale_factor: float) -> ImageType:
     """
-    Resizes an image by a given scale factor using cv2.INTER_LINEAR interpolation.
+    Scales the given image based on the given scale factor.
 
     Args:
-        image (np.ndarray): The input image to be resized.
+        image (ImageType): The image to be scaled. `ImageType` is a flexible type,
+            accepting either `numpy.ndarray` or `PIL.Image.Image`.
         scale_factor (float): The factor by which the image will be scaled. Scale
-            factor > 1.0 zooms in, < 1.0 zooms out.
+            factor > `1.0` zooms in, < `1.0` zooms out.
 
     Returns:
-        np.ndarray: The resized image.
+        (ImageType): The scaled image. The type is determined by the input type and
+            may be either a `numpy.ndarray` or `PIL.Image.Image`.
 
     Raises:
         ValueError: If the scale factor is non-positive.
+
+    Examples:
+
+    === "OpenCV"
+
+        ```python
+        import cv2
+        import supervision as sv
+
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        image.shape
+        # (1080, 1920, 3)
+
+        scaled_image = sv.scale_image(image=image, scale_factor=0.5)
+        scaled_image.shape
+        # (540, 960, 3)
+        ```
+
+    === "Pillow"
+
+        ```python
+        from PIL import Image
+        import supervision as sv
+
+        image = Image.open(<SOURCE_IMAGE_PATH>)
+        image.size
+        # (1920, 1080)
+
+        scaled_image = sv.scale_image(image=image, scale_factor=0.5)
+        scaled_image.size
+        # (540, 960)
+        ```
     """
     if scale_factor <= 0:
         raise ValueError("Scale factor must be positive.")
 
-    old_width, old_height = image.shape[1], image.shape[0]
-    new_width = int(old_width * scale_factor)
-    new_height = int(old_height * scale_factor)
-
-    return cv2.resize(image, (new_width, new_height), interpolation=cv2.INTER_LINEAR)
+    width_old, height_old = image.shape[1], image.shape[0]
+    width_new = int(width_old * scale_factor)
+    height_new = int(height_old * scale_factor)
+    return cv2.resize(image, (width_new, height_new), interpolation=cv2.INTER_LINEAR)
 
 
 def place_image(
@@ -573,9 +634,10 @@ def letterbox_image(
             decorator if function was called with PIL.Image)
     """
     color = unify_to_bgr(color=color)
-    resized_img = resize_image_keeping_aspect_ratio(
+    resized_img = resize_image(
         image=image,
-        desired_size=target_resolution_wh,
+        target_resolution_wh=target_resolution_wh,
+        keep_aspect_ratio=True
     )
     new_height, new_width = resized_img.shape[:2]
     top_padding = (target_resolution_wh[1] - new_height) // 2
@@ -594,40 +656,37 @@ def letterbox_image(
 
 
 @convert_for_image_processing
-def resize_image_keeping_aspect_ratio(
-    image: np.ndarray,
-    desired_size: Tuple[int, int],
-) -> np.ndarray:
+def resize_image(
+    image: ImageType,
+    target_resolution_wh: Tuple[int, int],
+    keep_aspect_ratio: bool = False
+) -> ImageType:
     """
-    Resize and pad image preserving its aspect ratio.
-
-    For example: input image is (640, 480) and we want to resize into
-    (1024, 1024). If this rectangular image is just resized naively
-    to square-shape output - aspect ratio would be altered. If we do not
-    want this to happen - we may resize bigger dimension (640) to 1024.
-    Ratio of change is 1.6. This ratio is later on used to calculate scaling
-    in the other dimension. As a result we have (1024, 768) image.
-
-    Parameters:
-    - image (np.ndarray): Input image (type will be adjusted by decorator,
-        you can provide PIL.Image)
-    - desired_size (Tuple[int, int]): image size (width, height) representing the
-        target dimensions. Parameter will be used to dictate maximum size of
-        output image. Output size may be smaller - to preserve aspect ratio of original
-        image.
+    Resizes the given image to a specified resolution. Can maintain the original aspect
+    ratio or resize directly to the desired dimensions.
+
+    Args:
+        image (ImageType): The image to be resized. `ImageType` is a flexible type,
+            accepting either `numpy.ndarray` or `PIL.Image.Image`.
+        target_resolution_wh (Tuple[int, int]): The target resolution as
+            `(width, height)`.
+        keep_aspect_ratio (bool, optional): Flag to maintain the image's original
+            aspect ratio. Defaults to `False`.
 
     Returns:
-        np.ndarray: resized image (type may be adjusted to PIL.Image by decorator
-            if function was called with PIL.Image)
+        ImageType: The resized image. The type is determined by the input type and
+            may be either a `numpy.ndarray` or `PIL.Image.Image`.
     """
-    if image.shape[:2] == desired_size[::-1]:
-        return image
-    img_ratio = image.shape[1] / image.shape[0]
-    desired_ratio = desired_size[0] / desired_size[1]
-    if img_ratio >= desired_ratio:
-        new_width = desired_size[0]
-        new_height = int(desired_size[0] / img_ratio)
+    if keep_aspect_ratio:
+        image_ratio = image.shape[1] / image.shape[0]
+        target_ratio = target_resolution_wh[0] / target_resolution_wh[1]
+        if image_ratio >= target_ratio:
+            width_new = target_resolution_wh[0]
+            height_new = int(target_resolution_wh[0] / image_ratio)
+        else:
+            height_new = target_resolution_wh[1]
+            width_new = int(target_resolution_wh[1] * image_ratio)
     else:
-        new_height = desired_size[1]
-        new_width = int(desired_size[1] * img_ratio)
-    return cv2.resize(image, (new_width, new_height))
+        width_new, height_new = target_resolution_wh
+
+    return cv2.resize(image, (width_new, height_new), interpolation=cv2.INTER_LINEAR)

From ad946893624e8609282035af3443d361f06b5564 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 14:46:45 +0000
Subject: [PATCH 118/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/__init__.py    | 2 +-
 supervision/utils/image.py | 8 +++-----
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index d6aeeab59..b14a37ab8 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -78,8 +78,8 @@
     crop_image,
     letterbox_image,
     place_image,
+    resize_image,
     scale_image,
-    resize_image
 )
 from supervision.utils.notebook import plot_image, plot_images_grid
 from supervision.utils.video import (
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 99fcb3f24..8fe25eea3 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -28,7 +28,7 @@
 @convert_for_image_processing
 def crop_image(
     image: ImageType,
-    xyxy: Union[npt.NDArray[int], List[int], Tuple[int, int, int, int]]
+    xyxy: Union[npt.NDArray[int], List[int], Tuple[int, int, int, int]],
 ) -> ImageType:
     """
     Crops the given image based on the given bounding box.
@@ -635,9 +635,7 @@ def letterbox_image(
     """
     color = unify_to_bgr(color=color)
     resized_img = resize_image(
-        image=image,
-        target_resolution_wh=target_resolution_wh,
-        keep_aspect_ratio=True
+        image=image, target_resolution_wh=target_resolution_wh, keep_aspect_ratio=True
     )
     new_height, new_width = resized_img.shape[:2]
     top_padding = (target_resolution_wh[1] - new_height) // 2
@@ -659,7 +657,7 @@ def letterbox_image(
 def resize_image(
     image: ImageType,
     target_resolution_wh: Tuple[int, int],
-    keep_aspect_ratio: bool = False
+    keep_aspect_ratio: bool = False,
 ) -> ImageType:
     """
     Resizes the given image to a specified resolution. Can maintain the original aspect

From 233d25d4c539eb180e2091856f3ebdddb6695c95 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 17:48:13 +0200
Subject: [PATCH 119/188] fix `resize_image` tests after rename

---
 supervision/utils/image.py | 116 ++++++++++++++++++++++++-------------
 test/utils/test_image.py   |  16 ++---
 2 files changed, 86 insertions(+), 46 deletions(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 8fe25eea3..4c5cc9c67 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -135,7 +135,7 @@ def scale_image(image: ImageType, scale_factor: float) -> ImageType:
 
         scaled_image = sv.scale_image(image=image, scale_factor=0.5)
         scaled_image.size
-        # (540, 960)
+        # (960, 540)
         ```
     """
     if scale_factor <= 0:
@@ -147,6 +147,81 @@ def scale_image(image: ImageType, scale_factor: float) -> ImageType:
     return cv2.resize(image, (width_new, height_new), interpolation=cv2.INTER_LINEAR)
 
 
+@convert_for_image_processing
+def resize_image(
+    image: ImageType,
+    resolution_wh: Tuple[int, int],
+    keep_aspect_ratio: bool = False,
+) -> ImageType:
+    """
+    Resizes the given image to a specified resolution. Can maintain the original aspect
+    ratio or resize directly to the desired dimensions.
+
+    Args:
+        image (ImageType): The image to be resized. `ImageType` is a flexible type,
+            accepting either `numpy.ndarray` or `PIL.Image.Image`.
+        resolution_wh (Tuple[int, int]): The target resolution as
+            `(width, height)`.
+        keep_aspect_ratio (bool, optional): Flag to maintain the image's original
+            aspect ratio. Defaults to `False`.
+
+    Returns:
+        ImageType: The resized image. The type is determined by the input type and
+            may be either a `numpy.ndarray` or `PIL.Image.Image`.
+
+    Examples:
+
+    === "OpenCV"
+
+        ```python
+        import cv2
+        import supervision as sv
+
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        image.shape
+        # (1080, 1920, 3)
+
+        resized_image = sv.resize_image(
+            image=image, resolution_wh=(1000, 1000), keep_aspect_ratio=True
+        )
+        resized_image.shape
+        # (562, 1000, 3)
+        ```
+
+    === "Pillow"
+
+        ```python
+        from PIL import Image
+        import supervision as sv
+
+        image = Image.open(<SOURCE_IMAGE_PATH>)
+        image.size
+        # (1920, 1080)
+
+        resized_image = sv.resize_image(
+            image=image, resolution_wh=(1000, 1000), keep_aspect_ratio=True
+        )
+        resized_image.size
+        # (1000, 562)
+        ```
+        
+    ![resize_image](https://media.roboflow.com/supervision-docs/resize-image.png){ align=center width="800" }
+    """  # noqa E501 // docs
+    if keep_aspect_ratio:
+        image_ratio = image.shape[1] / image.shape[0]
+        target_ratio = resolution_wh[0] / resolution_wh[1]
+        if image_ratio >= target_ratio:
+            width_new = resolution_wh[0]
+            height_new = int(resolution_wh[0] / image_ratio)
+        else:
+            height_new = resolution_wh[1]
+            width_new = int(resolution_wh[1] * image_ratio)
+    else:
+        width_new, height_new = resolution_wh
+
+    return cv2.resize(image, (width_new, height_new), interpolation=cv2.INTER_LINEAR)
+
+
 def place_image(
     scene: np.ndarray, image: np.ndarray, anchor: Tuple[int, int]
 ) -> np.ndarray:
@@ -635,7 +710,7 @@ def letterbox_image(
     """
     color = unify_to_bgr(color=color)
     resized_img = resize_image(
-        image=image, target_resolution_wh=target_resolution_wh, keep_aspect_ratio=True
+        image=image, resolution_wh=target_resolution_wh, keep_aspect_ratio=True
     )
     new_height, new_width = resized_img.shape[:2]
     top_padding = (target_resolution_wh[1] - new_height) // 2
@@ -651,40 +726,3 @@ def letterbox_image(
         cv2.BORDER_CONSTANT,
         value=color,
     )
-
-
-@convert_for_image_processing
-def resize_image(
-    image: ImageType,
-    target_resolution_wh: Tuple[int, int],
-    keep_aspect_ratio: bool = False,
-) -> ImageType:
-    """
-    Resizes the given image to a specified resolution. Can maintain the original aspect
-    ratio or resize directly to the desired dimensions.
-
-    Args:
-        image (ImageType): The image to be resized. `ImageType` is a flexible type,
-            accepting either `numpy.ndarray` or `PIL.Image.Image`.
-        target_resolution_wh (Tuple[int, int]): The target resolution as
-            `(width, height)`.
-        keep_aspect_ratio (bool, optional): Flag to maintain the image's original
-            aspect ratio. Defaults to `False`.
-
-    Returns:
-        ImageType: The resized image. The type is determined by the input type and
-            may be either a `numpy.ndarray` or `PIL.Image.Image`.
-    """
-    if keep_aspect_ratio:
-        image_ratio = image.shape[1] / image.shape[0]
-        target_ratio = target_resolution_wh[0] / target_resolution_wh[1]
-        if image_ratio >= target_ratio:
-            width_new = target_resolution_wh[0]
-            height_new = int(target_resolution_wh[0] / image_ratio)
-        else:
-            height_new = target_resolution_wh[1]
-            width_new = int(target_resolution_wh[1] * image_ratio)
-    else:
-        width_new, height_new = target_resolution_wh
-
-    return cv2.resize(image, (width_new, height_new), interpolation=cv2.INTER_LINEAR)
diff --git a/test/utils/test_image.py b/test/utils/test_image.py
index 50b6b5c1b..b3e28a277 100644
--- a/test/utils/test_image.py
+++ b/test/utils/test_image.py
@@ -8,19 +8,20 @@
 from supervision.utils.image import (
     create_tiles,
     letterbox_image,
-    resize_image_keeping_aspect_ratio,
+    resize_image,
 )
 
 
-def test_resize_image_keeping_aspect_ratio_for_opencv_image() -> None:
+def test_resize_image_for_opencv_image() -> None:
     # given
     image = np.zeros((480, 640, 3), dtype=np.uint8)
     expected_result = np.zeros((768, 1024, 3), dtype=np.uint8)
 
     # when
-    result = resize_image_keeping_aspect_ratio(
+    result = resize_image(
         image=image,
-        desired_size=(1024, 1024),
+        resolution_wh=(1024, 1024),
+        keep_aspect_ratio=True,
     )
 
     # then
@@ -29,15 +30,16 @@ def test_resize_image_keeping_aspect_ratio_for_opencv_image() -> None:
     ), "Expected output shape to be (w, h): (1024, 768)"
 
 
-def test_resize_image_keeping_aspect_ratio_for_pillow_image() -> None:
+def test_resize_image_for_pillow_image() -> None:
     # given
     image = Image.new(mode="RGB", size=(640, 480), color=(0, 0, 0))
     expected_result = Image.new(mode="RGB", size=(1024, 768), color=(0, 0, 0))
 
     # when
-    result = resize_image_keeping_aspect_ratio(
+    result = resize_image(
         image=image,
-        desired_size=(1024, 1024),
+        resolution_wh=(1024, 1024),
+        keep_aspect_ratio=True,
     )
 
     # then

From a7dccfcc0d3f168e36b9f4be06686206be1d3260 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 15:48:30 +0000
Subject: [PATCH 120/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/utils/image.py | 2 +-
 test/utils/test_image.py   | 6 +-----
 2 files changed, 2 insertions(+), 6 deletions(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 4c5cc9c67..e04ea45ed 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -204,7 +204,7 @@ def resize_image(
         resized_image.size
         # (1000, 562)
         ```
-        
+
     ![resize_image](https://media.roboflow.com/supervision-docs/resize-image.png){ align=center width="800" }
     """  # noqa E501 // docs
     if keep_aspect_ratio:
diff --git a/test/utils/test_image.py b/test/utils/test_image.py
index b3e28a277..a114d9aae 100644
--- a/test/utils/test_image.py
+++ b/test/utils/test_image.py
@@ -5,11 +5,7 @@
 from PIL import Image, ImageChops
 
 from supervision import Color, Point
-from supervision.utils.image import (
-    create_tiles,
-    letterbox_image,
-    resize_image,
-)
+from supervision.utils.image import create_tiles, letterbox_image, resize_image
 
 
 def test_resize_image_for_opencv_image() -> None:

From 774ac2ed4f82706c0a889741b2619cc8575b5ee0 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 17:59:19 +0200
Subject: [PATCH 121/188] update `letterbox_image` docs

---
 supervision/utils/image.py | 86 +++++++++++++++++++-------------------
 test/utils/test_image.py   |  4 +-
 2 files changed, 45 insertions(+), 45 deletions(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index e04ea45ed..274cef2f6 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -222,6 +222,48 @@ def resize_image(
     return cv2.resize(image, (width_new, height_new), interpolation=cv2.INTER_LINEAR)
 
 
+@convert_for_image_processing
+def letterbox_image(
+    image: ImageType,
+    resolution_wh: Tuple[int, int],
+    color: Union[Tuple[int, int, int], Color] = (0, 0, 0),
+) -> ImageType:
+    """
+    Resizes and pads an image to a specified resolution with a given color, maintaining
+    the original aspect ratio.
+
+    Args:
+        image (ImageType): The image to be resized. `ImageType` is a flexible type,
+            accepting either `numpy.ndarray` or `PIL.Image.Image`.
+        resolution_wh (Tuple[int, int]): The target resolution as
+            `(width, height)`.
+        color (Union[Tuple[int, int, int], Color]): The color to pad with. If tuple
+            provided it should be in BGR format.
+
+    Returns:
+        ImageType: The resized image. The type is determined by the input type and
+            may be either a `numpy.ndarray` or `PIL.Image.Image`.
+    """
+    color = unify_to_bgr(color=color)
+    resized_image = resize_image(
+        image=image, resolution_wh=resolution_wh, keep_aspect_ratio=True
+    )
+    height_new, width_new = resized_image.shape[:2]
+    padding_top = (resolution_wh[1] - height_new) // 2
+    padding_bottom = resolution_wh[1] - height_new - padding_top
+    padding_left = (resolution_wh[0] - width_new) // 2
+    padding_right = resolution_wh[0] - width_new - padding_left
+    return cv2.copyMakeBorder(
+        resized_image,
+        padding_top,
+        padding_bottom,
+        padding_left,
+        padding_right,
+        cv2.BORDER_CONSTANT,
+        value=color,
+    )
+
+
 def place_image(
     scene: np.ndarray, image: np.ndarray, anchor: Tuple[int, int]
 ) -> np.ndarray:
@@ -434,7 +476,7 @@ def create_tiles(
         single_tile_size = _aggregate_images_shape(images=images, mode=tile_scaling)
     resized_images = [
         letterbox_image(
-            image=i, target_resolution_wh=single_tile_size, color=tile_padding_color
+            image=i, resolution_wh=single_tile_size, color=tile_padding_color
         )
         for i in images
     ]
@@ -684,45 +726,3 @@ def _generate_color_image(
     shape: Tuple[int, int], color: Tuple[int, int, int]
 ) -> np.ndarray:
     return np.ones(shape[::-1] + (3,), dtype=np.uint8) * color
-
-
-@convert_for_image_processing
-def letterbox_image(
-    image: ImageType,
-    target_resolution_wh: Tuple[int, int],
-    color: Union[Tuple[int, int, int], Color] = (0, 0, 0),
-) -> np.ndarray:
-    """
-    Resize and pad image to fit the desired size, preserving its aspect
-    ratio, adding padding of given color if needed to maintain aspect ratio.
-
-    Args:
-        image (ImageType): Input image (type will be adjusted by decorator,
-            you can provide PIL.Image)
-        target_resolution_wh (Tuple[int, int]): image size (width, height) representing
-            the target dimensions.
-        color (Union[Tuple[int, int, int], Color]): the color to pad with - If
-            tuple provided - should be BGR.
-
-    Returns:
-        ImageType: letterboxed image (type may be adjusted to PIL.Image by
-            decorator if function was called with PIL.Image)
-    """
-    color = unify_to_bgr(color=color)
-    resized_img = resize_image(
-        image=image, resolution_wh=target_resolution_wh, keep_aspect_ratio=True
-    )
-    new_height, new_width = resized_img.shape[:2]
-    top_padding = (target_resolution_wh[1] - new_height) // 2
-    bottom_padding = target_resolution_wh[1] - new_height - top_padding
-    left_padding = (target_resolution_wh[0] - new_width) // 2
-    right_padding = target_resolution_wh[0] - new_width - left_padding
-    return cv2.copyMakeBorder(
-        resized_img,
-        top_padding,
-        bottom_padding,
-        left_padding,
-        right_padding,
-        cv2.BORDER_CONSTANT,
-        value=color,
-    )
diff --git a/test/utils/test_image.py b/test/utils/test_image.py
index a114d9aae..487434aed 100644
--- a/test/utils/test_image.py
+++ b/test/utils/test_image.py
@@ -60,7 +60,7 @@ def test_letterbox_image_for_opencv_image() -> None:
 
     # when
     result = letterbox_image(
-        image=image, target_resolution_wh=(1024, 1024), color=(255, 255, 255)
+        image=image, resolution_wh=(1024, 1024), color=(255, 255, 255)
     )
 
     # then
@@ -86,7 +86,7 @@ def test_letterbox_image_for_pillow_image() -> None:
 
     # when
     result = letterbox_image(
-        image=image, target_resolution_wh=(1024, 1024), color=(255, 255, 255)
+        image=image, resolution_wh=(1024, 1024), color=(255, 255, 255)
     )
 
     # then

From 079e62fb0c544248cc6511d79d6be664928aa81e Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 21:23:23 +0200
Subject: [PATCH 122/188] rename `place_image` to overlay `image`

---
 docs/utils/image.md            | 14 ++---
 supervision/__init__.py        |  2 +-
 supervision/annotators/core.py |  4 +-
 supervision/utils/image.py     | 96 +++++++++++++++++++++++++---------
 4 files changed, 81 insertions(+), 35 deletions(-)

diff --git a/docs/utils/image.md b/docs/utils/image.md
index b61cddfce..16a18dc40 100644
--- a/docs/utils/image.md
+++ b/docs/utils/image.md
@@ -5,12 +5,6 @@ status: new
 
 # Image Utils
 
-<div class="md-typeset">
-  <h2>ImageSink</h2>
-</div>
-
-:::supervision.utils.image.ImageSink
-
 <div class="md-typeset">
   <h2>crop_image</h2>
 </div>
@@ -39,4 +33,10 @@ status: new
   <h2>place_image</h2>
 </div>
 
-:::supervision.utils.image.place_image
+:::supervision.utils.image.overlay_image
+
+<div class="md-typeset">
+  <h2>ImageSink</h2>
+</div>
+
+:::supervision.utils.image.ImageSink
diff --git a/supervision/__init__.py b/supervision/__init__.py
index b14a37ab8..9ff095573 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -77,7 +77,7 @@
     create_tiles,
     crop_image,
     letterbox_image,
-    place_image,
+    overlay_image,
     resize_image,
     scale_image,
 )
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 38ddc4421..854a9ece6 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -13,7 +13,7 @@
 from supervision.draw.utils import draw_polygon
 from supervision.geometry.core import Position
 from supervision.utils.conversion import convert_for_annotation_method
-from supervision.utils.image import crop_image, place_image, scale_image
+from supervision.utils.image import crop_image, overlay_image, scale_image
 
 
 class BoundingBoxAnnotator(BaseAnnotator):
@@ -1974,7 +1974,7 @@ def annotate(
             (x1, y1), (x2, y2) = self.calculate_crop_coordinates(
                 anchor=anchor, crop_wh=crop_wh, position=self.position
             )
-            scene = place_image(scene=scene, image=resized_crop, anchor=(x1, y1))
+            scene = overlay_image(scene=scene, inserted_image=resized_crop, anchor=(x1, y1))
             color = resolve_color(
                 color=self.border_color,
                 detections=detections,
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 274cef2f6..b579ba75f 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -243,7 +243,41 @@ def letterbox_image(
     Returns:
         ImageType: The resized image. The type is determined by the input type and
             may be either a `numpy.ndarray` or `PIL.Image.Image`.
-    """
+
+    ## Examples:
+
+    === "OpenCV"
+
+        ```python
+        import cv2
+        import supervision as sv
+
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        image.shape
+        # (1080, 1920, 3)
+
+        letterboxed_image = sv.letterbox_image(image=image, resolution_wh=(1000, 1000))
+        letterboxed_image.shape
+        # (1000, 1000, 3)
+        ```
+
+    === "Pillow"
+
+        ```python
+        from PIL import Image
+        import supervision as sv
+
+        image = Image.open(<SOURCE_IMAGE_PATH>)
+        image.size
+        # (1920, 1080)
+
+        letterboxed_image = sv.letterbox_image(image=image, resolution_wh=(1000, 1000))
+        letterboxed_image.size
+        # (1000, 1000)
+        ```
+        
+    ![letterbox_image](https://media.roboflow.com/supervision-docs/letterbox-image.png){ align=center width="800" }
+    """  # noqa E501 // docs
     color = unify_to_bgr(color=color)
     resized_image = resize_image(
         image=image, resolution_wh=resolution_wh, keep_aspect_ratio=True
@@ -264,48 +298,60 @@ def letterbox_image(
     )
 
 
-def place_image(
-    scene: np.ndarray, image: np.ndarray, anchor: Tuple[int, int]
-) -> np.ndarray:
+def overlay_image(
+    image: npt.NDArray[np.uint8],
+    overlay: npt.NDArray[np.uint8],
+    anchor: Tuple[int, int]
+) -> npt.NDArray[np.uint8]:
     """
     Places an image onto a scene at a given anchor point, handling cases where
     the image's position is partially or completely outside the scene's bounds.
 
     Args:
-        scene (np.ndarray): The background scene onto which the image is placed.
-        image (np.ndarray): The image to be placed onto the scene.
-        anchor (Tuple[int, int]): The (x, y) coordinates in the scene where the
+        image (np.ndarray): The background scene onto which the image is placed.
+        overlay (np.ndarray): The image to be placed onto the scene.
+        anchor (Tuple[int, int]): The `(x, y)` coordinates in the scene where the
             top-left corner of the image will be placed.
 
     Returns:
-        np.ndarray: The modified scene with the image placed at the anchor point,
-            or unchanged if the image placement is completely outside the scene.
+        np.ndarray: The result image with overlay.
+
+    Examples:
+        ```python
+        import cv2
+        import numpy as np
+        import supervision as sv
+
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        overlay = np.zeros((200, 200, 3), dtype=np.uint8)
+        result_image = sv.letterbox_image(
+            image=image, overlay=overlay, anchor=(200, 400))
+        ```
     """
-    scene_height, scene_width = scene.shape[:2]
-    image_height, image_width = image.shape[:2]
+    scene_height, scene_width = image.shape[:2]
+    image_height, image_width = overlay.shape[:2]
     anchor_x, anchor_y = anchor
 
     is_out_horizontally = anchor_x + image_width <= 0 or anchor_x >= scene_width
     is_out_vertically = anchor_y + image_height <= 0 or anchor_y >= scene_height
 
     if is_out_horizontally or is_out_vertically:
-        return scene
+        return image
 
-    start_y = max(anchor_y, 0)
-    start_x = max(anchor_x, 0)
-    end_y = min(scene_height, anchor_y + image_height)
-    end_x = min(scene_width, anchor_x + image_width)
+    x_min = max(anchor_x, 0)
+    y_min = max(anchor_y, 0)
+    x_max = min(scene_width, anchor_x + image_width)
+    y_max = min(scene_height, anchor_y + image_height)
 
-    crop_start_y = max(-anchor_y, 0)
-    crop_start_x = max(-anchor_x, 0)
-    crop_end_y = image_height - max((anchor_y + image_height) - scene_height, 0)
-    crop_end_x = image_width - max((anchor_x + image_width) - scene_width, 0)
+    crop_x_min = max(-anchor_x, 0)
+    crop_y_min = max(-anchor_y, 0)
+    crop_x_max = image_width - max((anchor_x + image_width) - scene_width, 0)
+    crop_y_max = image_height - max((anchor_y + image_height) - scene_height, 0)
 
-    scene[start_y:end_y, start_x:end_x] = image[
-        crop_start_y:crop_end_y, crop_start_x:crop_end_x
-    ]
+    image[y_min:y_max, x_min:x_max] = \
+        overlay[crop_y_min:crop_y_max, crop_x_min:crop_x_max]
 
-    return scene
+    return image
 
 
 class ImageSink:
@@ -335,7 +381,7 @@ def __init__(
                     source_path='source_video.mp4', stride=2):
                     sink.save_image(image=image)
             ```
-        """
+        """  # noqa E501 // docs
 
         self.target_dir_path = target_dir_path
         self.overwrite = overwrite

From f872fddaffe2d34c11f2fcc62b6d1b53a28aec85 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 19:24:02 +0000
Subject: [PATCH 123/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/annotators/core.py | 4 +++-
 supervision/utils/image.py     | 9 +++++----
 2 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 854a9ece6..ac9018625 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -1974,7 +1974,9 @@ def annotate(
             (x1, y1), (x2, y2) = self.calculate_crop_coordinates(
                 anchor=anchor, crop_wh=crop_wh, position=self.position
             )
-            scene = overlay_image(scene=scene, inserted_image=resized_crop, anchor=(x1, y1))
+            scene = overlay_image(
+                scene=scene, inserted_image=resized_crop, anchor=(x1, y1)
+            )
             color = resolve_color(
                 color=self.border_color,
                 detections=detections,
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index b579ba75f..f6eef9ca8 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -275,7 +275,7 @@ def letterbox_image(
         letterboxed_image.size
         # (1000, 1000)
         ```
-        
+
     ![letterbox_image](https://media.roboflow.com/supervision-docs/letterbox-image.png){ align=center width="800" }
     """  # noqa E501 // docs
     color = unify_to_bgr(color=color)
@@ -301,7 +301,7 @@ def letterbox_image(
 def overlay_image(
     image: npt.NDArray[np.uint8],
     overlay: npt.NDArray[np.uint8],
-    anchor: Tuple[int, int]
+    anchor: Tuple[int, int],
 ) -> npt.NDArray[np.uint8]:
     """
     Places an image onto a scene at a given anchor point, handling cases where
@@ -348,8 +348,9 @@ def overlay_image(
     crop_x_max = image_width - max((anchor_x + image_width) - scene_width, 0)
     crop_y_max = image_height - max((anchor_y + image_height) - scene_height, 0)
 
-    image[y_min:y_max, x_min:x_max] = \
-        overlay[crop_y_min:crop_y_max, crop_x_min:crop_x_max]
+    image[y_min:y_max, x_min:x_max] = overlay[
+        crop_y_min:crop_y_max, crop_x_min:crop_x_max
+    ]
 
     return image
 

From c30e377eb5393aed81b182d6a66217e73c6d439a Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 22:07:12 +0200
Subject: [PATCH 124/188] more docs improvements

---
 docs/utils/image.md             |  2 +-
 supervision/__init__.py         |  1 +
 supervision/utils/conversion.py |  4 ++--
 supervision/utils/image.py      | 31 ++++++++++++-------------------
 supervision/utils/iterables.py  |  4 ++--
 5 files changed, 18 insertions(+), 24 deletions(-)

diff --git a/docs/utils/image.md b/docs/utils/image.md
index 16a18dc40..87fd1943e 100644
--- a/docs/utils/image.md
+++ b/docs/utils/image.md
@@ -30,7 +30,7 @@ status: new
 :::supervision.utils.image.letterbox_image
 
 <div class="md-typeset">
-  <h2>place_image</h2>
+  <h2>overlay_image</h2>
 </div>
 
 :::supervision.utils.image.overlay_image
diff --git a/supervision/__init__.py b/supervision/__init__.py
index 9ff095573..6cdb23ca9 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -34,6 +34,7 @@
     ClassificationDataset,
     DetectionDataset,
 )
+from supervision.utils.conversion import pillow_to_cv2, cv2_to_pillow
 from supervision.detection.annotate import BoxAnnotator
 from supervision.detection.core import Detections
 from supervision.detection.line_zone import LineZone, LineZoneAnnotator
diff --git a/supervision/utils/conversion.py b/supervision/utils/conversion.py
index 608104bcd..8ddce9695 100644
--- a/supervision/utils/conversion.py
+++ b/supervision/utils/conversion.py
@@ -81,7 +81,7 @@ def pillow_to_cv2(image: Image.Image) -> np.ndarray:
         image (Image.Image): Pillow image (in RGB format).
 
     Returns:
-        np.ndarray: Input image converted to OpenCV format.
+        (np.ndarray): Input image converted to OpenCV format.
     """
     scene = np.array(image)
     scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
@@ -97,7 +97,7 @@ def cv2_to_pillow(image: np.ndarray) -> Image.Image:
         image (np.ndarray): OpenCV image (in BGR format).
 
     Returns:
-        Image.Image: Input image converted to Pillow format.
+        (Image.Image): Input image converted to Pillow format.
     """
     image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
     return Image.fromarray(image)
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index b579ba75f..488a9d360 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -44,8 +44,6 @@ def crop_image(
         (ImageType): The cropped image. The type is determined by the input type and
             may be either a `numpy.ndarray` or `PIL.Image.Image`.
 
-    Examples:
-
     === "OpenCV"
 
         ```python
@@ -106,8 +104,6 @@ def scale_image(image: ImageType, scale_factor: float) -> ImageType:
     Raises:
         ValueError: If the scale factor is non-positive.
 
-    Examples:
-
     === "OpenCV"
 
         ```python
@@ -166,11 +162,9 @@ def resize_image(
             aspect ratio. Defaults to `False`.
 
     Returns:
-        ImageType: The resized image. The type is determined by the input type and
+        (ImageType): The resized image. The type is determined by the input type and
             may be either a `numpy.ndarray` or `PIL.Image.Image`.
 
-    Examples:
-
     === "OpenCV"
 
         ```python
@@ -226,7 +220,7 @@ def resize_image(
 def letterbox_image(
     image: ImageType,
     resolution_wh: Tuple[int, int],
-    color: Union[Tuple[int, int, int], Color] = (0, 0, 0),
+    color: Union[Tuple[int, int, int], Color] = Color.BLACK,
 ) -> ImageType:
     """
     Resizes and pads an image to a specified resolution with a given color, maintaining
@@ -241,11 +235,9 @@ def letterbox_image(
             provided it should be in BGR format.
 
     Returns:
-        ImageType: The resized image. The type is determined by the input type and
+        (ImageType): The resized image. The type is determined by the input type and
             may be either a `numpy.ndarray` or `PIL.Image.Image`.
 
-    ## Examples:
-
     === "OpenCV"
 
         ```python
@@ -314,7 +306,7 @@ def overlay_image(
             top-left corner of the image will be placed.
 
     Returns:
-        np.ndarray: The result image with overlay.
+        (np.ndarray): The result image with overlay.
 
     Examples:
         ```python
@@ -323,10 +315,11 @@ def overlay_image(
         import supervision as sv
 
         image = cv2.imread(<SOURCE_IMAGE_PATH>)
-        overlay = np.zeros((200, 200, 3), dtype=np.uint8)
-        result_image = sv.letterbox_image(
-            image=image, overlay=overlay, anchor=(200, 400))
+        overlay = np.zeros((400, 400, 3), dtype=np.uint8)
+        result_image = sv.overlay_image(image=image, overlay=overlay, anchor=(200, 400))
         ```
+
+    ![overlay_image](https://media.roboflow.com/supervision-docs/overlay-image.png){ align=center width="800" }
     """
     scene_height, scene_width = image.shape[:2]
     image_height, image_width = overlay.shape[:2]
@@ -374,11 +367,11 @@ def __init__(
         Examples:
             ```python
             import supervision as sv
+            
+            frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>, stride=2)
 
-            with sv.ImageSink(target_dir_path='target/directory/path',
-                              overwrite=True) as sink:
-                for image in sv.get_video_frames_generator(
-                    source_path='source_video.mp4', stride=2):
+            with sv.ImageSink(target_dir_path=<TARGET_CROPS_DIRECTORY>) as sink:
+                for image in frames_generator:
                     sink.save_image(image=image)
             ```
         """  # noqa E501 // docs
diff --git a/supervision/utils/iterables.py b/supervision/utils/iterables.py
index ad570379c..52bfbeb6c 100644
--- a/supervision/utils/iterables.py
+++ b/supervision/utils/iterables.py
@@ -16,7 +16,7 @@ def create_batches(
         batch_size (int): The expected size of a batch.
 
     Returns:
-        Generator[List[V], None, None]: A generator that yields chunks
+        (Generator[List[V], None, None]): A generator that yields chunks
             of `sequence` of size `batch_size`, up to the length of
             the input `sequence`.
 
@@ -54,7 +54,7 @@ def fill(sequence: List[V], desired_size: int, content: V) -> List[V]:
             `sequence` as padding.
 
     Returns:
-        List[V]: A padded version of the input `sequence` (if needed).
+        (List[V]): A padded version of the input `sequence` (if needed).
 
     Examples:
         ```python

From 6248fa7d170ce765e5d59d2bce839836171841f3 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 20:08:10 +0000
Subject: [PATCH 125/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/__init__.py    | 2 +-
 supervision/utils/image.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 6cdb23ca9..f8e7a8324 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -34,7 +34,6 @@
     ClassificationDataset,
     DetectionDataset,
 )
-from supervision.utils.conversion import pillow_to_cv2, cv2_to_pillow
 from supervision.detection.annotate import BoxAnnotator
 from supervision.detection.core import Detections
 from supervision.detection.line_zone import LineZone, LineZoneAnnotator
@@ -72,6 +71,7 @@
 from supervision.geometry.utils import get_polygon_center
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
+from supervision.utils.conversion import cv2_to_pillow, pillow_to_cv2
 from supervision.utils.file import list_files_with_extensions
 from supervision.utils.image import (
     ImageSink,
diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index dd3316ec4..44ccbeac1 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -368,7 +368,7 @@ def __init__(
         Examples:
             ```python
             import supervision as sv
-            
+
             frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>, stride=2)
 
             with sv.ImageSink(target_dir_path=<TARGET_CROPS_DIRECTORY>) as sink:

From d929d6f58b989a0fd38a359ca4b12b40921cccf2 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 22:44:10 +0200
Subject: [PATCH 126/188] `How to Save Detections` guide update

---
 docs/how_to/save_detections.md | 222 ++++++++++++++++++++++++++++-----
 1 file changed, 191 insertions(+), 31 deletions(-)

diff --git a/docs/how_to/save_detections.md b/docs/how_to/save_detections.md
index 81de930ec..e0233f9b5 100644
--- a/docs/how_to/save_detections.md
+++ b/docs/how_to/save_detections.md
@@ -9,48 +9,64 @@ TODO
 
 ## Run Detection
 
+First, you'll need to obtain predictions from your object detection or segmentation 
+model. You can learn more on this topic in our 
+[How to Detect and Annotate](/latest/how_to/detect_and_annotate.md) guide.
+
 === "Inference"
 
     ```python
-    import cv2
+    import supervision as sv
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
-    results = model.infer(image)[0]
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    for frame in frames_generator:
+
+        results = model.infer(image)[0]
+        detections = sv.Detections.from_inference(results)
     ```
 
 === "Ultralytics"
 
     ```python
-    import cv2
+    import supervision as sv
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
-    results = model(image)[0]
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    for frame in frames_generator:
+
+        results = model(frame)[0]
+        detections = sv.Detections.from_ultralytics(results)
     ```
 
 === "Transformers"
 
     ```python
     import torch
-    from PIL import Image
+    import supervision as sv
     from transformers import DetrImageProcessor, DetrForObjectDetection
 
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    for frame in frames_generator:
 
-    image = Image.open(<SOURCE_IMAGE_APTH>)
-    inputs = processor(images=image, return_tensors="pt")
+        frame = sv.cv2_to_pillow(frame)
+        inputs = processor(images=frame, return_tensors="pt")
 
-    with torch.no_grad():
-        outputs = model(**inputs)
+        with torch.no_grad():
+            outputs = model(**inputs)
 
-    width, height = image.size
-    target_size = torch.tensor([[height, width]])
-    results = processor.post_process_object_detection(
-        outputs=outputs, target_sizes=target_size)[0]
+        width, height = frame.size
+        target_size = torch.tensor([[height, width]])
+        results = processor.post_process_object_detection(
+            outputs=outputs, target_sizes=target_size)[0]
+        detections = sv.Detections.from_transformers(results)
     ```
 
 ## Save Detections as CSV
@@ -59,14 +75,15 @@ TODO
 
 === "Inference"
 
-    ```python
+    ```{ .py hl_lines="7 12" }
     import supervision as sv
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
 
     with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
-        for frame in sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>):
+        for frame in frames_generator:
 
             results = model.infer(image)[0]
             detections = sv.Detections.from_inference(results)
@@ -75,14 +92,15 @@ TODO
 
 === "Ultralytics"
 
-    ```python
+    ```{ .py hl_lines="7 12" }
     import supervision as sv
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
 
     with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
-        for frame in sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>):
+        for frame in frames_generator:
 
             results = model(frame)[0]
             detections = sv.Detections.from_ultralytics(results)
@@ -91,34 +109,176 @@ TODO
 
 === "Transformers"
 
-    ```python
+    ```{ .py hl_lines="9 23" }
     import torch
-    from PIL import Image
+    import supervision as sv
     from transformers import DetrImageProcessor, DetrForObjectDetection
 
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
 
-    image = Image.open(<SOURCE_IMAGE_APTH>)
-    inputs = processor(images=image, return_tensors="pt")
+    with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
+        for frame in frames_generator:
+
+            frame = sv.cv2_to_pillow(frame)
+            inputs = processor(images=frame, return_tensors="pt")
 
-    with torch.no_grad():
-        outputs = model(**inputs)
+            with torch.no_grad():
+                outputs = model(**inputs)
 
-    width, height = image.size
-    target_size = torch.tensor([[height, width]])
-    results = processor.post_process_object_detection(
-        outputs=outputs, target_sizes=target_size)[0]
+            width, height = frame.size
+            target_size = torch.tensor([[height, width]])
+            results = processor.post_process_object_detection(
+                outputs=outputs, target_sizes=target_size)[0]
+            detections = sv.Detections.from_transformers(results)
+            sink.append(detections, {})
     ```
 
+TODO
+
+| x_min   | y_min    | x_max   | y_max    | class_id | confidence | tracker_id | class_name |
+|---------|----------|---------|----------|----------|------------|------------|------------|
+| 2941.14 | 1269.31  | 3220.77 | 1500.67  | 2        | 0.8517     |            | car        |
+| 944.889 | 899.641  | 1235.42 | 1308.80  | 7        | 0.6752     |            | truck      |
+| 1439.78 | 1077.79  | 1621.27 | 1231.40  | 2        | 0.6450     |            | car        |
+
 ## Custom Fields
 
 TODO
 
-## Save Detections as JSON
+=== "Inference"
+
+    ```{ .py hl_lines="8 12" }
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
+        for frame_index, frame in enumerate(frames_generator):
+
+            results = model.infer(image)[0]
+            detections = sv.Detections.from_inference(results)
+            sink.append(detections, {"frame_index": frame_index})
+    ```
+
+=== "Ultralytics"
+
+    ```{ .py hl_lines="8 12" }
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8n.pt")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
+        for frame_index, frame in enumerate(frames_generator):
+
+            results = model(frame)[0]
+            detections = sv.Detections.from_ultralytics(results)
+            sink.append(detections, {"frame_index": frame_index})
+    ```
+
+=== "Transformers"
+
+    ```{ .py hl_lines="10 23" }
+    import torch
+    import supervision as sv
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    with sv.CSVSink(<TARGET_CSV_PATH>) as sink:
+        for frame_index, frame in enumerate(frames_generator):
+
+            frame = sv.cv2_to_pillow(frame)
+            inputs = processor(images=frame, return_tensors="pt")
+
+            with torch.no_grad():
+                outputs = model(**inputs)
+
+            width, height = frame.size
+            target_size = torch.tensor([[height, width]])
+            results = processor.post_process_object_detection(
+                outputs=outputs, target_sizes=target_size)[0]
+            detections = sv.Detections.from_transformers(results)
+            sink.append(detections, {"frame_index": frame_index})
+    ```
 
 TODO
 
-## Process Video and Save Detections
+| x_min   | y_min    | x_max   | y_max    | class_id | confidence | tracker_id | class_name | frame_index |
+|---------|----------|---------|----------|----------|------------|------------|------------|-------------|
+| 2941.14 | 1269.31  | 3220.77 | 1500.67  | 2        | 0.8517     |            | car        | 0           |
+| 944.889 | 899.641  | 1235.42 | 1308.80  | 7        | 0.6752     |            | truck      | 0           |
+| 1439.78 | 1077.79  | 1621.27 | 1231.40  | 2        | 0.6450     |            | car        | 0           |
+
+## Save Detections as JSON
 
 TODO
+
+=== "Inference"
+
+    ```{ .py hl_lines="7" }
+    import supervision as sv
+    from inference import get_model
+
+    model = get_model(model_id="yolov8n-640")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    with sv.JSONSink(<TARGET_CSV_PATH>) as sink:
+        for frame_index, frame in enumerate(frames_generator):
+
+            results = model.infer(image)[0]
+            detections = sv.Detections.from_inference(results)
+            sink.append(detections, {"frame_index": frame_index})
+    ```
+
+=== "Ultralytics"
+
+    ```{ .py hl_lines="7" }
+    import supervision as sv
+    from ultralytics import YOLO
+
+    model = YOLO("yolov8n.pt")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    with sv.JSONSink(<TARGET_CSV_PATH>) as sink:
+        for frame_index, frame in enumerate(frames_generator):
+
+            results = model(frame)[0]
+            detections = sv.Detections.from_ultralytics(results)
+            sink.append(detections, {"frame_index": frame_index})
+    ```
+
+=== "Transformers"
+
+    ```{ .py hl_lines="9" }
+    import torch
+    import supervision as sv
+    from transformers import DetrImageProcessor, DetrForObjectDetection
+
+    processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+    frames_generator = sv.get_video_frames_generator(<SOURCE_VIDEO_PATH>)
+
+    with sv.JSONSink(<TARGET_CSV_PATH>) as sink:
+        for frame_index, frame in enumerate(frames_generator):
+
+            frame = sv.cv2_to_pillow(frame)
+            inputs = processor(images=frame, return_tensors="pt")
+
+            with torch.no_grad():
+                outputs = model(**inputs)
+
+            width, height = frame.size
+            target_size = torch.tensor([[height, width]])
+            results = processor.post_process_object_detection(
+                outputs=outputs, target_sizes=target_size)[0]
+            detections = sv.Detections.from_transformers(results)
+            sink.append(detections, {"frame_index": frame_index})
+    ```
\ No newline at end of file

From 99fbd4b601657e7a25ed68a2ae805413788cd1ad Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 20:45:06 +0000
Subject: [PATCH 127/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/save_detections.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/how_to/save_detections.md b/docs/how_to/save_detections.md
index e0233f9b5..5d0dc61a9 100644
--- a/docs/how_to/save_detections.md
+++ b/docs/how_to/save_detections.md
@@ -9,8 +9,8 @@ TODO
 
 ## Run Detection
 
-First, you'll need to obtain predictions from your object detection or segmentation 
-model. You can learn more on this topic in our 
+First, you'll need to obtain predictions from your object detection or segmentation
+model. You can learn more on this topic in our
 [How to Detect and Annotate](/latest/how_to/detect_and_annotate.md) guide.
 
 === "Inference"
@@ -281,4 +281,4 @@ TODO
                 outputs=outputs, target_sizes=target_size)[0]
             detections = sv.Detections.from_transformers(results)
             sink.append(detections, {"frame_index": frame_index})
-    ```
\ No newline at end of file
+    ```

From e0d5f00ae3439bdece59cb1bd8d07ada53d91d78 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 23:15:49 +0200
Subject: [PATCH 128/188] initial version of `How to Save Detections` guide
 done

---
 docs/how_to/save_detections.md | 31 +++++++++++++++++++++++--------
 1 file changed, 23 insertions(+), 8 deletions(-)

diff --git a/docs/how_to/save_detections.md b/docs/how_to/save_detections.md
index e0233f9b5..f432c9398 100644
--- a/docs/how_to/save_detections.md
+++ b/docs/how_to/save_detections.md
@@ -5,7 +5,13 @@ status: new
 
 # Save Detections
 
-TODO
+Supervision enables an easy way to save detections in .CSV and .JSON files for offline 
+processing. This guide demonstrates how to perform video inference using the 
+[Inference](https://github.com/roboflow/inference),
+[Ultralytics](https://github.com/ultralytics/ultralytics) or
+[Transformers](https://github.com/huggingface/transformers) packages and save their results with 
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) and 
+[`sv.JSONSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.JSONSink).
 
 ## Run Detection
 
@@ -71,7 +77,11 @@ model. You can learn more on this topic in our
 
 ## Save Detections as CSV
 
-TODO
+To save detections to a `.CSV` file, open our 
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) 
+and then pass the 
+[`sv.Detections`](/latest/detection/core/#supervision.detection.core.Detections) 
+object resulting from the inference to it. Its fields are parsed and saved on disk.
 
 === "Inference"
 
@@ -135,8 +145,6 @@ TODO
             sink.append(detections, {})
     ```
 
-TODO
-
 | x_min   | y_min    | x_max   | y_max    | class_id | confidence | tracker_id | class_name |
 |---------|----------|---------|----------|----------|------------|------------|------------|
 | 2941.14 | 1269.31  | 3220.77 | 1500.67  | 2        | 0.8517     |            | car        |
@@ -145,7 +153,12 @@ TODO
 
 ## Custom Fields
 
-TODO
+Besides regular fields in 
+[`sv.Detections`](/latest/detection/core/#supervision.detection.core.Detections), 
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) 
+also allows you to add custom information to each row, which can be passed via the 
+`custom_data` dictionary. Let's utilize this feature to save information about the 
+frame index from which the detections originate.
 
 === "Inference"
 
@@ -209,8 +222,6 @@ TODO
             sink.append(detections, {"frame_index": frame_index})
     ```
 
-TODO
-
 | x_min   | y_min    | x_max   | y_max    | class_id | confidence | tracker_id | class_name | frame_index |
 |---------|----------|---------|----------|----------|------------|------------|------------|-------------|
 | 2941.14 | 1269.31  | 3220.77 | 1500.67  | 2        | 0.8517     |            | car        | 0           |
@@ -219,7 +230,11 @@ TODO
 
 ## Save Detections as JSON
 
-TODO
+If you prefer to save the result in a `.JSON` file instead of a `.CSV` file, all you 
+need to do is replace 
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) 
+with 
+[`sv.JSONSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.JSONSink).
 
 === "Inference"
 

From c27d9eaf22cb90efd8f88c91d555e9c32935ece2 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 9 Apr 2024 21:16:18 +0000
Subject: [PATCH 129/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/how_to/save_detections.md | 34 +++++++++++++++++-----------------
 1 file changed, 17 insertions(+), 17 deletions(-)

diff --git a/docs/how_to/save_detections.md b/docs/how_to/save_detections.md
index 2c9250ea6..94de6c618 100644
--- a/docs/how_to/save_detections.md
+++ b/docs/how_to/save_detections.md
@@ -5,12 +5,12 @@ status: new
 
 # Save Detections
 
-Supervision enables an easy way to save detections in .CSV and .JSON files for offline 
-processing. This guide demonstrates how to perform video inference using the 
+Supervision enables an easy way to save detections in .CSV and .JSON files for offline
+processing. This guide demonstrates how to perform video inference using the
 [Inference](https://github.com/roboflow/inference),
 [Ultralytics](https://github.com/ultralytics/ultralytics) or
-[Transformers](https://github.com/huggingface/transformers) packages and save their results with 
-[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) and 
+[Transformers](https://github.com/huggingface/transformers) packages and save their results with
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) and
 [`sv.JSONSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.JSONSink).
 
 ## Run Detection
@@ -77,10 +77,10 @@ model. You can learn more on this topic in our
 
 ## Save Detections as CSV
 
-To save detections to a `.CSV` file, open our 
-[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) 
-and then pass the 
-[`sv.Detections`](/latest/detection/core/#supervision.detection.core.Detections) 
+To save detections to a `.CSV` file, open our
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink)
+and then pass the
+[`sv.Detections`](/latest/detection/core/#supervision.detection.core.Detections)
 object resulting from the inference to it. Its fields are parsed and saved on disk.
 
 === "Inference"
@@ -153,11 +153,11 @@ object resulting from the inference to it. Its fields are parsed and saved on di
 
 ## Custom Fields
 
-Besides regular fields in 
-[`sv.Detections`](/latest/detection/core/#supervision.detection.core.Detections), 
-[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) 
-also allows you to add custom information to each row, which can be passed via the 
-`custom_data` dictionary. Let's utilize this feature to save information about the 
+Besides regular fields in
+[`sv.Detections`](/latest/detection/core/#supervision.detection.core.Detections),
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink)
+also allows you to add custom information to each row, which can be passed via the
+`custom_data` dictionary. Let's utilize this feature to save information about the
 frame index from which the detections originate.
 
 === "Inference"
@@ -230,10 +230,10 @@ frame index from which the detections originate.
 
 ## Save Detections as JSON
 
-If you prefer to save the result in a `.JSON` file instead of a `.CSV` file, all you 
-need to do is replace 
-[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) 
-with 
+If you prefer to save the result in a `.JSON` file instead of a `.CSV` file, all you
+need to do is replace
+[`sv.CSVSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink)
+with
 [`sv.JSONSink`](/latest/detection/tools/save_detections/#supervision.detection.tools.csv_sink.JSONSink).
 
 === "Inference"

From eb1c7716ef0e9835f873133dd41e3ae40c9442df Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 9 Apr 2024 23:18:02 +0200
Subject: [PATCH 130/188] make ruff happy

---
 supervision/utils/image.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/utils/image.py b/supervision/utils/image.py
index 44ccbeac1..9f2e17839 100644
--- a/supervision/utils/image.py
+++ b/supervision/utils/image.py
@@ -320,7 +320,7 @@ def overlay_image(
         ```
 
     ![overlay_image](https://media.roboflow.com/supervision-docs/overlay-image.png){ align=center width="800" }
-    """
+    """  # noqa E501 // docs
     scene_height, scene_width = image.shape[:2]
     image_height, image_width = overlay.shape[:2]
     anchor_x, anchor_y = anchor

From 2fd54521815f0267f746e14782c59916180e8b95 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 10 Apr 2024 00:14:47 +0000
Subject: [PATCH 131/188] :arrow_up: Bump mkdocs-jupyter from 0.24.3 to 0.24.7

Bumps [mkdocs-jupyter](https://github.com/danielfrg/mkdocs-jupyter) from 0.24.3 to 0.24.7.
- [Changelog](https://github.com/danielfrg/mkdocs-jupyter/blob/main/CHANGELOG.md)
- [Commits](https://github.com/danielfrg/mkdocs-jupyter/compare/0.24.3...0.24.7)

---
updated-dependencies:
- dependency-name: mkdocs-jupyter
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 65a9122fe..40e19b9ca 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2162,13 +2162,12 @@ pytz = "*"
 
 [[package]]
 name = "mkdocs-jupyter"
-version = "0.24.3"
+version = "0.24.7"
 description = "Use Jupyter in mkdocs websites"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_jupyter-0.24.3-py3-none-any.whl", hash = "sha256:904262a8678a5e5920b7c3c03b5010b36301a69d0a38f2fcbf430493adf6879e"},
-    {file = "mkdocs_jupyter-0.24.3.tar.gz", hash = "sha256:3d81da9aea27480e93bab22438910c4f0b9630613e74f85b576590d78e0e8b14"},
+    {file = "mkdocs_jupyter-0.24.7-py3-none-any.whl", hash = "sha256:893d04bea1e007479a46e4e72852cd4d280c4d358ce4a0445250f3f80c639723"},
 ]
 
 [package.dependencies]
@@ -2179,9 +2178,6 @@ mkdocs-material = ">9.0.0"
 nbconvert = ">=7.2.9,<8"
 pygments = ">2.12.0"
 
-[package.extras]
-test = ["coverage[toml]", "pymdown-extensions", "pytest", "pytest-cov"]
-
 [[package]]
 name = "mkdocs-material"
 version = "9.5.17"

From 98b64f5e7d23386a78017522fb35ea10207570cf Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 10 Apr 2024 09:34:44 +0300
Subject: [PATCH 132/188] Add beach drone footage asset

---
 supervision/assets/list.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/supervision/assets/list.py b/supervision/assets/list.py
index 83518cdbb..77b1e461a 100644
--- a/supervision/assets/list.py
+++ b/supervision/assets/list.py
@@ -18,6 +18,7 @@ class VideoAssets(Enum):
     | `SUBWAY`               | `subway.mp4`               | [Link](https://media.roboflow.com/supervision/video-examples/subway.mp4)              |
     | `MARKET_SQUARE`        | `market-square.mp4`        | [Link](https://media.roboflow.com/supervision/video-examples/market-square.mp4)       |
     | `PEOPLE_WALKING`       | `people-walking.mp4`       | [Link](https://media.roboflow.com/supervision/video-examples/people-walking.mp4)      |
+    | `BEACH`                | `beach-1.mp4`              | [Link](https://media.roboflow.com/supervision/video-examples/beach-1.mp4)             |
     """  # noqa: E501 // docs
 
     VEHICLES = "vehicles.mp4"
@@ -27,6 +28,7 @@ class VideoAssets(Enum):
     SUBWAY = "subway.mp4"
     MARKET_SQUARE = "market-square.mp4"
     PEOPLE_WALKING = "people-walking.mp4"
+    BEACH = "beach-1.mp4"
 
     @classmethod
     def list(cls):
@@ -62,4 +64,8 @@ def list(cls):
         f"{BASE_VIDEO_URL}{VideoAssets.PEOPLE_WALKING.value}",
         "0574c053c8686c3f1dc0aa3743e45cb9",
     ),
+    VideoAssets.BEACH.value: (
+        f"{BASE_VIDEO_URL}{VideoAssets.BEACH.value}",
+        "4175d42fec4d450ed081523fd39e0cf8",
+    ),
 }

From ed225187b248dad4dbcebc6385508a561d70a629 Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Thu, 11 Apr 2024 14:09:02 +0200
Subject: [PATCH 133/188] Update README.md

---
 README.md | 20 ++++++++++++--------
 1 file changed, 12 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 7d280b575..beed655c9 100644
--- a/README.md
+++ b/README.md
@@ -217,19 +217,23 @@ len(dataset)
 
 ## 🎬 tutorials
 
+Want to learn how to use Supervision? Explore our [how-to guides](https://supervision.roboflow.com/develop/how_to/detect_and_annotate/), [end-to-end examples](https://github.com/roboflow/supervision/tree/develop/examples), and [cookbooks](https://supervision.roboflow.com/develop/cookbooks/)!
+
+<br/>
+
 <p align="left">
-<a href="https://youtu.be/uWP6UjDeZvY" title="Speed Estimation & Vehicle Tracking | Computer Vision | Open Source"><img src="https://github.com/SkalskiP/SkalskiP/assets/26109316/61a444c8-b135-48ce-b979-2a5ab47c5a91" alt="Speed Estimation & Vehicle Tracking | Computer Vision | Open Source" width="300px" align="left" /></a>
-<a href="https://youtu.be/uWP6UjDeZvY" title="Speed Estimation & Vehicle Tracking | Computer Vision | Open Source"><strong>Speed Estimation & Vehicle Tracking | Computer Vision | Open Source</strong></a>
-<div><strong>Created: 11 Jan 2024</strong> | <strong>Updated: 11 Jan 2024</strong></div>
-<br/> Learn how to track and estimate the speed of vehicles using YOLO, ByteTrack, and Roboflow Inference. This comprehensive tutorial covers object detection, multi-object tracking, filtering detections, perspective transformation, speed estimation, visualization improvements, and more.</p>
+<a href="https://youtu.be/hAWpsIuem10" title="Dwell Time Analysis with Computer Vision | Real-Time Stream Processing"><img src="https://github.com/SkalskiP/SkalskiP/assets/26109316/a742823d-c158-407d-b30f-063a5d11b4e1" alt="Dwell Time Analysis with Computer Vision | Real-Time Stream Processing" width="300px" align="left" /></a>
+<a href="https://youtu.be/hAWpsIuem10" title="Dwell Time Analysis with Computer Vision | Real-Time Stream Processing"><strong>Dwell Time Analysis with Computer Vision | Real-Time Stream Processing</strong></a>
+<div><strong>Created: 5 Apr 2024</strong></div>
+<br/>Learn how to use computer vision to analyze wait times and optimize processes. This tutorial covers object detection, tracking, and calculating time spent in designated zones. Use these techniques to improve customer experience in retail, traffic management, or other scenarios.</p>
 
 <br/>
 
 <p align="left">
-<a href="https://youtu.be/4Q3ut7vqD5o" title="Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking"><img src="https://github.com/roboflow/supervision/assets/26109316/54afdf1c-218c-4451-8f12-627fb85f1682" alt="Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking" width="300px" align="left" /></a>
-<a href="https://youtu.be/4Q3ut7vqD5o" title="Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking"><strong>Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking</strong></a>
-<div><strong>Created: 6 Sep 2023</strong> | <strong>Updated: 6 Sep 2023</strong></div>
-<br/> In this video, we explore real-time traffic analysis using YOLOv8 and ByteTrack to detect and track vehicles on aerial images. Harnessing the power of Python and Supervision, we delve deep into assigning cars to specific entry zones and understanding their direction of movement. By visualizing their paths, we gain insights into traffic flow across bustling roundabouts... </p>
+<a href="https://youtu.be/uWP6UjDeZvY" title="Speed Estimation & Vehicle Tracking | Computer Vision | Open Source"><img src="https://github.com/SkalskiP/SkalskiP/assets/26109316/61a444c8-b135-48ce-b979-2a5ab47c5a91" alt="Speed Estimation & Vehicle Tracking | Computer Vision | Open Source" width="300px" align="left" /></a>
+<a href="https://youtu.be/uWP6UjDeZvY" title="Speed Estimation & Vehicle Tracking | Computer Vision | Open Source"><strong>Speed Estimation & Vehicle Tracking | Computer Vision | Open Source</strong></a>
+<div><strong>Created: 11 Jan 2024</strong></div>
+<br/>Learn how to track and estimate the speed of vehicles using YOLO, ByteTrack, and Roboflow Inference. This comprehensive tutorial covers object detection, multi-object tracking, filtering detections, perspective transformation, speed estimation, visualization improvements, and more.</p>
 
 ## 💜 built with supervision
 

From 263421d145d2d5836714365b59e537e75f21ee30 Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Thu, 11 Apr 2024 14:40:43 +0200
Subject: [PATCH 134/188] Update README.md

---
 examples/README.md | 26 +++-----------------------
 1 file changed, 3 insertions(+), 23 deletions(-)

diff --git a/examples/README.md b/examples/README.md
index 81c8054b9..b723a2470 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -1,8 +1,8 @@
 # Examples
 
-This repository is packed with real-world use-cases, provided through Python scripts or
-interactive notebooks. Browse through to understand how the Supervision library
-interfaces with diverse applications.
+Here, you'll find end-to-end examples that show how to solve common computer vision problems using Supervision.
+
+For more information and examples, visit our [documentation](https://supervision.roboflow.com/develop/annotators/) and explore our [how-to guides](https://supervision.roboflow.com/develop/how_to/detect_and_annotate/) and [cookbooks](https://supervision.roboflow.com/develop/cookbooks/). Join our [Discord](https://discord.com/invite/GbfgXGJ8Bk) and meet other Supervision power users!
 
 - [tracking](./tracking) by [@SkalskiP](https://github.com/SkalskiP)
 - [count people in zone](./count_people_in_zone) by [@SkalskiP](https://github.com/SkalskiP)
@@ -10,23 +10,3 @@ interfaces with diverse applications.
 - [speed estimation](./speed_estimation) by [@SkalskiP](https://github.com/SkalskiP)
 - [time in zone](./time_in_zone) by [@SkalskiP](https://github.com/SkalskiP)
 - [heatmap and track](./heatmap_and_track/) by [@HinePo](https://github.com/HinePo)
-
-## Contributing
-
-We welcome contributions from the community in the form of examples, applications, and
-guides. To contribute, please follow these steps:
-
-1. Create a pull request (PR) with the `[Example]` prefix in the title, adding your
-project folder to the `examples/` directory in the repository.
-2. Confirm your project aligns with the following standards:
-   - Incorporates the `supervision` package.
-   - Provides a `README.md` file, detailing the instructions to execute the project.
-   - Showcases visual results, demonstrating the app's functionality.
-   - Avoids adding large assets or dependencies unless absolutely necessary.
-   - The contributor is expected to provide support for issues related to their
-examples.
-   - In case the presented model has licensing complications, kindly specify them to
-circumvent potential misunderstandings.
-
-For inquiries or concerns about these prerequisites, feel free to raise a PR. We are
-committed to assist and guide you.

From 9284bfdcd900f4ebe4b30f375c0f1d4de2ef2b41 Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Thu, 11 Apr 2024 14:44:50 +0200
Subject: [PATCH 135/188] Update README.md

---
 examples/count_people_in_zone/README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/examples/count_people_in_zone/README.md b/examples/count_people_in_zone/README.md
index 2e14a80b4..d9d3cdb20 100644
--- a/examples/count_people_in_zone/README.md
+++ b/examples/count_people_in_zone/README.md
@@ -1,5 +1,8 @@
 # count people in zone
 
+[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/how-to-detect-and-count-objects-in-polygon-zone.ipynb)
+[![YouTube](https://badges.aleen42.com/src/youtube.svg)](https://www.youtube.com/watch?v=l_kf9CfZ_8M)
+
 ## 👋 hello
 
 This demo is a video analysis tool that counts and highlights objects in specific zones

From d3dbe7c59780307dec01ebb302f0f5762eaa3241 Mon Sep 17 00:00:00 2001
From: Piotr Skalski <piotr.skalski92@gmail.com>
Date: Thu, 11 Apr 2024 14:54:22 +0200
Subject: [PATCH 136/188] Update README.md

---
 examples/time_in_zone/README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/examples/time_in_zone/README.md b/examples/time_in_zone/README.md
index 2bfd6c7af..985879992 100644
--- a/examples/time_in_zone/README.md
+++ b/examples/time_in_zone/README.md
@@ -1,5 +1,7 @@
 # time in zone
 
+[![YouTube](https://badges.aleen42.com/src/youtube.svg)](https://www.youtube.com/watch?v=hAWpsIuem10)
+
 ## 👋 hello
 
 Practical demonstration on leveraging computer vision for analyzing wait times and

From b7607c6f152d73ee5556c67bdb6ff94b54d29847 Mon Sep 17 00:00:00 2001
From: Jeslin P James <jeslinpjames007@gmail.com>
Date: Thu, 11 Apr 2024 18:57:30 +0530
Subject: [PATCH 137/188] Updated PolyZone class to compute frame_resolution_wh
 based on polygon coordinates

---
 supervision/detection/tools/polygon_zone.py | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index 00b746aaa..f4825125a 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -2,6 +2,7 @@
 from typing import Iterable, Optional, Tuple
 
 import cv2
+import warnings
 import numpy as np
 import numpy.typing as npt
 
@@ -11,7 +12,7 @@
 from supervision.draw.utils import draw_polygon, draw_text
 from supervision.geometry.core import Position
 from supervision.geometry.utils import get_polygon_center
-from supervision.utils.internal import deprecated_parameter
+from supervision.utils.internal import deprecated_parameter, SupervisionWarnings
 
 
 class PolygonZone:
@@ -41,18 +42,24 @@ class PolygonZone:
     def __init__(
         self,
         polygon: npt.NDArray[np.int64],
-        frame_resolution_wh: Tuple[int, int],
         triggering_anchors: Iterable[Position] = (Position.BOTTOM_CENTER,),
+        frame_resolution_wh: Optional[Tuple[int, int]] = None,
     ):
+        if frame_resolution_wh is not None:
+            warnings.warn(
+                  "The `frame_resolution_wh` parameter is no longer required and will be dropped in version supervision-0.24.0. The mask resolution is now calculated automatically based on the polygon coordinates.",
+                  category=SupervisionWarnings,
+              )
+
         self.polygon = polygon.astype(int)
-        self.frame_resolution_wh = frame_resolution_wh
         self.triggering_anchors = triggering_anchors
 
         self.current_count = 0
 
-        width, height = frame_resolution_wh
+        x_max, y_max = np.max(polygon, axis=0)
+        self.frame_resolution_wh = (x_max , y_max)
         self.mask = polygon_to_mask(
-            polygon=polygon, resolution_wh=(width + 1, height + 1)
+            polygon=polygon, resolution_wh=(x_max + 1, y_max + 1)
         )
 
     def trigger(self, detections: Detections) -> npt.NDArray[np.bool_]:

From 28baf18cb6dcd6005fa030e35390028adfe350e8 Mon Sep 17 00:00:00 2001
From: Jeslin P James <jeslinpjames007@gmail.com>
Date: Thu, 11 Apr 2024 18:59:48 +0530
Subject: [PATCH 138/188] updated PolygonZone Attributes docs

---
 supervision/detection/tools/polygon_zone.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index f4825125a..72306e7e9 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -22,13 +22,16 @@ class PolygonZone:
     Attributes:
         polygon (np.ndarray): A polygon represented by a numpy array of shape
             `(N, 2)`, containing the `x`, `y` coordinates of the points.
-        frame_resolution_wh (Tuple[int, int]): The frame resolution (width, height)
         triggering_anchors (Iterable[sv.Position]): A list of positions specifying
             which anchors of the detections bounding box to consider when deciding on
             whether the detection fits within the PolygonZone
             (default: (sv.Position.BOTTOM_CENTER,)).
         current_count (int): The current count of detected objects within the zone
         mask (np.ndarray): The 2D bool mask for the polygon zone
+        frame_resolution_wh (Optional[Tuple[int, int]], optional): DEPRECATED. The frame resolution
+                (width, height). This parameter is no longer required and will be dropped in version
+                supervision-0.24.0. The mask resolution is now calculated automatically based on the
+                polygon coordinates. Defaults to None.
     """
 
     @deprecated_parameter(

From b64c61c3885fdd449e0dfae9080c1c6073c75aed Mon Sep 17 00:00:00 2001
From: Jeslin P James <jeslinpjames007@gmail.com>
Date: Thu, 11 Apr 2024 19:04:06 +0530
Subject: [PATCH 139/188] formated code

---
 supervision/detection/tools/polygon_zone.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index 72306e7e9..ccc6ec95c 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -50,9 +50,10 @@ def __init__(
     ):
         if frame_resolution_wh is not None:
             warnings.warn(
-                  "The `frame_resolution_wh` parameter is no longer required and will be dropped in version supervision-0.24.0. The mask resolution is now calculated automatically based on the polygon coordinates.",
-                  category=SupervisionWarnings,
-              )
+                "The `frame_resolution_wh` parameter is no longer required and will be dropped in version "
+                "supervision-0.24.0. The mask resolution is now calculated automatically based on the polygon coordinates.",
+                category=SupervisionWarnings,
+            )
 
         self.polygon = polygon.astype(int)
         self.triggering_anchors = triggering_anchors
@@ -60,7 +61,7 @@ def __init__(
         self.current_count = 0
 
         x_max, y_max = np.max(polygon, axis=0)
-        self.frame_resolution_wh = (x_max , y_max)
+        self.frame_resolution_wh = (x_max, y_max)
         self.mask = polygon_to_mask(
             polygon=polygon, resolution_wh=(x_max + 1, y_max + 1)
         )
@@ -100,6 +101,7 @@ def trigger(self, detections: Detections) -> npt.NDArray[np.bool_]:
         return is_in_zone.astype(bool)
 
 
+
 class PolygonZoneAnnotator:
     """
     A class for annotating a polygon-shaped zone within a

From 743e42080bcc4ba60ff7ffda03f8c50e52a6edfc Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 11 Apr 2024 13:57:48 +0000
Subject: [PATCH 140/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/tools/polygon_zone.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index ccc6ec95c..f78bd609b 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -1,8 +1,8 @@
+import warnings
 from dataclasses import replace
 from typing import Iterable, Optional, Tuple
 
 import cv2
-import warnings
 import numpy as np
 import numpy.typing as npt
 
@@ -12,7 +12,7 @@
 from supervision.draw.utils import draw_polygon, draw_text
 from supervision.geometry.core import Position
 from supervision.geometry.utils import get_polygon_center
-from supervision.utils.internal import deprecated_parameter, SupervisionWarnings
+from supervision.utils.internal import SupervisionWarnings, deprecated_parameter
 
 
 class PolygonZone:
@@ -101,7 +101,6 @@ def trigger(self, detections: Detections) -> npt.NDArray[np.bool_]:
         return is_in_zone.astype(bool)
 
 
-
 class PolygonZoneAnnotator:
     """
     A class for annotating a polygon-shaped zone within a

From 7126adc74a38d080c430af76643af249d5a624b9 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 12 Apr 2024 00:13:05 +0000
Subject: [PATCH 141/188] :arrow_up: Bump ruff from 0.3.5 to 0.3.6

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.3.5 to 0.3.6.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.3.5...v0.3.6)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 40e19b9ca..3bd87ec36 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3643,28 +3643,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.3.5"
+version = "0.3.6"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "ruff-0.3.5-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:aef5bd3b89e657007e1be6b16553c8813b221ff6d92c7526b7e0227450981eac"},
-    {file = "ruff-0.3.5-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:89b1e92b3bd9fca249153a97d23f29bed3992cff414b222fcd361d763fc53f12"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5e55771559c89272c3ebab23326dc23e7f813e492052391fe7950c1a5a139d89"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:dabc62195bf54b8a7876add6e789caae0268f34582333cda340497c886111c39"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3a05f3793ba25f194f395578579c546ca5d83e0195f992edc32e5907d142bfa3"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:dfd3504e881082959b4160ab02f7a205f0fadc0a9619cc481982b6837b2fd4c0"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:87258e0d4b04046cf1d6cc1c56fadbf7a880cc3de1f7294938e923234cf9e498"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:712e71283fc7d9f95047ed5f793bc019b0b0a29849b14664a60fd66c23b96da1"},
-    {file = "ruff-0.3.5-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a532a90b4a18d3f722c124c513ffb5e5eaff0cc4f6d3aa4bda38e691b8600c9f"},
-    {file = "ruff-0.3.5-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:122de171a147c76ada00f76df533b54676f6e321e61bd8656ae54be326c10296"},
-    {file = "ruff-0.3.5-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:d80a6b18a6c3b6ed25b71b05eba183f37d9bc8b16ace9e3d700997f00b74660b"},
-    {file = "ruff-0.3.5-py3-none-musllinux_1_2_i686.whl", hash = "sha256:a7b6e63194c68bca8e71f81de30cfa6f58ff70393cf45aab4c20f158227d5936"},
-    {file = "ruff-0.3.5-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:a759d33a20c72f2dfa54dae6e85e1225b8e302e8ac655773aff22e542a300985"},
-    {file = "ruff-0.3.5-py3-none-win32.whl", hash = "sha256:9d8605aa990045517c911726d21293ef4baa64f87265896e491a05461cae078d"},
-    {file = "ruff-0.3.5-py3-none-win_amd64.whl", hash = "sha256:dc56bb16a63c1303bd47563c60482a1512721053d93231cf7e9e1c6954395a0e"},
-    {file = "ruff-0.3.5-py3-none-win_arm64.whl", hash = "sha256:faeeae9905446b975dcf6d4499dc93439b131f1443ee264055c5716dd947af55"},
-    {file = "ruff-0.3.5.tar.gz", hash = "sha256:a067daaeb1dc2baf9b82a32dae67d154d95212080c80435eb052d95da647763d"},
+    {file = "ruff-0.3.6-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:732ef99984275534f9466fbc01121523caf72aa8c2bdeb36fd2edf2bc294a992"},
+    {file = "ruff-0.3.6-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:93699d61116807edc5ca1cdf9d2d22cf8d93335d59e3ff0ca7aee62c1818a736"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc4006cbc6c11fefc25f122d2eb4731d7a3d815dc74d67c54991cc3f99c90177"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:878ef1a55ce931f3ca23b690b159cd0659f495a4c231a847b00ca55e4c688baf"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ecb87788284af96725643eae9ab3ac746d8cc09aad140268523b019f7ac3cd98"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:b2e79f8e1b6bd5411d7ddad3f2abff3f9d371beda29daef86400d416dedb7e02"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cf48ec2c4bfae7837dc325c431a2932dc23a1485e71c59591c1df471ba234e0e"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c466a52c522e6a08df0af018f550902f154f5649ad09e7f0d43da766e7399ebc"},
+    {file = "ruff-0.3.6-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:28ccf3fb6d1162a73cd286c63a5e4d885f46a1f99f0b392924bc95ccbd18ea8f"},
+    {file = "ruff-0.3.6-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:b11e09439d9df6cc12d9f622065834654417c40216d271f639512d80e80e3e53"},
+    {file = "ruff-0.3.6-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:647f1fb5128a3e24ce68878b8050bb55044c45bb3f3ae4710d4da9ca96ede5cb"},
+    {file = "ruff-0.3.6-py3-none-musllinux_1_2_i686.whl", hash = "sha256:2b0c4c70578ef1871a9ac5c85ed7a8c33470e976c73ba9211a111d2771b5f787"},
+    {file = "ruff-0.3.6-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:e3da499ded004d0b956ab04248b2ae17e54a67ffc81353514ac583af5959a255"},
+    {file = "ruff-0.3.6-py3-none-win32.whl", hash = "sha256:4056480f5cf38ad278667c31b0ef334c29acdfcea617cb89c4ccbc7d96f1637f"},
+    {file = "ruff-0.3.6-py3-none-win_amd64.whl", hash = "sha256:f1aa621beed533f46e9c7d6fe00e7f6e4570155b61d8f020387b72ace2b42e04"},
+    {file = "ruff-0.3.6-py3-none-win_arm64.whl", hash = "sha256:7c8a2a0e0cab077a07465259ffe3b3c090e747ca8097c5dc4c36ca0fdaaac90d"},
+    {file = "ruff-0.3.6.tar.gz", hash = "sha256:26071fb530038602b984e3bbe1443ef82a38450c4dcb1344a9caf67234ff9756"},
 ]
 
 [[package]]

From 89d84d1f7437bb9561ef2527fea5dac4770e2d53 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 12 Apr 2024 04:14:49 +0000
Subject: [PATCH 142/188] :arrow_up: Bump idna from 3.6 to 3.7

Bumps [idna](https://github.com/kjd/idna) from 3.6 to 3.7.
- [Release notes](https://github.com/kjd/idna/releases)
- [Changelog](https://github.com/kjd/idna/blob/master/HISTORY.rst)
- [Commits](https://github.com/kjd/idna/compare/v3.6...v3.7)

---
updated-dependencies:
- dependency-name: idna
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 40e19b9ca..932c51bc9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1122,13 +1122,13 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.6"
+version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
-    {file = "idna-3.6-py3-none-any.whl", hash = "sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f"},
-    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
+    {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"},
+    {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"},
 ]
 
 [[package]]

From 510df5457255aa70cdb8a8daa24aedaa624d9dd9 Mon Sep 17 00:00:00 2001
From: Jeslin P James <jeslinpjames007@gmail.com>
Date: Fri, 12 Apr 2024 16:16:48 +0530
Subject: [PATCH 143/188] Updated order of parameters in PolygonZone __init__()

---
 supervision/detection/tools/polygon_zone.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index ccc6ec95c..fa71b1243 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -1,8 +1,8 @@
+import warnings
 from dataclasses import replace
 from typing import Iterable, Optional, Tuple
 
 import cv2
-import warnings
 import numpy as np
 import numpy.typing as npt
 
@@ -12,7 +12,7 @@
 from supervision.draw.utils import draw_polygon, draw_text
 from supervision.geometry.core import Position
 from supervision.geometry.utils import get_polygon_center
-from supervision.utils.internal import deprecated_parameter, SupervisionWarnings
+from supervision.utils.internal import SupervisionWarnings, deprecated_parameter
 
 
 class PolygonZone:
@@ -45,8 +45,8 @@ class PolygonZone:
     def __init__(
         self,
         polygon: npt.NDArray[np.int64],
-        triggering_anchors: Iterable[Position] = (Position.BOTTOM_CENTER,),
         frame_resolution_wh: Optional[Tuple[int, int]] = None,
+        triggering_anchors: Iterable[Position] = (Position.BOTTOM_CENTER,),
     ):
         if frame_resolution_wh is not None:
             warnings.warn(
@@ -101,7 +101,6 @@ def trigger(self, detections: Detections) -> npt.NDArray[np.bool_]:
         return is_in_zone.astype(bool)
 
 
-
 class PolygonZoneAnnotator:
     """
     A class for annotating a polygon-shaped zone within a

From 0ad3796571e04b3435d1a31d4adec483a18412e0 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 12 Apr 2024 16:13:09 +0200
Subject: [PATCH 144/188] bug fix

---
 supervision/detection/tools/polygon_zone.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index fa71b1243..244b793b8 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -61,9 +61,9 @@ def __init__(
         self.current_count = 0
 
         x_max, y_max = np.max(polygon, axis=0)
-        self.frame_resolution_wh = (x_max, y_max)
+        self.frame_resolution_wh = (x_max + 1, y_max + 1)
         self.mask = polygon_to_mask(
-            polygon=polygon, resolution_wh=(x_max + 1, y_max + 1)
+            polygon=polygon, resolution_wh=(x_max + 2, y_max + 2)
         )
 
     def trigger(self, detections: Detections) -> npt.NDArray[np.bool_]:

From 2c62f0b26dfdac73ce941e425c2325ad87f2499b Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 12 Apr 2024 16:15:10 +0200
Subject: [PATCH 145/188] drop `frame_resolution_wh` from docs

---
 supervision/detection/tools/polygon_zone.py | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index 244b793b8..561cb9ced 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -28,10 +28,6 @@ class PolygonZone:
             (default: (sv.Position.BOTTOM_CENTER,)).
         current_count (int): The current count of detected objects within the zone
         mask (np.ndarray): The 2D bool mask for the polygon zone
-        frame_resolution_wh (Optional[Tuple[int, int]], optional): DEPRECATED. The frame resolution
-                (width, height). This parameter is no longer required and will be dropped in version
-                supervision-0.24.0. The mask resolution is now calculated automatically based on the
-                polygon coordinates. Defaults to None.
     """
 
     @deprecated_parameter(

From dfd9fc8e6d696eec671445136b8a50a5c2c901bd Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Fri, 12 Apr 2024 16:17:29 +0200
Subject: [PATCH 146/188] fix too long string

---
 supervision/detection/tools/polygon_zone.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index 561cb9ced..a19972127 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -46,8 +46,9 @@ def __init__(
     ):
         if frame_resolution_wh is not None:
             warnings.warn(
-                "The `frame_resolution_wh` parameter is no longer required and will be dropped in version "
-                "supervision-0.24.0. The mask resolution is now calculated automatically based on the polygon coordinates.",
+                "The `frame_resolution_wh` parameter is no longer required and will be "
+                "dropped in version supervision-0.24.0. The mask resolution is now "
+                "calculated automatically based on the polygon coordinates.",
                 category=SupervisionWarnings,
             )
 

From 77d3276ad6a94dcbd728254153f3741397fc33aa Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 15 Apr 2024 01:13:38 +0000
Subject: [PATCH 147/188] :arrow_up: Bump ruff from 0.3.6 to 0.3.7

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.3.6 to 0.3.7.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.3.6...v0.3.7)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 7910b9f67..76edc310f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3643,28 +3643,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.3.6"
+version = "0.3.7"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "ruff-0.3.7-py3-none-win_amd64.whl", hash = "sha256:5ef0e501e1e39f35e03c2acb1d1238c595b8bb36cf7a170e7c1df1b73da00e74"},
+    {file = "ruff-0.3.7-py3-none-win_arm64.whl", hash = "sha256:789e144f6dc7019d1f92a812891c645274ed08af6037d11fc65fcbc183b7d59f"},
+    {file = "ruff-0.3.7.tar.gz", hash = "sha256:d5c1aebee5162c2226784800ae031f660c350e7a3402c4d1f8ea4e97e232e3ba"},
 ]
 
 [[package]]

From 2af86e56f09c675db2f89471c60abe17d040a3c3 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 15 Apr 2024 17:52:01 +0000
Subject: [PATCH 148/188] =?UTF-8?q?chore(pre=5Fcommit):=20=E2=AC=86=20pre?=
 =?UTF-8?q?=5Fcommit=20autoupdate?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.3.5 → v0.3.7](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.5...v0.3.7)
---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 4c2b1a7ed..b016ca8d6 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -45,7 +45,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.3.5
+      rev: v0.3.7
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

From b3f022b15abc5644aa122a8ddfd527ef99f1bb0d Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 17 Apr 2024 00:29:27 +0000
Subject: [PATCH 149/188] :arrow_up: Bump mkdocs-material from 9.5.17 to 9.5.18

Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 9.5.17 to 9.5.18.
- [Release notes](https://github.com/squidfunk/mkdocs-material/releases)
- [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG)
- [Commits](https://github.com/squidfunk/mkdocs-material/compare/9.5.17...9.5.18)

---
updated-dependencies:
- dependency-name: mkdocs-material
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 76edc310f..b5ce75b4c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2180,13 +2180,13 @@ pygments = ">2.12.0"
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.17"
+version = "9.5.18"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.17-py3-none-any.whl", hash = "sha256:14a2a60119a785e70e765dd033e6211367aca9fc70230e577c1cf6a326949571"},
-    {file = "mkdocs_material-9.5.17.tar.gz", hash = "sha256:06ae1275a72db1989cf6209de9e9ecdfbcfdbc24c58353877b2bb927dbe413e4"},
+    {file = "mkdocs_material-9.5.18-py3-none-any.whl", hash = "sha256:1e0e27fc9fe239f9064318acf548771a4629d5fd5dfd45444fd80a953fe21eb4"},
+    {file = "mkdocs_material-9.5.18.tar.gz", hash = "sha256:a43f470947053fa2405c33995f282d24992c752a50114f23f30da9d8d0c57e62"},
 ]
 
 [package.dependencies]

From 53eb76922de4783c41502e41c967d1fb30efdd8a Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 18 Apr 2024 00:42:40 +0000
Subject: [PATCH 150/188] :arrow_up: Bump notebook from 7.1.2 to 7.1.3

Bumps [notebook](https://github.com/jupyter/notebook) from 7.1.2 to 7.1.3.
- [Release notes](https://github.com/jupyter/notebook/releases)
- [Changelog](https://github.com/jupyter/notebook/blob/@jupyter-notebook/tree@7.1.3/CHANGELOG.md)
- [Commits](https://github.com/jupyter/notebook/compare/@jupyter-notebook/tree@7.1.2...@jupyter-notebook/tree@7.1.3)

---
updated-dependencies:
- dependency-name: notebook
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 76edc310f..33e1f9351 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2466,13 +2466,13 @@ setuptools = "*"
 
 [[package]]
 name = "notebook"
-version = "7.1.2"
+version = "7.1.3"
 description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "notebook-7.1.2-py3-none-any.whl", hash = "sha256:fc6c24b9aef18d0cd57157c9c47e95833b9b0bdc599652639acf0bdb61dc7d5f"},
-    {file = "notebook-7.1.2.tar.gz", hash = "sha256:efc2c80043909e0faa17fce9e9b37c059c03af0ec99a4d4db84cb21d9d2e936a"},
+    {file = "notebook-7.1.3-py3-none-any.whl", hash = "sha256:919b911e59f41f6e3857ce93c9d93535ba66bb090059712770e5968c07e1004d"},
+    {file = "notebook-7.1.3.tar.gz", hash = "sha256:41fcebff44cf7bb9377180808bcbae066629b55d8c7722f1ebbe75ca44f9cfc1"},
 ]
 
 [package.dependencies]

From a1a66e7078fb32e5c4eba0ffa755d3a39c068e32 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 19 Apr 2024 00:17:17 +0000
Subject: [PATCH 151/188] :arrow_up: Bump ruff from 0.3.7 to 0.4.0

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.3.7 to 0.4.0.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.3.7...v0.4.0)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index ed0facf03..04cb6e95f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3643,28 +3643,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.3.7"
+version = "0.4.0"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "ruff-0.4.0-py3-none-musllinux_1_2_i686.whl", hash = "sha256:0b20e7db4a672495320a8a18149b7febf4e4f97509a4657367144569ce0915fd"},
+    {file = "ruff-0.4.0-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:0b0eddd339e24dc4f7719b1cde4967f6b6bc0ad948cc183711ba8910f14aeafe"},
+    {file = "ruff-0.4.0-py3-none-win32.whl", hash = "sha256:e70befd488271a2c28c80bd427f73d8855dd222fc549fa1e9967d287c5cfe781"},
+    {file = "ruff-0.4.0-py3-none-win_amd64.whl", hash = "sha256:8584b9361900997ccf8d7aaa4dc4ab43e258a853ca7189d98ac929dc9ee50875"},
+    {file = "ruff-0.4.0-py3-none-win_arm64.whl", hash = "sha256:fea4ec813c965e40af29ee627a1579ee1d827d77e81d54b85bdd7b42d1540cdd"},
+    {file = "ruff-0.4.0.tar.gz", hash = "sha256:7457308d9ebf00d6a1c9a26aa755e477787a636c90b823f91cd7d4bea9e89260"},
 ]
 
 [[package]]

From 98493c2ae1d15ee773f22b98a517101394d7769a Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 22 Apr 2024 00:45:54 +0000
Subject: [PATCH 152/188] :arrow_up: Bump ruff from 0.4.0 to 0.4.1

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.4.0 to 0.4.1.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/v0.4.0...v0.4.1)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 poetry.lock | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 04cb6e95f..95cbef017 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -3643,28 +3643,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.4.0"
+version = "0.4.1"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "ruff-0.4.0-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:70b8c620cf2212744eabd6d69c4f839f2be0d8880d27beaeb0adb6aa0b316aa8"},
-    {file = "ruff-0.4.0-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:cfa3e3ff53be05a8c5570c1585ea1e089f6b399ca99fcb78598d4a8234f248db"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5616cca501d1d16b932b7e607d7e1fd1b8c8c51d6ee484b7940fc1adc5bea541"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:46eff08dd480b5d9b540846159fe134d70e3c45a3c913c600047cbf7f0e4e308"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2d546f511431fff2b17adcf7110f3b2c2c0c8d33b0e10e5fd27fd340bc617efc"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:c7b6b6b38e216036284c5779b6aa14acbf5664e3b5872533219cf93daf40ddfb"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5e1cf8b064bb2a6b4922af7274fe2dffcb552d96ba716b2fbe5e2c970ed7de18"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9911c9046b94253e1fa844c0192bb764b86866a881502dee324686474d498c17"},
-    {file = "ruff-0.4.0-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ca7a971c8f1a0b6f5ff4a819c0d1c2619536530bbd5a289af725d8b2ef1013d"},
-    {file = "ruff-0.4.0-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:752e0f77f421141dd470a0b1bed4fd8f763aebabe32c80ed3580f740ef4ba807"},
-    {file = "ruff-0.4.0-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:84f2a5dd8f33964d826c5377e094f7ce11e55e432cd42d3bf64efe4384224a03"},
-    {file = "ruff-0.4.0-py3-none-musllinux_1_2_i686.whl", hash = "sha256:0b20e7db4a672495320a8a18149b7febf4e4f97509a4657367144569ce0915fd"},
-    {file = "ruff-0.4.0-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:0b0eddd339e24dc4f7719b1cde4967f6b6bc0ad948cc183711ba8910f14aeafe"},
-    {file = "ruff-0.4.0-py3-none-win32.whl", hash = "sha256:e70befd488271a2c28c80bd427f73d8855dd222fc549fa1e9967d287c5cfe781"},
-    {file = "ruff-0.4.0-py3-none-win_amd64.whl", hash = "sha256:8584b9361900997ccf8d7aaa4dc4ab43e258a853ca7189d98ac929dc9ee50875"},
-    {file = "ruff-0.4.0-py3-none-win_arm64.whl", hash = "sha256:fea4ec813c965e40af29ee627a1579ee1d827d77e81d54b85bdd7b42d1540cdd"},
-    {file = "ruff-0.4.0.tar.gz", hash = "sha256:7457308d9ebf00d6a1c9a26aa755e477787a636c90b823f91cd7d4bea9e89260"},
+    {file = "ruff-0.4.1-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:2d9ef6231e3fbdc0b8c72404a1a0c46fd0dcea84efca83beb4681c318ea6a953"},
+    {file = "ruff-0.4.1-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:9485f54a7189e6f7433e0058cf8581bee45c31a25cd69009d2a040d1bd4bfaef"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d2921ac03ce1383e360e8a95442ffb0d757a6a7ddd9a5be68561a671e0e5807e"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eec8d185fe193ad053eda3a6be23069e0c8ba8c5d20bc5ace6e3b9e37d246d3f"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:baa27d9d72a94574d250f42b7640b3bd2edc4c58ac8ac2778a8c82374bb27984"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:f1ee41580bff1a651339eb3337c20c12f4037f6110a36ae4a2d864c52e5ef954"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0926cefb57fc5fced629603fbd1a23d458b25418681d96823992ba975f050c2b"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2c6e37f2e3cd74496a74af9a4fa67b547ab3ca137688c484749189bf3a686ceb"},
+    {file = "ruff-0.4.1-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efd703a5975ac1998c2cc5e9494e13b28f31e66c616b0a76e206de2562e0843c"},
+    {file = "ruff-0.4.1-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:b92f03b4aa9fa23e1799b40f15f8b95cdc418782a567d6c43def65e1bbb7f1cf"},
+    {file = "ruff-0.4.1-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:1c859f294f8633889e7d77de228b203eb0e9a03071b72b5989d89a0cf98ee262"},
+    {file = "ruff-0.4.1-py3-none-musllinux_1_2_i686.whl", hash = "sha256:b34510141e393519a47f2d7b8216fec747ea1f2c81e85f076e9f2910588d4b64"},
+    {file = "ruff-0.4.1-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:6e68d248ed688b9d69fd4d18737edcbb79c98b251bba5a2b031ce2470224bdf9"},
+    {file = "ruff-0.4.1-py3-none-win32.whl", hash = "sha256:b90506f3d6d1f41f43f9b7b5ff845aeefabed6d2494307bc7b178360a8805252"},
+    {file = "ruff-0.4.1-py3-none-win_amd64.whl", hash = "sha256:c7d391e5936af5c9e252743d767c564670dc3889aff460d35c518ee76e4b26d7"},
+    {file = "ruff-0.4.1-py3-none-win_arm64.whl", hash = "sha256:a1eaf03d87e6a7cd5e661d36d8c6e874693cb9bc3049d110bc9a97b350680c43"},
+    {file = "ruff-0.4.1.tar.gz", hash = "sha256:d592116cdbb65f8b1b7e2a2b48297eb865f6bdc20641879aa9d7b9c11d86db79"},
 ]
 
 [[package]]

From feae6d3f78844a32ec03723eb91d6d37d6258d02 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 22 Apr 2024 17:43:51 +0000
Subject: [PATCH 153/188] =?UTF-8?q?chore(pre=5Fcommit):=20=E2=AC=86=20pre?=
 =?UTF-8?q?=5Fcommit=20autoupdate?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.3.7 → v0.4.1](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.7...v0.4.1)
---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index b016ca8d6..ef3620b13 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -45,7 +45,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.3.7
+      rev: v0.4.1
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

From a6b563cf4def3dbdca8dfeae60a5cfdbf87ff8b5 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Tue, 23 Apr 2024 17:18:34 +0300
Subject: [PATCH 154/188] Add keypoints skeleton, 2x annotators

---
 supervision/keypoints/annotate.py | 102 ++++++++++++++++++++++++++++++
 supervision/keypoints/core.py     |  43 ++++++++++++-
 2 files changed, 142 insertions(+), 3 deletions(-)
 create mode 100644 supervision/keypoints/annotate.py

diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
new file mode 100644
index 000000000..4c37b2480
--- /dev/null
+++ b/supervision/keypoints/annotate.py
@@ -0,0 +1,102 @@
+from abc import ABC, abstractmethod
+
+import cv2
+import numpy as np
+
+from supervision.annotators.base import ImageType
+from supervision.annotators.utils import scene_to_annotator_img_type
+from supervision.draw.color import Color
+from supervision.keypoints.core import KeyPoints, Skeleton
+
+
+class BaseKeyPointAnnotator(ABC):
+    @abstractmethod
+    def annotate(self, scene: ImageType, detections: KeyPoints) -> ImageType:
+        pass
+
+
+class PointAnnotator(BaseKeyPointAnnotator):
+    def __init__(
+        self,
+        color: Color = Color.GREEN,
+        radius: int = 4,
+    ) -> None:
+        """
+        Most basic keypoint annotator.
+        """
+        self.color = color
+        self.radius = radius
+
+    @scene_to_annotator_img_type
+    def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
+        # TODO: I'm getting shape [1, N, 2] here - not [N, 2].
+        #       Seems like it accounts for more than 1 person in an image.
+        if len(keypoints) == 0:
+            return scene
+
+        xy = keypoints.xy[0]
+        for i, (x, y) in enumerate(xy):
+            cv2.circle(
+                img=scene,
+                center=(int(x), int(y)),
+                radius=self.radius,
+                color=self.color.as_bgr(),
+                thickness=-1,
+            )
+
+        return scene
+
+
+class SkeletonAnnotator(BaseKeyPointAnnotator):
+    def __init__(
+        self,
+        point_color: Color = Color.GREEN,
+        point_radius: int = 4,
+        limb_color: Color = Color.GREEN,
+        limb_thickness: int = 2,
+    ) -> None:
+        self.point_color = point_color
+        self.point_radius = point_radius
+        self.limb_color = limb_color
+        self.limb_thickness = limb_thickness
+
+    @scene_to_annotator_img_type
+    def annotate(
+        self, scene: ImageType, keypoints: KeyPoints, skeleton: Skeleton
+    ) -> ImageType:
+        if len(keypoints) == 0:
+            return scene
+        if keypoints.class_id is None:
+            raise ValueError("KeyPoints must have class_id to annotate a skeleton")
+
+        # print(keypoints)
+
+        xy = keypoints.xy[0]
+        class_id = keypoints.class_id[0]
+
+        for i, (x, y) in enumerate(xy):
+            cv2.circle(
+                img=scene,
+                center=(int(x), int(y)),
+                radius=self.point_radius,
+                color=self.point_color.as_bgr(),
+                thickness=-1,
+            )
+
+        for class_a, class_b in skeleton.limbs:
+            xy_a = xy[class_a - 1]
+            xy_b = xy[class_b - 1]
+            missing_a = np.allclose(xy_a, 0)
+            missing_b = np.allclose(xy_b, 0)
+            if missing_a or missing_b:
+                continue
+
+            cv2.line(
+                img=scene,
+                pt1=(int(xy_a[0]), int(xy_a[1])),
+                pt2=(int(xy_b[0]), int(xy_b[1])),
+                color=self.limb_color.as_bgr(),
+                thickness=self.limb_thickness,
+            )
+
+        return scene
diff --git a/supervision/keypoints/core.py b/supervision/keypoints/core.py
index 646b99db7..25f14fae4 100644
--- a/supervision/keypoints/core.py
+++ b/supervision/keypoints/core.py
@@ -132,14 +132,15 @@ def from_ultralytics(cls, ultralytics_results) -> "KeyPoints":
             result = model(image)[0]
             keypoints = sv.KeyPoints.from_ultralytics(result)
             ```
-        """  #
+        """
+        if len(ultralytics_results.keypoints.xy) == 0:
+            return cls.empty()
 
+        xy = ultralytics_results.keypoints.xy.cpu().numpy()
         class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
         class_names = np.array([ultralytics_results.names[i] for i in class_id])
 
-        xy = ultralytics_results.keypoints.xy.cpu().numpy()
         confidence = ultralytics_results.keypoints.conf.cpu().numpy()
-        class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
         data = {CLASS_NAME_DATA_FIELD: class_names}
         return cls(xy, class_id, confidence, data)
 
@@ -238,3 +239,39 @@ def empty(cls) -> "KeyPoints":
             ```
         """
         return cls(xy=np.empty((0, 0, 2), dtype=np.float32))
+
+
+class Skeleton:
+    """
+    The `Skeleton` class connects keypoints to form a skeleton.
+
+    It provides utility methods to compute angles within itself, compare to skeletons, etc.
+    """
+
+    limbs: List[Tuple[int, int]]
+
+    def __init__(self, limbs: List[Tuple[int, int]]):
+        self.limbs = limbs
+
+
+YOLO_V8_SKELETON = Skeleton(
+    [
+        (1, 2),
+        (1, 3),
+        (2, 3),
+        (2, 4),
+        (3, 5),
+        (6, 12),
+        (6, 7),
+        (6, 8),
+        (7, 13),
+        (7, 9),
+        (8, 10),
+        (9, 11),
+        (12, 13),
+        (14, 12),
+        (15, 13),
+        (16, 14),
+        (17, 15),
+    ]
+)

From d079ce92df781fb43ee46d8047faa795fb066983 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Tue, 23 Apr 2024 19:26:12 +0300
Subject: [PATCH 155/188] Keypoints: Separate-out skeleton annotator

---
 supervision/keypoints/annotate.py | 31 ++++++++-----------------------
 1 file changed, 8 insertions(+), 23 deletions(-)

diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
index 4c37b2480..b82ea071b 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoints/annotate.py
@@ -50,15 +50,11 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
 class SkeletonAnnotator(BaseKeyPointAnnotator):
     def __init__(
         self,
-        point_color: Color = Color.GREEN,
-        point_radius: int = 4,
-        limb_color: Color = Color.GREEN,
-        limb_thickness: int = 2,
+        color: Color = Color.GREEN,
+        thickness: int = 2,
     ) -> None:
-        self.point_color = point_color
-        self.point_radius = point_radius
-        self.limb_color = limb_color
-        self.limb_thickness = limb_thickness
+        self.color = color
+        self.thickness = thickness
 
     @scene_to_annotator_img_type
     def annotate(
@@ -67,21 +63,10 @@ def annotate(
         if len(keypoints) == 0:
             return scene
         if keypoints.class_id is None:
-            raise ValueError("KeyPoints must have class_id to annotate a skeleton")
-
-        # print(keypoints)
+            raise ValueError(
+                "KeyPoints must have class_id to annotate a skeleton")
 
         xy = keypoints.xy[0]
-        class_id = keypoints.class_id[0]
-
-        for i, (x, y) in enumerate(xy):
-            cv2.circle(
-                img=scene,
-                center=(int(x), int(y)),
-                radius=self.point_radius,
-                color=self.point_color.as_bgr(),
-                thickness=-1,
-            )
 
         for class_a, class_b in skeleton.limbs:
             xy_a = xy[class_a - 1]
@@ -95,8 +80,8 @@ def annotate(
                 img=scene,
                 pt1=(int(xy_a[0]), int(xy_a[1])),
                 pt2=(int(xy_b[0]), int(xy_b[1])),
-                color=self.limb_color.as_bgr(),
-                thickness=self.limb_thickness,
+                color=self.color.as_bgr(),
+                thickness=self.thickness,
             )
 
         return scene

From a00604bfb24c609727a4b26cea923d62602a07fc Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Tue, 23 Apr 2024 19:28:34 +0300
Subject: [PATCH 156/188] Keypoints: Expose KeyPoints, annotators in __init__

---
 supervision/__init__.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index df04534dd..ad02202d2 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -56,6 +56,8 @@
     polygon_to_xyxy,
     scale_boxes,
 )
+from supervision.keypoints.core import KeyPoints, YOLO_V8_SKELETON
+from supervision.keypoints.annotate import PointAnnotator, SkeletonAnnotator
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import (
     calculate_optimal_line_thickness,

From 7f0ecbbd0a2f76f9a54a36449a48033d87df83fc Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Tue, 23 Apr 2024 20:19:28 +0300
Subject: [PATCH 157/188] Keypoints: Smart skellies

---
 supervision/__init__.py            |  5 +-
 supervision/keypoints/annotate.py  | 30 +++++++--
 supervision/keypoints/core.py      | 42 ++-----------
 supervision/keypoints/skeletons.py | 97 ++++++++++++++++++++++++++++++
 4 files changed, 129 insertions(+), 45 deletions(-)
 create mode 100644 supervision/keypoints/skeletons.py

diff --git a/supervision/__init__.py b/supervision/__init__.py
index ad02202d2..549e870e3 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -56,8 +56,9 @@
     polygon_to_xyxy,
     scale_boxes,
 )
-from supervision.keypoints.core import KeyPoints, YOLO_V8_SKELETON
-from supervision.keypoints.annotate import PointAnnotator, SkeletonAnnotator
+from supervision.keypoints.core import KeyPoints
+from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
+from supervision.keypoints.annotate import KeyPointAnnotator, SkeletonAnnotator
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import (
     calculate_optimal_line_thickness,
diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
index b82ea071b..0511def43 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoints/annotate.py
@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+from typing import Optional
 
 import cv2
 import numpy as np
@@ -6,7 +7,8 @@
 from supervision.annotators.base import ImageType
 from supervision.annotators.utils import scene_to_annotator_img_type
 from supervision.draw.color import Color
-from supervision.keypoints.core import KeyPoints, Skeleton
+from supervision.keypoints.core import KeyPoints
+from supervision.keypoints.skeletons import Skeleton, KnownSkeletons
 
 
 class BaseKeyPointAnnotator(ABC):
@@ -15,14 +17,18 @@ def annotate(self, scene: ImageType, detections: KeyPoints) -> ImageType:
         pass
 
 
-class PointAnnotator(BaseKeyPointAnnotator):
+class KeyPointAnnotator(BaseKeyPointAnnotator):
     def __init__(
         self,
-        color: Color = Color.GREEN,
+        color: Color = Color.ROBOFLOW,
         radius: int = 4,
     ) -> None:
         """
         Most basic keypoint annotator.
+
+        Args:
+            color (Color, optional): The color of the keypoint.
+            radius (int, optional): The radius of the keypoint.
         """
         self.color = color
         self.radius = radius
@@ -50,15 +56,26 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
 class SkeletonAnnotator(BaseKeyPointAnnotator):
     def __init__(
         self,
-        color: Color = Color.GREEN,
+        color: Color = Color.ROBOFLOW,
         thickness: int = 2,
+        skeleton: Optional[Skeleton] = None,
     ) -> None:
+        """
+        Draw the lines between points of the image.
+
+        Args:
+            color (Color, optional): The color of the lines.
+            thickness (int, optional): The thickness of the lines.
+            skeleton (Skeleton, optional): The skeleton to draw.
+                If set to `None`, will attempt to select automatically.
+        """
         self.color = color
         self.thickness = thickness
+        self.skeleton = skeleton
 
     @scene_to_annotator_img_type
     def annotate(
-        self, scene: ImageType, keypoints: KeyPoints, skeleton: Skeleton
+        self, scene: ImageType, keypoints: KeyPoints
     ) -> ImageType:
         if len(keypoints) == 0:
             return scene
@@ -67,6 +84,9 @@ def annotate(
                 "KeyPoints must have class_id to annotate a skeleton")
 
         xy = keypoints.xy[0]
+        skeleton = self.skeleton
+        if not skeleton:
+            skeleton = KnownSkeletons().get_skeleton(len(xy))
 
         for class_a, class_b in skeleton.limbs:
             xy_a = xy[class_a - 1]
diff --git a/supervision/keypoints/core.py b/supervision/keypoints/core.py
index 25f14fae4..5aa0a4d11 100644
--- a/supervision/keypoints/core.py
+++ b/supervision/keypoints/core.py
@@ -58,7 +58,8 @@ class KeyPoints:
     xy: npt.NDArray[np.float32]
     class_id: Optional[npt.NDArray[np.int_]] = None
     confidence: Optional[npt.NDArray[np.float32]] = None
-    data: Dict[str, Union[npt.NDArray[Any], List]] = field(default_factory=dict)
+    data: Dict[str, Union[npt.NDArray[Any], List]
+               ] = field(default_factory=dict)
 
     def __post_init__(self):
         validate_keypoints_fields(
@@ -138,7 +139,8 @@ def from_ultralytics(cls, ultralytics_results) -> "KeyPoints":
 
         xy = ultralytics_results.keypoints.xy.cpu().numpy()
         class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
-        class_names = np.array([ultralytics_results.names[i] for i in class_id])
+        class_names = np.array([ultralytics_results.names[i]
+                               for i in class_id])
 
         confidence = ultralytics_results.keypoints.conf.cpu().numpy()
         data = {CLASS_NAME_DATA_FIELD: class_names}
@@ -239,39 +241,3 @@ def empty(cls) -> "KeyPoints":
             ```
         """
         return cls(xy=np.empty((0, 0, 2), dtype=np.float32))
-
-
-class Skeleton:
-    """
-    The `Skeleton` class connects keypoints to form a skeleton.
-
-    It provides utility methods to compute angles within itself, compare to skeletons, etc.
-    """
-
-    limbs: List[Tuple[int, int]]
-
-    def __init__(self, limbs: List[Tuple[int, int]]):
-        self.limbs = limbs
-
-
-YOLO_V8_SKELETON = Skeleton(
-    [
-        (1, 2),
-        (1, 3),
-        (2, 3),
-        (2, 4),
-        (3, 5),
-        (6, 12),
-        (6, 7),
-        (6, 8),
-        (7, 13),
-        (7, 9),
-        (8, 10),
-        (9, 11),
-        (12, 13),
-        (14, 12),
-        (15, 13),
-        (16, 14),
-        (17, 15),
-    ]
-)
diff --git a/supervision/keypoints/skeletons.py b/supervision/keypoints/skeletons.py
new file mode 100644
index 000000000..a9d8d01f5
--- /dev/null
+++ b/supervision/keypoints/skeletons.py
@@ -0,0 +1,97 @@
+
+
+from typing import List, Tuple
+
+
+class Skeleton:
+    """
+    The `Skeleton` class connects keypoints to form a skeleton.
+
+    Args:
+        limbs: (List[Tuple[int, int]]): List of (`class_id_1`,
+        `class_id_2`) representing connected points of the skeleton.
+    """
+
+    limbs: List[Tuple[int, int]]
+
+    def __init__(self, limbs: List[Tuple[int, int]]):
+        self.limbs = limbs
+
+
+NO_SKELETON = Skeleton([])
+YOLO_V8_SKELETON = Skeleton(
+    [
+        (1, 2),
+        (1, 3),
+        (2, 3),
+        (2, 4),
+        (3, 5),
+        (6, 12),
+        (6, 7),
+        (6, 8),
+        (7, 13),
+        (7, 9),
+        (8, 10),
+        (9, 11),
+        (12, 13),
+        (14, 12),
+        (15, 13),
+        (16, 14),
+        (17, 15),
+    ]
+)
+
+
+def _make_sequential_skeleton(limb_count: int) -> Skeleton:
+    """
+    Create a skeleton where neighboring keypoints are connected sequentially.
+
+    Args:
+        limb_count (int): The number of limbs to connect.
+
+    Returns:
+        Skeleton: The skeleton connecting all keypoints.
+    """
+    limbs = []
+    for i in range(0, limb_count - 1):
+        limbs.append((i, i + 1))
+    limbs.append((0, limb_count - 1))
+    return Skeleton(limbs)
+
+
+class KnownSkeletons:
+    """
+    Helps automatically determine which skeleton to use.
+
+    The `KnownSkeletons` class contains a collection of predefined skeletons
+    for various keypoint models, to be distinguished by limb counts.
+
+    Example:
+        # Suppose you have a model returning 15 keypoints.
+        skeleton = KnownSkeletons().get_skeleton(15)
+    """
+    _instance = None
+    _skeletons: dict[int, Skeleton] = {}
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(KnownSkeletons, cls).__new__(cls)
+        return cls._instance
+
+    def add_skeleton(self, skeleton: Skeleton) -> None:
+        len_limbs = len(skeleton.limbs)
+        if len_limbs in self._skeletons:
+            raise ValueError(
+                f"A skeleton with {len_limbs} limbs already exists")
+        self._skeletons[len_limbs] = skeleton
+
+    def get_skeleton(self, limb_count: int) -> Skeleton:
+        if limb_count not in self._skeletons:
+            print(
+                f"Warning: No skeleton found with {limb_count} limbs. Will create one now.")
+            self.add_skeleton(_make_sequential_skeleton(limb_count))
+        return self._skeletons[limb_count]
+
+
+KnownSkeletons().add_skeleton(NO_SKELETON)
+KnownSkeletons().add_skeleton(YOLO_V8_SKELETON)

From 07482a347cfcbbfb7bf7d130541146c211c8f896 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Tue, 23 Apr 2024 20:43:14 +0300
Subject: [PATCH 158/188] Keypoints: Multi-person annotators

---
 supervision/keypoints/annotate.py | 60 ++++++++++++++++---------------
 1 file changed, 31 insertions(+), 29 deletions(-)

diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
index 0511def43..e051fa8e5 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoints/annotate.py
@@ -40,15 +40,16 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
 
-        xy = keypoints.xy[0]
-        for i, (x, y) in enumerate(xy):
-            cv2.circle(
-                img=scene,
-                center=(int(x), int(y)),
-                radius=self.radius,
-                color=self.color.as_bgr(),
-                thickness=-1,
-            )
+        xy_all = keypoints.xy
+        for xy in xy_all:
+            for x, y in xy:
+                cv2.circle(
+                    img=scene,
+                    center=(int(x), int(y)),
+                    radius=self.radius,
+                    color=self.color.as_bgr(),
+                    thickness=-1,
+                )
 
         return scene
 
@@ -83,25 +84,26 @@ def annotate(
             raise ValueError(
                 "KeyPoints must have class_id to annotate a skeleton")
 
-        xy = keypoints.xy[0]
-        skeleton = self.skeleton
-        if not skeleton:
-            skeleton = KnownSkeletons().get_skeleton(len(xy))
-
-        for class_a, class_b in skeleton.limbs:
-            xy_a = xy[class_a - 1]
-            xy_b = xy[class_b - 1]
-            missing_a = np.allclose(xy_a, 0)
-            missing_b = np.allclose(xy_b, 0)
-            if missing_a or missing_b:
-                continue
-
-            cv2.line(
-                img=scene,
-                pt1=(int(xy_a[0]), int(xy_a[1])),
-                pt2=(int(xy_b[0]), int(xy_b[1])),
-                color=self.color.as_bgr(),
-                thickness=self.thickness,
-            )
+        xy_all = keypoints.xy
+        for xy in xy_all:
+            skeleton = self.skeleton
+            if not skeleton:
+                skeleton = KnownSkeletons().get_skeleton(len(xy))
+
+            for class_a, class_b in skeleton.limbs:
+                xy_a = xy[class_a - 1]
+                xy_b = xy[class_b - 1]
+                missing_a = np.allclose(xy_a, 0)
+                missing_b = np.allclose(xy_b, 0)
+                if missing_a or missing_b:
+                    continue
+
+                cv2.line(
+                    img=scene,
+                    pt1=(int(xy_a[0]), int(xy_a[1])),
+                    pt2=(int(xy_b[0]), int(xy_b[1])),
+                    color=self.color.as_bgr(),
+                    thickness=self.thickness,
+                )
 
         return scene

From 409dcbd9da5d1aeb5c3a7746163be87bfaf3628d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 23 Apr 2024 20:49:03 +0000
Subject: [PATCH 159/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/__init__.py            | 5 ++---
 supervision/keypoints/annotate.py  | 9 +++------
 supervision/keypoints/core.py      | 6 ++----
 supervision/keypoints/skeletons.py | 9 ++++-----
 4 files changed, 11 insertions(+), 18 deletions(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 549e870e3..c48833358 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -56,9 +56,6 @@
     polygon_to_xyxy,
     scale_boxes,
 )
-from supervision.keypoints.core import KeyPoints
-from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
-from supervision.keypoints.annotate import KeyPointAnnotator, SkeletonAnnotator
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import (
     calculate_optimal_line_thickness,
@@ -72,7 +69,9 @@
 )
 from supervision.geometry.core import Point, Position, Rect
 from supervision.geometry.utils import get_polygon_center
+from supervision.keypoints.annotate import KeyPointAnnotator, SkeletonAnnotator
 from supervision.keypoints.core import KeyPoints
+from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
 from supervision.utils.file import list_files_with_extensions
diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
index e051fa8e5..978c1e8d3 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoints/annotate.py
@@ -8,7 +8,7 @@
 from supervision.annotators.utils import scene_to_annotator_img_type
 from supervision.draw.color import Color
 from supervision.keypoints.core import KeyPoints
-from supervision.keypoints.skeletons import Skeleton, KnownSkeletons
+from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
 
 
 class BaseKeyPointAnnotator(ABC):
@@ -75,14 +75,11 @@ def __init__(
         self.skeleton = skeleton
 
     @scene_to_annotator_img_type
-    def annotate(
-        self, scene: ImageType, keypoints: KeyPoints
-    ) -> ImageType:
+    def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
         if keypoints.class_id is None:
-            raise ValueError(
-                "KeyPoints must have class_id to annotate a skeleton")
+            raise ValueError("KeyPoints must have class_id to annotate a skeleton")
 
         xy_all = keypoints.xy
         for xy in xy_all:
diff --git a/supervision/keypoints/core.py b/supervision/keypoints/core.py
index 5aa0a4d11..2b432be4b 100644
--- a/supervision/keypoints/core.py
+++ b/supervision/keypoints/core.py
@@ -58,8 +58,7 @@ class KeyPoints:
     xy: npt.NDArray[np.float32]
     class_id: Optional[npt.NDArray[np.int_]] = None
     confidence: Optional[npt.NDArray[np.float32]] = None
-    data: Dict[str, Union[npt.NDArray[Any], List]
-               ] = field(default_factory=dict)
+    data: Dict[str, Union[npt.NDArray[Any], List]] = field(default_factory=dict)
 
     def __post_init__(self):
         validate_keypoints_fields(
@@ -139,8 +138,7 @@ def from_ultralytics(cls, ultralytics_results) -> "KeyPoints":
 
         xy = ultralytics_results.keypoints.xy.cpu().numpy()
         class_id = ultralytics_results.boxes.cls.cpu().numpy().astype(int)
-        class_names = np.array([ultralytics_results.names[i]
-                               for i in class_id])
+        class_names = np.array([ultralytics_results.names[i] for i in class_id])
 
         confidence = ultralytics_results.keypoints.conf.cpu().numpy()
         data = {CLASS_NAME_DATA_FIELD: class_names}
diff --git a/supervision/keypoints/skeletons.py b/supervision/keypoints/skeletons.py
index a9d8d01f5..03a4f3357 100644
--- a/supervision/keypoints/skeletons.py
+++ b/supervision/keypoints/skeletons.py
@@ -1,5 +1,3 @@
-
-
 from typing import List, Tuple
 
 
@@ -70,6 +68,7 @@ class KnownSkeletons:
         # Suppose you have a model returning 15 keypoints.
         skeleton = KnownSkeletons().get_skeleton(15)
     """
+
     _instance = None
     _skeletons: dict[int, Skeleton] = {}
 
@@ -81,14 +80,14 @@ def __new__(cls):
     def add_skeleton(self, skeleton: Skeleton) -> None:
         len_limbs = len(skeleton.limbs)
         if len_limbs in self._skeletons:
-            raise ValueError(
-                f"A skeleton with {len_limbs} limbs already exists")
+            raise ValueError(f"A skeleton with {len_limbs} limbs already exists")
         self._skeletons[len_limbs] = skeleton
 
     def get_skeleton(self, limb_count: int) -> Skeleton:
         if limb_count not in self._skeletons:
             print(
-                f"Warning: No skeleton found with {limb_count} limbs. Will create one now.")
+                f"Warning: No skeleton found with {limb_count} limbs. Will create one now."
+            )
             self.add_skeleton(_make_sequential_skeleton(limb_count))
         return self._skeletons[limb_count]
 

From 0274c45dbc086b75144a85a30af0630adf94fadf Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 23 Apr 2024 23:12:54 +0200
Subject: [PATCH 160/188] solve CI tests

---
 supervision/keypoints/annotate.py  | 6 +++---
 supervision/keypoints/skeletons.py | 3 ++-
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
index 978c1e8d3..0a8379464 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoints/annotate.py
@@ -5,10 +5,10 @@
 import numpy as np
 
 from supervision.annotators.base import ImageType
-from supervision.annotators.utils import scene_to_annotator_img_type
 from supervision.draw.color import Color
 from supervision.keypoints.core import KeyPoints
 from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
+from supervision.utils.conversion import convert_for_annotation_method
 
 
 class BaseKeyPointAnnotator(ABC):
@@ -33,7 +33,7 @@ def __init__(
         self.color = color
         self.radius = radius
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         # TODO: I'm getting shape [1, N, 2] here - not [N, 2].
         #       Seems like it accounts for more than 1 person in an image.
@@ -74,7 +74,7 @@ def __init__(
         self.thickness = thickness
         self.skeleton = skeleton
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
diff --git a/supervision/keypoints/skeletons.py b/supervision/keypoints/skeletons.py
index 03a4f3357..d150b661b 100644
--- a/supervision/keypoints/skeletons.py
+++ b/supervision/keypoints/skeletons.py
@@ -86,7 +86,8 @@ def add_skeleton(self, skeleton: Skeleton) -> None:
     def get_skeleton(self, limb_count: int) -> Skeleton:
         if limb_count not in self._skeletons:
             print(
-                f"Warning: No skeleton found with {limb_count} limbs. Will create one now."
+                f"Warning: No skeleton found with {limb_count} limbs. "
+                f"Will create one now."
             )
             self.add_skeleton(_make_sequential_skeleton(limb_count))
         return self._skeletons[limb_count]

From 9789ff4043b0c6cf7a70b62a9deac1bceb807be5 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Tue, 23 Apr 2024 23:12:54 +0200
Subject: [PATCH 161/188] solve CI tests

---
 supervision/keypoints/annotate.py  | 6 +++---
 supervision/keypoints/skeletons.py | 7 ++++---
 supervision/keypoints/utils.py     | 0
 3 files changed, 7 insertions(+), 6 deletions(-)
 delete mode 100644 supervision/keypoints/utils.py

diff --git a/supervision/keypoints/annotate.py b/supervision/keypoints/annotate.py
index 978c1e8d3..0a8379464 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoints/annotate.py
@@ -5,10 +5,10 @@
 import numpy as np
 
 from supervision.annotators.base import ImageType
-from supervision.annotators.utils import scene_to_annotator_img_type
 from supervision.draw.color import Color
 from supervision.keypoints.core import KeyPoints
 from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
+from supervision.utils.conversion import convert_for_annotation_method
 
 
 class BaseKeyPointAnnotator(ABC):
@@ -33,7 +33,7 @@ def __init__(
         self.color = color
         self.radius = radius
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         # TODO: I'm getting shape [1, N, 2] here - not [N, 2].
         #       Seems like it accounts for more than 1 person in an image.
@@ -74,7 +74,7 @@ def __init__(
         self.thickness = thickness
         self.skeleton = skeleton
 
-    @scene_to_annotator_img_type
+    @convert_for_annotation_method
     def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
diff --git a/supervision/keypoints/skeletons.py b/supervision/keypoints/skeletons.py
index 03a4f3357..5b0722759 100644
--- a/supervision/keypoints/skeletons.py
+++ b/supervision/keypoints/skeletons.py
@@ -1,4 +1,4 @@
-from typing import List, Tuple
+from typing import List, Tuple, Dict
 
 
 class Skeleton:
@@ -70,7 +70,7 @@ class KnownSkeletons:
     """
 
     _instance = None
-    _skeletons: dict[int, Skeleton] = {}
+    _skeletons: Dict[int, Skeleton] = {}
 
     def __new__(cls):
         if cls._instance is None:
@@ -86,7 +86,8 @@ def add_skeleton(self, skeleton: Skeleton) -> None:
     def get_skeleton(self, limb_count: int) -> Skeleton:
         if limb_count not in self._skeletons:
             print(
-                f"Warning: No skeleton found with {limb_count} limbs. Will create one now."
+                f"Warning: No skeleton found with {limb_count} limbs. "
+                f"Will create one now."
             )
             self.add_skeleton(_make_sequential_skeleton(limb_count))
         return self._skeletons[limb_count]
diff --git a/supervision/keypoints/utils.py b/supervision/keypoints/utils.py
deleted file mode 100644
index e69de29bb..000000000

From e2fabc1cfe38ea815100b6651c6ea5d359c138f5 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 23 Apr 2024 21:57:28 +0000
Subject: [PATCH 162/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/keypoints/skeletons.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/keypoints/skeletons.py b/supervision/keypoints/skeletons.py
index 5b0722759..dd8c7ec83 100644
--- a/supervision/keypoints/skeletons.py
+++ b/supervision/keypoints/skeletons.py
@@ -1,4 +1,4 @@
-from typing import List, Tuple, Dict
+from typing import Dict, List, Tuple
 
 
 class Skeleton:

From 2745c70ae0e558c18afef7a0c67d0d88d6311f89 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 00:21:19 +0200
Subject: [PATCH 163/188] docs plugged into `mkdocs.yml`

---
 docs/keypoint/annotate.md                        | 10 ++++++++++
 docs/keypoint/core.md                            |  8 ++++++++
 mkdocs.yml                                       |  3 +++
 supervision/__init__.py                          |  6 +++---
 supervision/{keypoints => keypoint}/__init__.py  |  0
 supervision/{keypoints => keypoint}/annotate.py  |  8 +++-----
 supervision/{keypoints => keypoint}/core.py      |  8 +++++---
 supervision/{keypoints => keypoint}/skeletons.py |  0
 8 files changed, 32 insertions(+), 11 deletions(-)
 create mode 100644 docs/keypoint/annotate.md
 create mode 100644 docs/keypoint/core.md
 rename supervision/{keypoints => keypoint}/__init__.py (100%)
 rename supervision/{keypoints => keypoint}/annotate.py (90%)
 rename supervision/{keypoints => keypoint}/core.py (97%)
 rename supervision/{keypoints => keypoint}/skeletons.py (100%)

diff --git a/docs/keypoint/annotate.md b/docs/keypoint/annotate.md
new file mode 100644
index 000000000..8507f54e4
--- /dev/null
+++ b/docs/keypoint/annotate.md
@@ -0,0 +1,10 @@
+---
+comments: true
+status: new
+---
+
+# Annotate
+
+:::supervision.keypoint.annotate.VertexAnnotator
+
+:::supervision.keypoint.annotate.SkeletonAnnotator
\ No newline at end of file
diff --git a/docs/keypoint/core.md b/docs/keypoint/core.md
new file mode 100644
index 000000000..7354babab
--- /dev/null
+++ b/docs/keypoint/core.md
@@ -0,0 +1,8 @@
+---
+comments: true
+status: new
+---
+
+# Keypoint Detection
+
+:::supervision.keypoint.core.KeyPoints
diff --git a/mkdocs.yml b/mkdocs.yml
index dd6feb8db..256c6bef4 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -50,6 +50,9 @@ nav:
     - Detections:
         - Core: detection/core.md
         - Utils: detection/utils.md
+    - KeyPoints:
+        - Core: keypoint/core.md
+        - Annotators: keypoint/annotate.md
     - Tools:
         - Line Zone: detection/tools/line_zone.md
         - Polygon Zone: detection/tools/polygon_zone.md
diff --git a/supervision/__init__.py b/supervision/__init__.py
index c25ec791d..70c912c08 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -69,9 +69,9 @@
 )
 from supervision.geometry.core import Point, Position, Rect
 from supervision.geometry.utils import get_polygon_center
-from supervision.keypoints.annotate import KeyPointAnnotator, SkeletonAnnotator
-from supervision.keypoints.core import KeyPoints
-from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
+from supervision.keypoint.annotate import VertexAnnotator, SkeletonAnnotator
+from supervision.keypoint.core import KeyPoints
+from supervision.keypoint.skeletons import KnownSkeletons, Skeleton
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
 from supervision.utils.conversion import cv2_to_pillow, pillow_to_cv2
diff --git a/supervision/keypoints/__init__.py b/supervision/keypoint/__init__.py
similarity index 100%
rename from supervision/keypoints/__init__.py
rename to supervision/keypoint/__init__.py
diff --git a/supervision/keypoints/annotate.py b/supervision/keypoint/annotate.py
similarity index 90%
rename from supervision/keypoints/annotate.py
rename to supervision/keypoint/annotate.py
index 0a8379464..802199f39 100644
--- a/supervision/keypoints/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -6,8 +6,8 @@
 
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color
-from supervision.keypoints.core import KeyPoints
-from supervision.keypoints.skeletons import KnownSkeletons, Skeleton
+from supervision.keypoint.core import KeyPoints
+from supervision.keypoint.skeletons import KnownSkeletons, Skeleton
 from supervision.utils.conversion import convert_for_annotation_method
 
 
@@ -17,7 +17,7 @@ def annotate(self, scene: ImageType, detections: KeyPoints) -> ImageType:
         pass
 
 
-class KeyPointAnnotator(BaseKeyPointAnnotator):
+class VertexAnnotator(BaseKeyPointAnnotator):
     def __init__(
         self,
         color: Color = Color.ROBOFLOW,
@@ -35,8 +35,6 @@ def __init__(
 
     @convert_for_annotation_method
     def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
-        # TODO: I'm getting shape [1, N, 2] here - not [N, 2].
-        #       Seems like it accounts for more than 1 person in an image.
         if len(keypoints) == 0:
             return scene
 
diff --git a/supervision/keypoints/core.py b/supervision/keypoint/core.py
similarity index 97%
rename from supervision/keypoints/core.py
rename to supervision/keypoint/core.py
index 2b432be4b..aca50ad5b 100644
--- a/supervision/keypoints/core.py
+++ b/supervision/keypoint/core.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from dataclasses import dataclass, field
 from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
 
@@ -98,7 +100,7 @@ def __iter__(
                 get_data_item(self.data, i),
             )
 
-    def __eq__(self, other: "KeyPoints") -> bool:
+    def __eq__(self, other: KeyPoints) -> bool:
         return all(
             [
                 np.array_equal(self.xy, other.xy),
@@ -109,7 +111,7 @@ def __eq__(self, other: "KeyPoints") -> bool:
         )
 
     @classmethod
-    def from_ultralytics(cls, ultralytics_results) -> "KeyPoints":
+    def from_ultralytics(cls, ultralytics_results) -> KeyPoints:
         """
         Creates a Keypoints instance from a
             [YOLOv8](https://github.com/ultralytics/ultralytics) inference result.
@@ -225,7 +227,7 @@ def __setitem__(self, key: str, value: Union[np.ndarray, List]):
         self.data[key] = value
 
     @classmethod
-    def empty(cls) -> "KeyPoints":
+    def empty(cls) -> KeyPoints:
         """
         Create an empty Keypoints object with no keypoints.
 
diff --git a/supervision/keypoints/skeletons.py b/supervision/keypoint/skeletons.py
similarity index 100%
rename from supervision/keypoints/skeletons.py
rename to supervision/keypoint/skeletons.py

From e2865ecda73e99ed072ebdae3dd65147e551f2be Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 23 Apr 2024 22:21:47 +0000
Subject: [PATCH 164/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/keypoint/annotate.md | 2 +-
 supervision/__init__.py   | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/keypoint/annotate.md b/docs/keypoint/annotate.md
index 8507f54e4..476ae9186 100644
--- a/docs/keypoint/annotate.md
+++ b/docs/keypoint/annotate.md
@@ -7,4 +7,4 @@ status: new
 
 :::supervision.keypoint.annotate.VertexAnnotator
 
-:::supervision.keypoint.annotate.SkeletonAnnotator
\ No newline at end of file
+:::supervision.keypoint.annotate.SkeletonAnnotator
diff --git a/supervision/__init__.py b/supervision/__init__.py
index 70c912c08..53948d1a0 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -69,7 +69,7 @@
 )
 from supervision.geometry.core import Point, Position, Rect
 from supervision.geometry.utils import get_polygon_center
-from supervision.keypoint.annotate import VertexAnnotator, SkeletonAnnotator
+from supervision.keypoint.annotate import SkeletonAnnotator, VertexAnnotator
 from supervision.keypoint.core import KeyPoints
 from supervision.keypoint.skeletons import KnownSkeletons, Skeleton
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision

From 397b2249a776c2321d18b89b5a984ec38773b498 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 00:24:21 +0200
Subject: [PATCH 165/188] fix typo

---
 test/test_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test_utils.py b/test/test_utils.py
index d36248450..b676cb549 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -3,7 +3,7 @@
 import numpy as np
 
 from supervision.detection.core import Detections
-from supervision.keypoints.core import KeyPoints
+from supervision.keypoint.core import KeyPoints
 
 
 def mock_detections(

From 102c5adc386c12a53ef7ddec583bfe68f171ccd1 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 00:43:46 +0200
Subject: [PATCH 166/188] test simplified skeleton API

---
 supervision/__init__.py           |  2 +-
 supervision/keypoint/annotate.py  | 10 ++--
 supervision/keypoint/skeletons.py | 88 ++++++-------------------------
 3 files changed, 21 insertions(+), 79 deletions(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 53948d1a0..63235df81 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -71,7 +71,7 @@
 from supervision.geometry.utils import get_polygon_center
 from supervision.keypoint.annotate import SkeletonAnnotator, VertexAnnotator
 from supervision.keypoint.core import KeyPoints
-from supervision.keypoint.skeletons import KnownSkeletons, Skeleton
+from supervision.keypoint.skeletons import Skeleton
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
 from supervision.utils.conversion import cv2_to_pillow, pillow_to_cv2
diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index 802199f39..b3a29b4a1 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Optional
+from typing import Optional, List, Tuple
 
 import cv2
 import numpy as np
@@ -7,7 +7,7 @@
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color
 from supervision.keypoint.core import KeyPoints
-from supervision.keypoint.skeletons import KnownSkeletons, Skeleton
+from supervision.keypoint.skeletons import resolve_skeleton_by_vertex_count
 from supervision.utils.conversion import convert_for_annotation_method
 
 
@@ -57,7 +57,7 @@ def __init__(
         self,
         color: Color = Color.ROBOFLOW,
         thickness: int = 2,
-        skeleton: Optional[Skeleton] = None,
+        skeleton: Optional[List[Tuple[int, int]]] = None,
     ) -> None:
         """
         Draw the lines between points of the image.
@@ -83,9 +83,9 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         for xy in xy_all:
             skeleton = self.skeleton
             if not skeleton:
-                skeleton = KnownSkeletons().get_skeleton(len(xy))
+                skeleton = resolve_skeleton_by_vertex_count(len(xy))
 
-            for class_a, class_b in skeleton.limbs:
+            for class_a, class_b in skeleton:
                 xy_a = xy[class_a - 1]
                 xy_b = xy[class_b - 1]
                 missing_a = np.allclose(xy_a, 0)
diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index dd8c7ec83..31ddbab7a 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -1,24 +1,9 @@
-from typing import Dict, List, Tuple
+from enum import Enum
+from typing import Optional, Tuple, List
 
 
-class Skeleton:
-    """
-    The `Skeleton` class connects keypoints to form a skeleton.
-
-    Args:
-        limbs: (List[Tuple[int, int]]): List of (`class_id_1`,
-        `class_id_2`) representing connected points of the skeleton.
-    """
-
-    limbs: List[Tuple[int, int]]
-
-    def __init__(self, limbs: List[Tuple[int, int]]):
-        self.limbs = limbs
-
-
-NO_SKELETON = Skeleton([])
-YOLO_V8_SKELETON = Skeleton(
-    [
+class Skeleton(Enum):
+    COCO = [
         (1, 2),
         (1, 3),
         (2, 3),
@@ -37,61 +22,18 @@ def __init__(self, limbs: List[Tuple[int, int]]):
         (16, 14),
         (17, 15),
     ]
-)
-
-
-def _make_sequential_skeleton(limb_count: int) -> Skeleton:
-    """
-    Create a skeleton where neighboring keypoints are connected sequentially.
-
-    Args:
-        limb_count (int): The number of limbs to connect.
-
-    Returns:
-        Skeleton: The skeleton connecting all keypoints.
-    """
-    limbs = []
-    for i in range(0, limb_count - 1):
-        limbs.append((i, i + 1))
-    limbs.append((0, limb_count - 1))
-    return Skeleton(limbs)
-
-
-class KnownSkeletons:
-    """
-    Helps automatically determine which skeleton to use.
-
-    The `KnownSkeletons` class contains a collection of predefined skeletons
-    for various keypoint models, to be distinguished by limb counts.
-
-    Example:
-        # Suppose you have a model returning 15 keypoints.
-        skeleton = KnownSkeletons().get_skeleton(15)
-    """
-
-    _instance = None
-    _skeletons: Dict[int, Skeleton] = {}
-
-    def __new__(cls):
-        if cls._instance is None:
-            cls._instance = super(KnownSkeletons, cls).__new__(cls)
-        return cls._instance
 
-    def add_skeleton(self, skeleton: Skeleton) -> None:
-        len_limbs = len(skeleton.limbs)
-        if len_limbs in self._skeletons:
-            raise ValueError(f"A skeleton with {len_limbs} limbs already exists")
-        self._skeletons[len_limbs] = skeleton
 
-    def get_skeleton(self, limb_count: int) -> Skeleton:
-        if limb_count not in self._skeletons:
-            print(
-                f"Warning: No skeleton found with {limb_count} limbs. "
-                f"Will create one now."
-            )
-            self.add_skeleton(_make_sequential_skeleton(limb_count))
-        return self._skeletons[limb_count]
+def resolve_skeleton_by_vertex_count(count: int) -> Optional[List[Tuple[int, int]]]:
+    for skeleton in Skeleton:
+        unique_vertices = set(vertex for edge in skeleton.value for vertex in edge)
+        if len(unique_vertices) == count:
+            return skeleton.value
+    return None
 
 
-KnownSkeletons().add_skeleton(NO_SKELETON)
-KnownSkeletons().add_skeleton(YOLO_V8_SKELETON)
+def resolve_skeleton_by_edge_count(count: int) -> Optional[List[Tuple[int, int]]]:
+    for skeleton in Skeleton:
+        if len(skeleton.value) == count:
+            return skeleton.value
+    return None

From 9ad35bcfb9b46daa47ece8a8c815217048a15d07 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 23 Apr 2024 22:44:00 +0000
Subject: [PATCH 167/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/keypoint/annotate.py  | 2 +-
 supervision/keypoint/skeletons.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index b3a29b4a1..adae6745e 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Optional, List, Tuple
+from typing import List, Optional, Tuple
 
 import cv2
 import numpy as np
diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index 31ddbab7a..d2882f1bf 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Optional, Tuple, List
+from typing import List, Optional, Tuple
 
 
 class Skeleton(Enum):

From d8681b8b4f1277b9f5da5a43b97c2561136717b2 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 24 Apr 2024 09:51:40 +0300
Subject: [PATCH 168/188] remove xy_all, turn to `for xy in keypoints.xy`

---
 supervision/keypoint/annotate.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index adae6745e..15f0eb4ee 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -38,8 +38,7 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
 
-        xy_all = keypoints.xy
-        for xy in xy_all:
+        for xy in keypoints.xy:
             for x, y in xy:
                 cv2.circle(
                     img=scene,
@@ -77,10 +76,10 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
         if keypoints.class_id is None:
-            raise ValueError("KeyPoints must have class_id to annotate a skeleton")
+            raise ValueError(
+                "KeyPoints must have class_id to annotate a skeleton")
 
-        xy_all = keypoints.xy
-        for xy in xy_all:
+        for xy in keypoints.xy:
             skeleton = self.skeleton
             if not skeleton:
                 skeleton = resolve_skeleton_by_vertex_count(len(xy))

From 0749efed8f38273ab03b66274091d149746953f6 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 06:52:17 +0000
Subject: [PATCH 169/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/keypoint/annotate.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index 15f0eb4ee..1589f02ef 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -76,8 +76,7 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
         if keypoints.class_id is None:
-            raise ValueError(
-                "KeyPoints must have class_id to annotate a skeleton")
+            raise ValueError("KeyPoints must have class_id to annotate a skeleton")
 
         for xy in keypoints.xy:
             skeleton = self.skeleton

From 1c27bf7fea1173f2a72088036925f5802ff3b604 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 24 Apr 2024 12:44:29 +0300
Subject: [PATCH 170/188] EdgeAnnotator, warn and not crash when None

---
 supervision/__init__.py           |  2 +-
 supervision/keypoint/annotate.py  | 24 +++++++++++++-----------
 supervision/keypoint/skeletons.py |  3 ++-
 3 files changed, 16 insertions(+), 13 deletions(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 63235df81..b716275d5 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -69,7 +69,7 @@
 )
 from supervision.geometry.core import Point, Position, Rect
 from supervision.geometry.utils import get_polygon_center
-from supervision.keypoint.annotate import SkeletonAnnotator, VertexAnnotator
+from supervision.keypoint.annotate import EdgeAnnotator, VertexAnnotator
 from supervision.keypoint.core import KeyPoints
 from supervision.keypoint.skeletons import Skeleton
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index 1589f02ef..49c07bd0b 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -1,5 +1,6 @@
 from abc import ABC, abstractmethod
 from typing import List, Optional, Tuple
+from logging import warn
 
 import cv2
 import numpy as np
@@ -51,12 +52,12 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         return scene
 
 
-class SkeletonAnnotator(BaseKeyPointAnnotator):
+class EdgeAnnotator(BaseKeyPointAnnotator):
     def __init__(
         self,
         color: Color = Color.ROBOFLOW,
         thickness: int = 2,
-        skeleton: Optional[List[Tuple[int, int]]] = None,
+        edges: Optional[List[Tuple[int, int]]] = None,
     ) -> None:
         """
         Draw the lines between points of the image.
@@ -64,26 +65,27 @@ def __init__(
         Args:
             color (Color, optional): The color of the lines.
             thickness (int, optional): The thickness of the lines.
-            skeleton (Skeleton, optional): The skeleton to draw.
+            edge (Optional[List[Tuple[int, int]]]): The edges to draw.
                 If set to `None`, will attempt to select automatically.
         """
         self.color = color
         self.thickness = thickness
-        self.skeleton = skeleton
+        self.edges = edges
 
     @convert_for_annotation_method
     def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         if len(keypoints) == 0:
             return scene
-        if keypoints.class_id is None:
-            raise ValueError("KeyPoints must have class_id to annotate a skeleton")
 
         for xy in keypoints.xy:
-            skeleton = self.skeleton
-            if not skeleton:
-                skeleton = resolve_skeleton_by_vertex_count(len(xy))
-
-            for class_a, class_b in skeleton:
+            edges = self.edges
+            if not edges:
+                edges = resolve_skeleton_by_vertex_count(len(xy))
+            if not edges:
+                warn(f"No skeleton found with {len(xy)} vertices")
+                return scene
+
+            for class_a, class_b in edges:
                 xy_a = xy[class_a - 1]
                 xy_b = xy[class_b - 1]
                 missing_a = np.allclose(xy_a, 0)
diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index d2882f1bf..750580ddd 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -26,7 +26,8 @@ class Skeleton(Enum):
 
 def resolve_skeleton_by_vertex_count(count: int) -> Optional[List[Tuple[int, int]]]:
     for skeleton in Skeleton:
-        unique_vertices = set(vertex for edge in skeleton.value for vertex in edge)
+        unique_vertices = set(
+            vertex for edge in skeleton.value for vertex in edge)
         if len(unique_vertices) == count:
             return skeleton.value
     return None

From 0f6ad236ebf304d7ebb86d3902c076edb1c000c4 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 09:45:44 +0000
Subject: [PATCH 171/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/keypoint/annotate.py  | 2 +-
 supervision/keypoint/skeletons.py | 3 +--
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index 49c07bd0b..b683b45f9 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -1,6 +1,6 @@
 from abc import ABC, abstractmethod
-from typing import List, Optional, Tuple
 from logging import warn
+from typing import List, Optional, Tuple
 
 import cv2
 import numpy as np
diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index 750580ddd..d2882f1bf 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -26,8 +26,7 @@ class Skeleton(Enum):
 
 def resolve_skeleton_by_vertex_count(count: int) -> Optional[List[Tuple[int, int]]]:
     for skeleton in Skeleton:
-        unique_vertices = set(
-            vertex for edge in skeleton.value for vertex in edge)
+        unique_vertices = set(vertex for edge in skeleton.value for vertex in edge)
         if len(unique_vertices) == count:
             return skeleton.value
     return None

From d1c103ee16742dc7e09e486412385f99fad6970a Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 24 Apr 2024 12:50:19 +0300
Subject: [PATCH 172/188] Best skeleton cache ever, obviously

---
 supervision/keypoint/annotate.py  |  4 ++--
 supervision/keypoint/skeletons.py | 22 ++++++++++------------
 2 files changed, 12 insertions(+), 14 deletions(-)

diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index b683b45f9..1e7cf1936 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -8,7 +8,7 @@
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color
 from supervision.keypoint.core import KeyPoints
-from supervision.keypoint.skeletons import resolve_skeleton_by_vertex_count
+from supervision.keypoint.skeletons import skeletons_by_vertex_count
 from supervision.utils.conversion import convert_for_annotation_method
 
 
@@ -80,7 +80,7 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         for xy in keypoints.xy:
             edges = self.edges
             if not edges:
-                edges = resolve_skeleton_by_vertex_count(len(xy))
+                edges = skeletons_by_vertex_count.get(len(xy))
             if not edges:
                 warn(f"No skeleton found with {len(xy)} vertices")
                 return scene
diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index d2882f1bf..373b8fcc7 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -1,5 +1,7 @@
 from enum import Enum
-from typing import List, Optional, Tuple
+from typing import Dict, List, Tuple
+
+Edges = List[Tuple[int, int]]
 
 
 class Skeleton(Enum):
@@ -24,16 +26,12 @@ class Skeleton(Enum):
     ]
 
 
-def resolve_skeleton_by_vertex_count(count: int) -> Optional[List[Tuple[int, int]]]:
-    for skeleton in Skeleton:
-        unique_vertices = set(vertex for edge in skeleton.value for vertex in edge)
-        if len(unique_vertices) == count:
-            return skeleton.value
-    return None
+skeletons_by_edge_count: Dict[int, Edges] = {}
+skeletons_by_vertex_count: Dict[int, Edges] = {}
 
+for skeleton in Skeleton:
+    skeletons_by_edge_count[len(skeleton.value)] = skeleton.value
 
-def resolve_skeleton_by_edge_count(count: int) -> Optional[List[Tuple[int, int]]]:
-    for skeleton in Skeleton:
-        if len(skeleton.value) == count:
-            return skeleton.value
-    return None
+    unique_vertices = set(
+        vertex for edge in skeleton.value for vertex in edge)
+    skeletons_by_vertex_count[len(unique_vertices)] = skeleton.value

From 08d7a6b4cdc5646888ebfe032e4f1a432898380b Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 09:53:33 +0000
Subject: [PATCH 173/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/keypoint/skeletons.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index 373b8fcc7..1c785d785 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -32,6 +32,5 @@ class Skeleton(Enum):
 for skeleton in Skeleton:
     skeletons_by_edge_count[len(skeleton.value)] = skeleton.value
 
-    unique_vertices = set(
-        vertex for edge in skeleton.value for vertex in edge)
+    unique_vertices = set(vertex for edge in skeleton.value for vertex in edge)
     skeletons_by_vertex_count[len(unique_vertices)] = skeleton.value

From 741309fd099f47e89a748a00784b8f9c2c6d3612 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 24 Apr 2024 13:13:10 +0300
Subject: [PATCH 174/188] Remove Skeleton from __init__, small renames, consts

---
 docs/keypoint/annotate.md         | 2 +-
 supervision/__init__.py           | 1 -
 supervision/keypoint/annotate.py  | 4 ++--
 supervision/keypoint/skeletons.py | 8 ++++----
 4 files changed, 7 insertions(+), 8 deletions(-)

diff --git a/docs/keypoint/annotate.md b/docs/keypoint/annotate.md
index 476ae9186..4f9cd8615 100644
--- a/docs/keypoint/annotate.md
+++ b/docs/keypoint/annotate.md
@@ -7,4 +7,4 @@ status: new
 
 :::supervision.keypoint.annotate.VertexAnnotator
 
-:::supervision.keypoint.annotate.SkeletonAnnotator
+:::supervision.keypoint.annotate.EdgeAnnotator
diff --git a/supervision/__init__.py b/supervision/__init__.py
index b716275d5..053e3718c 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -71,7 +71,6 @@
 from supervision.geometry.utils import get_polygon_center
 from supervision.keypoint.annotate import EdgeAnnotator, VertexAnnotator
 from supervision.keypoint.core import KeyPoints
-from supervision.keypoint.skeletons import Skeleton
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
 from supervision.utils.conversion import cv2_to_pillow, pillow_to_cv2
diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
index 1e7cf1936..b1f3530f2 100644
--- a/supervision/keypoint/annotate.py
+++ b/supervision/keypoint/annotate.py
@@ -8,7 +8,7 @@
 from supervision.annotators.base import ImageType
 from supervision.draw.color import Color
 from supervision.keypoint.core import KeyPoints
-from supervision.keypoint.skeletons import skeletons_by_vertex_count
+from supervision.keypoint.skeletons import SKELETONS_BY_VERTEX_COUNT
 from supervision.utils.conversion import convert_for_annotation_method
 
 
@@ -80,7 +80,7 @@ def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
         for xy in keypoints.xy:
             edges = self.edges
             if not edges:
-                edges = skeletons_by_vertex_count.get(len(xy))
+                edges = SKELETONS_BY_VERTEX_COUNT.get(len(xy))
             if not edges:
                 warn(f"No skeleton found with {len(xy)} vertices")
                 return scene
diff --git a/supervision/keypoint/skeletons.py b/supervision/keypoint/skeletons.py
index 1c785d785..6c1108541 100644
--- a/supervision/keypoint/skeletons.py
+++ b/supervision/keypoint/skeletons.py
@@ -26,11 +26,11 @@ class Skeleton(Enum):
     ]
 
 
-skeletons_by_edge_count: Dict[int, Edges] = {}
-skeletons_by_vertex_count: Dict[int, Edges] = {}
+SKELETONS_BY_EDGE_COUNT: Dict[int, Edges] = {}
+SKELETONS_BY_VERTEX_COUNT: Dict[int, Edges] = {}
 
 for skeleton in Skeleton:
-    skeletons_by_edge_count[len(skeleton.value)] = skeleton.value
+    SKELETONS_BY_EDGE_COUNT[len(skeleton.value)] = skeleton.value
 
     unique_vertices = set(vertex for edge in skeleton.value for vertex in edge)
-    skeletons_by_vertex_count[len(unique_vertices)] = skeleton.value
+    SKELETONS_BY_VERTEX_COUNT[len(unique_vertices)] = skeleton.value

From 4b89bece4fdc849a7ed7f0e1e1bf49bb1c12f17e Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 24 Apr 2024 14:58:52 +0300
Subject: [PATCH 175/188] Fix keypoint crash with no detections

---
 supervision/keypoint/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/keypoint/core.py b/supervision/keypoint/core.py
index aca50ad5b..6749f8452 100644
--- a/supervision/keypoint/core.py
+++ b/supervision/keypoint/core.py
@@ -135,7 +135,7 @@ def from_ultralytics(cls, ultralytics_results) -> KeyPoints:
             keypoints = sv.KeyPoints.from_ultralytics(result)
             ```
         """
-        if len(ultralytics_results.keypoints.xy) == 0:
+        if ultralytics_results.keypoints.xy.numel() == 0:
             return cls.empty()
 
         xy = ultralytics_results.keypoints.xy.cpu().numpy()

From 48809c13322553ab6b87bf05aa10987e472e3f08 Mon Sep 17 00:00:00 2001
From: Linas Kondrackis <linas.ko+dev@skiff.com>
Date: Wed, 24 Apr 2024 16:37:41 +0300
Subject: [PATCH 176/188] Add a basic from_supervision function to KeyPoints

---
 supervision/keypoint/core.py | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/supervision/keypoint/core.py b/supervision/keypoint/core.py
index 6749f8452..87f0a20be 100644
--- a/supervision/keypoint/core.py
+++ b/supervision/keypoint/core.py
@@ -110,6 +110,37 @@ def __eq__(self, other: KeyPoints) -> bool:
             ]
         )
 
+    @classmethod
+    def from_inference(cls, inference_result: dict) -> KeyPoints:
+        if not inference_result.get("predictions"):
+            return cls.empty()
+
+        xy = []
+        confidence = []
+        class_id = []
+        class_names = []
+
+        for prediction in inference_result["predictions"]:
+            prediction_xy = []
+            prediction_confidence = []
+            for keypoint in prediction["keypoints"]:
+                prediction_xy.append([keypoint["x"], keypoint["y"]])
+                prediction_confidence.append(keypoint["confidence"])
+            xy.append(prediction_xy)
+            confidence.append(prediction_confidence)
+
+            class_id.append(prediction["class_id"])
+            class_names.append(prediction["class"])
+
+        data = {CLASS_NAME_DATA_FIELD: np.array(class_names)}
+
+        return cls(
+            xy=np.array(xy, dtype=np.float32),
+            confidence=np.array(confidence, dtype=np.float32),
+            class_id=np.array(class_id, dtype=int),
+            data=data,
+        )
+
     @classmethod
     def from_ultralytics(cls, ultralytics_results) -> KeyPoints:
         """

From 77793571b094f646eaec2bebd99369e203b87159 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 15:39:08 +0200
Subject: [PATCH 177/188] major docs refactor

---
 README.md                                    |   7 +-
 docs/deprecated.md                           |   2 +-
 docs/{ => detection}/annotators.md           |   0
 docs/detection/metrics.md                    |  21 +++
 docs/draw/color.md                           |  13 --
 docs/how_to/detect_and_annotate.md           |  28 +--
 docs/how_to/detect_small_objects.md          |  16 +-
 docs/keypoint/annotate.md                    |  10 --
 docs/keypoint/annotators.md                  |  10 ++
 docs/metrics/detection.md                    |  22 ---
 docs/{draw/utils.md => utils/draw.md}        |  13 ++
 docs/{geometry/core.md => utils/geometry.md} |   0
 mkdocs.yml                                   |  22 +--
 supervision/__init__.py                      |   2 +-
 supervision/assets/list.py                   |   5 +
 supervision/detection/core.py                | 127 ++++++++------
 supervision/keypoint/annotate.py             | 104 ------------
 supervision/keypoint/annotators.py           | 170 +++++++++++++++++++
 supervision/keypoint/core.py                 |  43 ++---
 19 files changed, 348 insertions(+), 267 deletions(-)
 rename docs/{ => detection}/annotators.md (100%)
 create mode 100644 docs/detection/metrics.md
 delete mode 100644 docs/draw/color.md
 delete mode 100644 docs/keypoint/annotate.md
 create mode 100644 docs/keypoint/annotators.md
 delete mode 100644 docs/metrics/detection.md
 rename docs/{draw/utils.md => utils/draw.md} (83%)
 rename docs/{geometry/core.md => utils/geometry.md} (100%)
 delete mode 100644 supervision/keypoint/annotate.py
 create mode 100644 supervision/keypoint/annotators.py

diff --git a/README.md b/README.md
index beed655c9..0894a6a48 100644
--- a/README.md
+++ b/README.md
@@ -71,16 +71,15 @@ len(detections)
     ```python
     import cv2
     import supervision as sv
-    from inference.models.utils import get_roboflow_model
+    from inference import get_model
 
     image = cv2.imread(...)
-    model = get_roboflow_model(model_id="yolov8s-640", api_key=<ROBOFLOW API KEY>)
+    model = get_model(model_id="yolov8s-640", api_key=<ROBOFLOW API KEY>)
     result = model.infer(image)[0]
     detections = sv.Detections.from_inference(result)
 
     len(detections)
-    # 5
-
+    # 5
     ```
 
 </details>
diff --git a/docs/deprecated.md b/docs/deprecated.md
index 35c332e4f..cc1e96498 100644
--- a/docs/deprecated.md
+++ b/docs/deprecated.md
@@ -12,7 +12,7 @@ These features are phased out due to better alternatives or potential issues in
 - The method `Color.green()` is deprecated and will be removed in `supervision-0.22.0`. Use the constant `Color.GREEN` instead.
 - The method `Color.blue()` is deprecated and will be removed in `supervision-0.22.0`. Use the constant `Color.BLUE` instead.
 - The method [`ColorPalette.default()`](draw/color.md/#supervision.draw.color.ColorPalette.default) is deprecated and will be removed in `supervision-0.22.0`. Use the constant [`ColorPalette.DEFAULT`](draw/color.md/#supervision.draw.color.ColorPalette.DEFAULT) instead.
-- `BoxAnnotator` is deprecated and will be removed in `supervision-0.22.0`. Use [`BoundingBoxAnnotator`](annotators.md/#supervision.annotators.core.BoundingBoxAnnotator) and [`LabelAnnotator`](annotators.md/#supervision.annotators.core.LabelAnnotator) instead.
+- `BoxAnnotator` is deprecated and will be removed in `supervision-0.22.0`. Use [`BoundingBoxAnnotator`](detection/annotators.md/#supervision.annotators.core.BoundingBoxAnnotator) and [`LabelAnnotator`](detection/annotators.md/#supervision.annotators.core.LabelAnnotator) instead.
 - The method [`FPSMonitor.__call__`](utils/video.md/#supervision.utils.video.FPSMonitor.__call__) is deprecated and will be removed in `supervision-0.22.0`. Use the attribute [`FPSMonitor.fps`](utils/video.md/#supervision.utils.video.FPSMonitor.fps) instead.
 - The `track_buffer`, `track_thresh`, and `match_thresh` parameters in [`ByterTrack`](trackers.md/#supervision.tracker.byte_tracker.core.ByteTrack) are deprecated and will be removed in `supervision-0.23.0`. Use `lost_track_buffer,` `track_activation_threshold`, and `minimum_matching_threshold` instead.
 - The `triggering_position ` parameter in [`sv.PolygonZone`](detection/tools/polygon_zone.md/#supervision.detection.tools.polygon_zone.PolygonZone) is deprecated and will be removed in `supervision-0.23.0`. Use `triggering_anchors ` instead.
diff --git a/docs/annotators.md b/docs/detection/annotators.md
similarity index 100%
rename from docs/annotators.md
rename to docs/detection/annotators.md
diff --git a/docs/detection/metrics.md b/docs/detection/metrics.md
new file mode 100644
index 000000000..981f399cd
--- /dev/null
+++ b/docs/detection/metrics.md
@@ -0,0 +1,21 @@
+---
+comments: true
+---
+
+# Metrics
+
+!!! warning
+
+    Evaluation API is still fluid and may change. If you use Evaluation API in your project until further notice, freeze the `supervision` version in your `requirements.txt` or `setup.py`.
+
+<div class="md-typeset">
+    <h2><a href="#supervision.detection.metrics.ConfusionMatrix">ConfusionMatrix</a></h2>
+</div>
+
+:::supervision.metrics.detection.ConfusionMatrix
+
+<div class="md-typeset">
+    <h2><a href="#supervision.detection.metrics.MeanAveragePrecision">MeanAveragePrecision</a></h2>
+</div>
+
+:::supervision.metrics.detection.MeanAveragePrecision
diff --git a/docs/draw/color.md b/docs/draw/color.md
deleted file mode 100644
index c702814ab..000000000
--- a/docs/draw/color.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-comments: true
----
-
-# Color
-
-:::supervision.draw.color.Color
-
-<div class="md-typeset">
-  <h2>ColorPalette</h2>
-</div>
-
-:::supervision.draw.color.ColorPalette
diff --git a/docs/how_to/detect_and_annotate.md b/docs/how_to/detect_and_annotate.md
index adea95cf7..a9a4405e2 100644
--- a/docs/how_to/detect_and_annotate.md
+++ b/docs/how_to/detect_and_annotate.md
@@ -27,7 +27,7 @@ model.
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     ```
 
@@ -38,7 +38,7 @@ model.
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image)[0]
     ```
 
@@ -52,7 +52,7 @@ model.
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<SOURCE_IMAGE_APTH>)
+    image = Image.open(<SOURCE_IMAGE_PATH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -78,7 +78,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
     ```
@@ -93,7 +93,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
     ```
@@ -111,7 +111,7 @@ Now that we have predictions from a model, we can load them into Supervision.
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<SOURCE_IMAGE_APTH>)
+    image = Image.open(<SOURCE_IMAGE_PATH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -146,7 +146,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
@@ -167,7 +167,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<SOURCE_IMAGE_APTH>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
 
@@ -191,7 +191,7 @@ Finally, we can annotate the image with the predictions. Since we are working wi
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<SOURCE_IMAGE_APTH>)
+    image = Image.open(<SOURCE_IMAGE_PATH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -230,7 +230,7 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
     from inference import get_model
 
     model = get_model(model_id="yolov8n-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
@@ -257,7 +257,7 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
     from ultralytics import YOLO
 
     model = YOLO("yolov8n.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
 
@@ -287,7 +287,7 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<PATH TO IMAGE>)
+    image = Image.open(<SOURCE_IMAGE_PATH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -334,7 +334,7 @@ that will allow you to draw masks instead of boxes.
     from inference import get_model
 
     model = get_model(model_id="yolov8n-seg-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
@@ -355,7 +355,7 @@ that will allow you to draw masks instead of boxes.
     from ultralytics import YOLO
 
     model = YOLO("yolov8n-seg.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
 
diff --git a/docs/how_to/detect_small_objects.md b/docs/how_to/detect_small_objects.md
index 9f35a96c5..e2d023284 100644
--- a/docs/how_to/detect_small_objects.md
+++ b/docs/how_to/detect_small_objects.md
@@ -28,7 +28,7 @@ size relative to the image resolution.
     from inference import get_model
 
     model = get_model(model_id="yolov8x-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
@@ -49,7 +49,7 @@ size relative to the image resolution.
     from ultralytics import YOLO
 
     model = YOLO("yolov8x.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image)[0]
     detections = sv.Detections.from_ultralytics(results)
 
@@ -73,7 +73,7 @@ size relative to the image resolution.
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = Image.open(<PATH TO IMAGE>)
+    image = Image.open(<SOURCE_IMAGE_PATH>)
     inputs = processor(images=image, return_tensors="pt")
 
     with torch.no_grad():
@@ -116,7 +116,7 @@ is less effective for ultra-high-resolution images (4K and above).
     from inference import get_model
 
     model = get_model(model_id="yolov8x-1280")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model.infer(image)[0]
     detections = sv.Detections.from_inference(results)
 
@@ -137,7 +137,7 @@ is less effective for ultra-high-resolution images (4K and above).
     from ultralytics import YOLO
 
     model = YOLO("yolov8x.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
     results = model(image, imgsz=1280)[0]
     detections = sv.Detections.from_ultralytics(results)
 
@@ -171,7 +171,7 @@ objects within each, and aggregating the results.
     from inference import get_model
 
     model = get_model(model_id="yolov8x-640")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
 
     def callback(image_slice: np.ndarray) -> sv.Detections:
         results = model.infer(image_slice)[0]
@@ -198,7 +198,7 @@ objects within each, and aggregating the results.
     from ultralytics import YOLO
 
     model = YOLO("yolov8x.pt")
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
 
     def callback(image_slice: np.ndarray) -> sv.Detections:
         result = model(image_slice)[0]
@@ -229,7 +229,7 @@ objects within each, and aggregating the results.
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
-    image = cv2.imread(<PATH TO IMAGE>)
+    image = cv2.imread(<SOURCE_IMAGE_PATH>)
 
     def callback(image_slice: np.ndarray) -> sv.Detections:
         image_slice = cv2.cvtColor(image_slice, cv2.COLOR_BGR2RGB)
diff --git a/docs/keypoint/annotate.md b/docs/keypoint/annotate.md
deleted file mode 100644
index 4f9cd8615..000000000
--- a/docs/keypoint/annotate.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-comments: true
-status: new
----
-
-# Annotate
-
-:::supervision.keypoint.annotate.VertexAnnotator
-
-:::supervision.keypoint.annotate.EdgeAnnotator
diff --git a/docs/keypoint/annotators.md b/docs/keypoint/annotators.md
new file mode 100644
index 000000000..3efc5b032
--- /dev/null
+++ b/docs/keypoint/annotators.md
@@ -0,0 +1,10 @@
+---
+comments: true
+status: new
+---
+
+# Annotators
+
+:::supervision.keypoint.annotators.VertexAnnotator
+
+:::supervision.keypoint.annotators.EdgeAnnotator
diff --git a/docs/metrics/detection.md b/docs/metrics/detection.md
deleted file mode 100644
index a953ba9b2..000000000
--- a/docs/metrics/detection.md
+++ /dev/null
@@ -1,22 +0,0 @@
----
-comments: true
----
-
-#  Detection Metrics
-
-!!! warning
-
-    Evaluation API is still fluid and may change. If you use Evaluation API in your project until further notice, freeze the
-    `supervision` version in your `requirements.txt` or `setup.py`.
-
-<div class="md-typeset">
-    <h2><a href="#supervision.metrics.detection.ConfusionMatrix">ConfusionMatrix</a></h2>
-</div>
-
-:::supervision.metrics.detection.ConfusionMatrix
-
-<div class="md-typeset">
-    <h2><a href="#supervision.annotators.core.MeanAveragePrecision">MeanAveragePrecision</a></h2>
-</div>
-
-:::supervision.metrics.detection.MeanAveragePrecision
diff --git a/docs/draw/utils.md b/docs/utils/draw.md
similarity index 83%
rename from docs/draw/utils.md
rename to docs/utils/draw.md
index 7975952c3..7b47a6a76 100644
--- a/docs/draw/utils.md
+++ b/docs/utils/draw.md
@@ -51,3 +51,16 @@ comments: true
 </div>
 
 :::supervision.draw.utils.calculate_optimal_line_thickness
+
+<div class="md-typeset">
+  <h2>Color</h2>
+</div>
+
+:::supervision.draw.color.Color
+
+<div class="md-typeset">
+  <h2>ColorPalette</h2>
+</div>
+
+:::supervision.draw.color.ColorPalette
+
diff --git a/docs/geometry/core.md b/docs/utils/geometry.md
similarity index 100%
rename from docs/geometry/core.md
rename to docs/utils/geometry.md
diff --git a/mkdocs.yml b/mkdocs.yml
index 256c6bef4..cf206a82e 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -44,15 +44,16 @@ nav:
       - Track Objects: how_to/track_objects.md
 
   - API:
-    - Annotators: annotators.md
-    - Classifications:
-        - Core: classification/core.md
-    - Detections:
+    - Detection and Segmentation:
         - Core: detection/core.md
+        - Annotators: detection/annotators.md
+        - Metrics: detection/metrics.md
         - Utils: detection/utils.md
-    - KeyPoints:
+    - Keypoint Detection:
         - Core: keypoint/core.md
-        - Annotators: keypoint/annotate.md
+        - Annotators: keypoint/annotators.md
+    - Classification:
+        - Core: classification/core.md
     - Tools:
         - Line Zone: detection/tools/line_zone.md
         - Polygon Zone: detection/tools/polygon_zone.md
@@ -61,19 +62,14 @@ nav:
         - Save Detections: detection/tools/save_detections.md
     - Trackers: trackers.md
     - Datasets: datasets.md
-    - Metrics:
-      - Object Detection: metrics/detection.md
-    - Draw:
-        - Color: draw/color.md
-        - Utils: draw/utils.md
-    - Geometry:
-        - Position: geometry/core.md
     - Utils:
         - Video: utils/video.md
         - Image: utils/image.md
         - Iterables: utils/iterables.md
         - Notebook: utils/notebook.md
         - File: utils/file.md
+        - Draw: utils/draw.md
+        - Geometry: utils/geometry.md
     - Assets: assets.md
   - Cookbooks: cookbooks.md
   - Contribute:
diff --git a/supervision/__init__.py b/supervision/__init__.py
index 053e3718c..bb5265141 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -69,7 +69,7 @@
 )
 from supervision.geometry.core import Point, Position, Rect
 from supervision.geometry.utils import get_polygon_center
-from supervision.keypoint.annotate import EdgeAnnotator, VertexAnnotator
+from supervision.keypoint.annotators import EdgeAnnotator, VertexAnnotator
 from supervision.keypoint.core import KeyPoints
 from supervision.metrics.detection import ConfusionMatrix, MeanAveragePrecision
 from supervision.tracker.byte_tracker.core import ByteTrack
diff --git a/supervision/assets/list.py b/supervision/assets/list.py
index 77b1e461a..0866431a8 100644
--- a/supervision/assets/list.py
+++ b/supervision/assets/list.py
@@ -29,6 +29,7 @@ class VideoAssets(Enum):
     MARKET_SQUARE = "market-square.mp4"
     PEOPLE_WALKING = "people-walking.mp4"
     BEACH = "beach-1.mp4"
+    BASKETBALL = "basketball-1.mp4"
 
     @classmethod
     def list(cls):
@@ -68,4 +69,8 @@ def list(cls):
         f"{BASE_VIDEO_URL}{VideoAssets.BEACH.value}",
         "4175d42fec4d450ed081523fd39e0cf8",
     ),
+    VideoAssets.BASKETBALL.value: (
+        f"{BASE_VIDEO_URL}{VideoAssets.BASKETBALL.value}",
+        "60d94a3c7c47d16f09d342b088012ecc",
+    ),
 }
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 53286375a..3e3d01140 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -27,34 +27,68 @@
 @dataclass
 class Detections:
     """
-    The `sv.Detections` allows you to convert results from a variety of object detection
-    and segmentation models into a single, unified format. The `sv.Detections` class
-    enables easy data manipulation and filtering, and provides a consistent API for
-    Supervision's tools like trackers, annotators, and zones.
+    The `sv.Detections` class in the Supervision library standardizes results from
+    various object detection and segmentation models into a consistent format. This
+    class simplifies data manipulation and filtering, providing a uniform API for
+    integration with Supervision [trackers](/trackers/), [annotators](/detection/annotators/), and [tools](/detection/tools/line_zone/).
 
-    ```python
-    import cv2
-    import supervision as sv
-    from ultralytics import YOLO
+    === "Inference"
 
-    image = cv2.imread(<SOURCE_IMAGE_PATH>)
-    model = YOLO('yolov8s.pt')
-    annotator = sv.BoundingBoxAnnotator()
+        Use [`sv.Detections.from_inference`](/detection/core/#supervision.detection.core.Detections.from_inference) method, which accepts model results from both detection and segmentation models.
 
-    result = model(image)[0]
-    detections = sv.Detections.from_ultralytics(result)
+        ```python
+        import cv2
+        import supervision as sv
+        from inference import get_model
 
-    annotated_image = annotator.annotate(image, detections)
-    ```
+        model = get_model(model_id="yolov8n-640")
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        results = model.infer(image)[0]
+        detections = sv.Detections.from_inference(results)
+        ```
 
-    !!! tip
+    === "Ultralytics"
 
-        In `sv.Detections`, detection data is categorized into two main field types:
-        fixed and custom. The fixed fields include `xyxy`, `mask`, `confidence`,
-        `class_id`, and `tracker_id`. For any additional data requirements, custom
-        fields come into play, stored in the data field. These custom fields are easily
-        accessible using the `detections[<FIELD_NAME>]` syntax, providing flexibility
-        for diverse data handling needs.
+        Use [`sv.Detections.from_ultralytics`](/detection/core/#supervision.detection.core.Detections.from_ultralytics) method, which accepts model results from both detection and segmentation models.
+
+        ```python
+        import cv2
+        import supervision as sv
+        from ultralytics import YOLO
+
+        model = YOLO("yolov8n.pt")
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        results = model(image)[0]
+        detections = sv.Detections.from_ultralytics(results)
+        ```
+
+    === "Transformers"
+
+        Use [`sv.Detections.from_transformers`](/detection/core/#supervision.detection.core.Detections.from_transformers) method, which accepts model results from both detection and segmentation models.
+
+        ```python
+        import torch
+        import supervision as sv
+        from PIL import Image
+        from transformers import DetrImageProcessor, DetrForObjectDetection
+
+        processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+        model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+
+        image = Image.open(<SOURCE_IMAGE_PATH>)
+        inputs = processor(images=image, return_tensors="pt")
+
+        with torch.no_grad():
+            outputs = model(**inputs)
+
+        width, height = image.size
+        target_size = torch.tensor([[height, width]])
+        results = processor.post_process_object_detection(
+            outputs=outputs, target_sizes=target_size)[0]
+        detections = sv.Detections.from_transformers(
+            transformers_results=results,
+            id2label=model.config.id2label)
+        ```
 
     Attributes:
         xyxy (np.ndarray): An array of shape `(n, 4)` containing
@@ -70,14 +104,6 @@ class Detections:
         data (Dict[str, Union[np.ndarray, List]]): A dictionary containing additional
             data where each key is a string representing the data type, and the value
             is either a NumPy array or a list of corresponding data.
-
-    !!! warning
-
-        The `data` field in the `sv.Detections` class is currently in an experimental
-        phase. Please be aware that its API and functionality are subject to change in
-        future updates as we continue to refine and improve its capabilities.
-        We encourage users to experiment with this feature and provide feedback, but
-        also to be prepared for potential modifications in upcoming releases.
     """
 
     xyxy: np.ndarray
@@ -177,8 +203,8 @@ def from_yolov5(cls, yolov5_results) -> Detections:
     @classmethod
     def from_ultralytics(cls, ultralytics_results) -> Detections:
         """
-        Creates a Detections instance from a
-            [YOLOv8](https://github.com/ultralytics/ultralytics) inference result.
+        Creates a `sv.Detections` instance from a
+        [YOLOv8](https://github.com/ultralytics/ultralytics) inference result.
 
         !!! Note
 
@@ -202,10 +228,13 @@ def from_ultralytics(cls, ultralytics_results) -> Detections:
 
             image = cv2.imread(<SOURCE_IMAGE_PATH>)
             model = YOLO('yolov8s.pt')
-
-            result = model(image)[0]
-            detections = sv.Detections.from_ultralytics(result)
+            results = model(image)[0]
+            detections = sv.Detections.from_ultralytics(results)
             ```
+            
+        !!! tip
+
+            Class names values can be accessed using `detections["class_name"]`.
         """  # noqa: E501 // docs
 
         if "obb" in ultralytics_results and ultralytics_results.obb is not None:
@@ -396,11 +425,6 @@ def from_transformers(
         Creates a Detections instance from object detection or segmentation
         [Transformer](https://github.com/huggingface/transformers) inference result.
 
-        !!! note
-
-            Class names can be accessed using the key `class_name` in the returned
-            object's data attribute.
-
         Args:
             transformers_results (dict): The output of Transformers model inference. A
                 dictionary containing the `scores`, `labels`, `boxes` and `masks` keys.
@@ -437,6 +461,10 @@ class names. If provided, the resulting Detections object will contain
                 id2label=model.config.id2label
             )
             ```
+        
+        !!! tip
+
+            Class names values can be accessed using `detections["class_name"]`.
         """  # noqa: E501 // docs
 
         class_ids = transformers_results["labels"].cpu().detach().numpy().astype(int)
@@ -510,17 +538,12 @@ class IDs, and confidences of the predictions.
     @classmethod
     def from_inference(cls, roboflow_result: Union[dict, Any]) -> Detections:
         """
-        Create a Detections object from the [Roboflow](https://roboflow.com/)
+        Create a `sv.Detections` object from the [Roboflow](https://roboflow.com/)
         API inference result or the [Inference](https://inference.roboflow.com/)
         package results. This method extracts bounding boxes, class IDs,
         confidences, and class names from the Roboflow API result and encapsulates
         them into a Detections object.
 
-        !!! note
-
-            Class names can be accessed using the key `class_name` in the returned
-            object's data attribute.
-
         Args:
             roboflow_result (dict, any): The result from the
                 Roboflow API or Inference package containing predictions.
@@ -533,14 +556,18 @@ def from_inference(cls, roboflow_result: Union[dict, Any]) -> Detections:
             ```python
             import cv2
             import supervision as sv
-            from inference.models.utils import get_roboflow_model
+            from inference import get_model
 
             image = cv2.imread(<SOURCE_IMAGE_PATH>)
-            model = get_roboflow_model(model_id="yolov8s-640")
+            model = get_model(model_id="yolov8s-640")
 
             result = model.infer(image)[0]
             detections = sv.Detections.from_inference(result)
             ```
+
+        !!! tip
+
+            Class names values can be accessed using `detections["class_name"]`.
         """
         with suppress(AttributeError):
             roboflow_result = roboflow_result.dict(exclude_none=True, by_alias=True)
@@ -590,10 +617,10 @@ def from_roboflow(cls, roboflow_result: Union[dict, Any]) -> Detections:
             ```python
             import cv2
             import supervision as sv
-            from inference.models.utils import get_roboflow_model
+            from inference import get_model
 
             image = cv2.imread(<SOURCE_IMAGE_PATH>)
-            model = get_roboflow_model(model_id="yolov8s-640")
+            model = get_model(model_id="yolov8s-640")
 
             result = model.infer(image)[0]
             detections = sv.Detections.from_roboflow(result)
diff --git a/supervision/keypoint/annotate.py b/supervision/keypoint/annotate.py
deleted file mode 100644
index b1f3530f2..000000000
--- a/supervision/keypoint/annotate.py
+++ /dev/null
@@ -1,104 +0,0 @@
-from abc import ABC, abstractmethod
-from logging import warn
-from typing import List, Optional, Tuple
-
-import cv2
-import numpy as np
-
-from supervision.annotators.base import ImageType
-from supervision.draw.color import Color
-from supervision.keypoint.core import KeyPoints
-from supervision.keypoint.skeletons import SKELETONS_BY_VERTEX_COUNT
-from supervision.utils.conversion import convert_for_annotation_method
-
-
-class BaseKeyPointAnnotator(ABC):
-    @abstractmethod
-    def annotate(self, scene: ImageType, detections: KeyPoints) -> ImageType:
-        pass
-
-
-class VertexAnnotator(BaseKeyPointAnnotator):
-    def __init__(
-        self,
-        color: Color = Color.ROBOFLOW,
-        radius: int = 4,
-    ) -> None:
-        """
-        Most basic keypoint annotator.
-
-        Args:
-            color (Color, optional): The color of the keypoint.
-            radius (int, optional): The radius of the keypoint.
-        """
-        self.color = color
-        self.radius = radius
-
-    @convert_for_annotation_method
-    def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
-        if len(keypoints) == 0:
-            return scene
-
-        for xy in keypoints.xy:
-            for x, y in xy:
-                cv2.circle(
-                    img=scene,
-                    center=(int(x), int(y)),
-                    radius=self.radius,
-                    color=self.color.as_bgr(),
-                    thickness=-1,
-                )
-
-        return scene
-
-
-class EdgeAnnotator(BaseKeyPointAnnotator):
-    def __init__(
-        self,
-        color: Color = Color.ROBOFLOW,
-        thickness: int = 2,
-        edges: Optional[List[Tuple[int, int]]] = None,
-    ) -> None:
-        """
-        Draw the lines between points of the image.
-
-        Args:
-            color (Color, optional): The color of the lines.
-            thickness (int, optional): The thickness of the lines.
-            edge (Optional[List[Tuple[int, int]]]): The edges to draw.
-                If set to `None`, will attempt to select automatically.
-        """
-        self.color = color
-        self.thickness = thickness
-        self.edges = edges
-
-    @convert_for_annotation_method
-    def annotate(self, scene: ImageType, keypoints: KeyPoints) -> ImageType:
-        if len(keypoints) == 0:
-            return scene
-
-        for xy in keypoints.xy:
-            edges = self.edges
-            if not edges:
-                edges = SKELETONS_BY_VERTEX_COUNT.get(len(xy))
-            if not edges:
-                warn(f"No skeleton found with {len(xy)} vertices")
-                return scene
-
-            for class_a, class_b in edges:
-                xy_a = xy[class_a - 1]
-                xy_b = xy[class_b - 1]
-                missing_a = np.allclose(xy_a, 0)
-                missing_b = np.allclose(xy_b, 0)
-                if missing_a or missing_b:
-                    continue
-
-                cv2.line(
-                    img=scene,
-                    pt1=(int(xy_a[0]), int(xy_a[1])),
-                    pt2=(int(xy_b[0]), int(xy_b[1])),
-                    color=self.color.as_bgr(),
-                    thickness=self.thickness,
-                )
-
-        return scene
diff --git a/supervision/keypoint/annotators.py b/supervision/keypoint/annotators.py
new file mode 100644
index 000000000..5cadc3773
--- /dev/null
+++ b/supervision/keypoint/annotators.py
@@ -0,0 +1,170 @@
+from abc import ABC, abstractmethod
+from logging import warn
+from typing import List, Optional, Tuple
+
+import cv2
+import numpy as np
+
+from supervision.annotators.base import ImageType
+from supervision.draw.color import Color
+from supervision.keypoint.core import KeyPoints
+from supervision.keypoint.skeletons import SKELETONS_BY_VERTEX_COUNT
+from supervision.utils.conversion import convert_for_annotation_method
+
+
+class BaseKeyPointAnnotator(ABC):
+    @abstractmethod
+    def annotate(self, scene: ImageType, key_points: KeyPoints) -> ImageType:
+        pass
+
+
+class VertexAnnotator(BaseKeyPointAnnotator):
+    """
+    A class that specializes in drawing skeleton vertices on images. It uses
+    specified key points to determine the locations where the vertices should be
+    drawn.
+    """
+
+    def __init__(
+        self,
+        color: Color = Color.ROBOFLOW,
+        radius: int = 4,
+    ) -> None:
+        """
+        Args:
+            color (Color, optional): The color to use for annotating key points.
+            radius (int, optional): The radius of the circles used to represent the key
+                points.
+        """
+        self.color = color
+        self.radius = radius
+
+    @convert_for_annotation_method
+    def annotate(self, scene: ImageType, key_points: KeyPoints) -> ImageType:
+        """
+        Annotates the given scene with skeleton vertices based on the provided key
+        points. It draws circles at each key point location.
+
+        Args:
+            scene (ImageType): The image where bounding boxes will be drawn. `ImageType`
+                is a flexible type, accepting either `numpy.ndarray` or
+                `PIL.Image.Image`.
+            key_points (KeyPoints): A collection of key points where each key point
+                consists of x and y coordinates.
+
+        Returns:
+            The annotated image, matching the type of `scene` (`numpy.ndarray`
+                or `PIL.Image.Image`)
+
+        Example:
+            ```python
+            import supervision as sv
+
+            image = ...
+            key_points = sv.KeyPoints(...)
+
+            vertex_annotator = sv.VertexAnnotator()
+            annotated_frame = vertex_annotator.annotate(
+                scene=image.copy(),
+                key_points=key_points
+            )
+            ```
+        """
+        if len(key_points) == 0:
+            return scene
+
+        for xy in key_points.xy:
+            for x, y in xy:
+                cv2.circle(
+                    img=scene,
+                    center=(int(x), int(y)),
+                    radius=self.radius,
+                    color=self.color.as_bgr(),
+                    thickness=-1,
+                )
+
+        return scene
+
+
+class EdgeAnnotator(BaseKeyPointAnnotator):
+    """
+     A class that specializes in drawing skeleton edges on images using specified key
+     points. It connects key points with lines to form the skeleton structure.
+    """
+    def __init__(
+        self,
+        color: Color = Color.ROBOFLOW,
+        thickness: int = 2,
+        edges: Optional[List[Tuple[int, int]]] = None,
+    ) -> None:
+        """
+        Args:
+            color (Color, optional): The color to use for the edges.
+            thickness (int, optional): The thickness of the edges.
+            edges (Optional[List[Tuple[int, int]]]): The edges to draw.
+                If set to `None`, will attempt to select automatically.
+        """
+        self.color = color
+        self.thickness = thickness
+        self.edges = edges
+
+    @convert_for_annotation_method
+    def annotate(self, scene: ImageType, key_points: KeyPoints) -> ImageType:
+        """
+        Annotates the given scene by drawing lines between specified key points to form
+        edges.
+
+        Args:
+            scene (ImageType): The image where bounding boxes will be drawn. `ImageType`
+                is a flexible type, accepting either `numpy.ndarray` or
+                `PIL.Image.Image`.
+            key_points (KeyPoints): A collection of key points where each key point
+                consists of x and y coordinates.
+
+        Returns:
+            Returns:
+                The annotated image, matching the type of `scene` (`numpy.ndarray`
+                    or `PIL.Image.Image`)
+
+        Example:
+            ```python
+            import supervision as sv
+
+            image = ...
+            key_points = sv.KeyPoints(...)
+
+            edge_annotator = sv.EdgeAnnotator()
+            annotated_frame = edge_annotator.annotate(
+                scene=image.copy(),
+                key_points=key_points
+            )
+            ```
+        """
+        if len(key_points) == 0:
+            return scene
+
+        for xy in key_points.xy:
+            edges = self.edges
+            if not edges:
+                edges = SKELETONS_BY_VERTEX_COUNT.get(len(xy))
+            if not edges:
+                warn(f"No skeleton found with {len(xy)} vertices")
+                return scene
+
+            for class_a, class_b in edges:
+                xy_a = xy[class_a - 1]
+                xy_b = xy[class_b - 1]
+                missing_a = np.allclose(xy_a, 0)
+                missing_b = np.allclose(xy_b, 0)
+                if missing_a or missing_b:
+                    continue
+
+                cv2.line(
+                    img=scene,
+                    pt1=(int(xy_a[0]), int(xy_a[1])),
+                    pt2=(int(xy_b[0]), int(xy_b[1])),
+                    color=self.color.as_bgr(),
+                    thickness=self.thickness,
+                )
+
+        return scene
diff --git a/supervision/keypoint/core.py b/supervision/keypoint/core.py
index 6749f8452..b44d3b7c0 100644
--- a/supervision/keypoint/core.py
+++ b/supervision/keypoint/core.py
@@ -14,28 +14,25 @@
 @dataclass
 class KeyPoints:
     """
-    The `sv.KeyPoints` allows you to convert results from a variety of keypoint
-    keypoints models into a single, unified format.
+    The `sv.KeyPoints` class in the Supervision library standardizes results from
+    various keypoint detection and pose estimation models into a consistent format. This
+    class simplifies data manipulation and filtering, providing a uniform API for
+    integration with Supervision annotators.
 
-    ```python
-    import cv2
-    import supervision as sv
-    from ultralytics import YOLO
+    === "Ultralytics"
 
-    image = cv2.imread(<SOURCE_IMAGE_PATH>)
-    model = YOLO('yolov8s-pose.pt')
-    result = model(image)[0]
-    keypoints = sv.KeyPoints.from_ultralytics(result)
-    ```
+        Use [`sv.KeyPoints.from_ultralytics`](/keypoint/core/#supervision.keypoint.core.KeyPoints.from_ultralytics) method, which accepts model results.
 
-    !!! tip
+        ```python
+        import cv2
+        import supervision as sv
+        from ultralytics import YOLO
 
-        In `sv.KeyPoints`, detection data is categorized into two main field types:
-        fixed and custom. The fixed fields include `xy`, `confidence`,
-        `class_id`. For any additional data requirements, custom
-        fields come into play, stored in the data field. These custom fields are easily
-        accessible using the `keypoints[<FIELD_NAME>]` syntax, providing flexibility
-        for diverse data handling needs.
+        image = cv2.imread(<SOURCE_IMAGE_PATH>)
+        model = YOLO('yolov8s-pose.pt')
+        result = model(image)[0]
+        key_points = sv.KeyPoints.from_ultralytics(result)
+        ```
 
     Attributes:
         xy (np.ndarray): An array of shape `(n, 2)` containing
@@ -47,14 +44,6 @@ class KeyPoints:
         data (Dict[str, Union[np.ndarray, List]]): A dictionary containing additional
             data where each key is a string representing the data type, and the value
             is either a NumPy array or a list of corresponding data.
-
-    !!! warning
-
-        The `data` field in the `sv.KeyPoints` class is currently in an experimental
-        phase. Please be aware that its API and functionality are subject to change in
-        future updates as we continue to refine and improve its capabilities.
-        We encourage users to experiment with this feature and provide feedback, but
-        also to be prepared for potential modifications in upcoming releases.
     """
 
     xy: npt.NDArray[np.float32]
@@ -232,7 +221,7 @@ def empty(cls) -> KeyPoints:
         Create an empty Keypoints object with no keypoints.
 
         Returns:
-            (Keypoints): An empty Keypoints object.
+            (KeyPoints): An empty Keypoints object.
 
         Example:
             ```python

From 389453777ec94dab77e8d6e474907314ef5bbb55 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 16:18:21 +0200
Subject: [PATCH 178/188] vertex and edge annotators visualizations added

---
 docs/assets.md                     |  4 +--
 docs/detection/metrics.md          |  8 ++---
 docs/detection/utils.md            | 22 ++++++-------
 docs/keypoint/annotators.md        | 50 ++++++++++++++++++++++++++++++
 supervision/assets/list.py         |  1 +
 supervision/keypoint/annotators.py | 10 ++++--
 6 files changed, 74 insertions(+), 21 deletions(-)

diff --git a/docs/assets.md b/docs/assets.md
index 7e0d7dffc..3fd293eed 100644
--- a/docs/assets.md
+++ b/docs/assets.md
@@ -19,13 +19,13 @@ as an extra within the Supervision package.
     ```
 
 <div class="md-typeset">
-  <h2>download_assets</h2>
+    <h2><a href="#supervision.assets.downloader.download_assets.download_assets">download_assets</a></h2>
 </div>
 
 :::supervision.assets.downloader.download_assets
 
 <div class="md-typeset">
-  <h2>VideoAssets</h2>
+    <h2><a href="#supervision.assets.downloader.download_assets.VideoAssets">VideoAssets</a></h2>
 </div>
 
 :::supervision.assets.list.VideoAssets
diff --git a/docs/detection/metrics.md b/docs/detection/metrics.md
index 981f399cd..a68f0f968 100644
--- a/docs/detection/metrics.md
+++ b/docs/detection/metrics.md
@@ -4,18 +4,14 @@ comments: true
 
 # Metrics
 
-!!! warning
-
-    Evaluation API is still fluid and may change. If you use Evaluation API in your project until further notice, freeze the `supervision` version in your `requirements.txt` or `setup.py`.
-
 <div class="md-typeset">
-    <h2><a href="#supervision.detection.metrics.ConfusionMatrix">ConfusionMatrix</a></h2>
+    <h2><a href="#supervision.metrics.detection.ConfusionMatrix">ConfusionMatrix</a></h2>
 </div>
 
 :::supervision.metrics.detection.ConfusionMatrix
 
 <div class="md-typeset">
-    <h2><a href="#supervision.detection.metrics.MeanAveragePrecision">MeanAveragePrecision</a></h2>
+    <h2><a href="#supervision.metrics.detection.MeanAveragePrecision">MeanAveragePrecision</a></h2>
 </div>
 
 :::supervision.metrics.detection.MeanAveragePrecision
diff --git a/docs/detection/utils.md b/docs/detection/utils.md
index cc4eff5da..abacdc210 100644
--- a/docs/detection/utils.md
+++ b/docs/detection/utils.md
@@ -6,67 +6,67 @@ status: new
 # Detection Utils
 
 <div class="md-typeset">
-  <h2>box_iou_batch</h2>
+  <h2><a href="#supervision.detection.utils.box_iou_batch">box_iou_batch</a></h2>
 </div>
 
 :::supervision.detection.utils.box_iou_batch
 
 <div class="md-typeset">
-  <h2>mask_iou_batch</h2>
+  <h2><a href="#supervision.detection.utils.mask_iou_batch">mask_iou_batch</a></h2>
 </div>
 
 :::supervision.detection.utils.mask_iou_batch
 
 <div class="md-typeset">
-  <h2>box_non_max_suppression</h2>
+  <h2><a href="#supervision.detection.utils.box_non_max_suppression">box_non_max_suppression</a></h2>
 </div>
 
 :::supervision.detection.utils.box_non_max_suppression
 
 <div class="md-typeset">
-  <h2>mask_non_max_suppression</h2>
+  <h2><a href="#supervision.detection.utils.mask_non_max_suppression">mask_non_max_suppression</a></h2>
 </div>
 
 :::supervision.detection.utils.mask_non_max_suppression
 
 <div class="md-typeset">
-    <h2>polygon_to_mask</h2>
+  <h2><a href="#supervision.detection.utils.polygon_to_mask">polygon_to_mask</a></h2>
 </div>
 
 :::supervision.detection.utils.polygon_to_mask
 
 <div class="md-typeset">
-    <h2>mask_to_xyxy</h2>
+  <h2><a href="#supervision.detection.utils.mask_to_xyxy">mask_to_xyxy</a></h2>
 </div>
 
 :::supervision.detection.utils.mask_to_xyxy
 
 <div class="md-typeset">
-    <h2>mask_to_polygons</h2>
+  <h2><a href="#supervision.detection.utils.mask_to_polygons">mask_to_polygons</a></h2>
 </div>
 
 :::supervision.detection.utils.mask_to_polygons
 
 <div class="md-typeset">
-    <h2>polygon_to_xyxy</h2>
+  <h2><a href="#supervision.detection.utils.polygon_to_xyxy">polygon_to_xyxy</a></h2>
 </div>
 
 :::supervision.detection.utils.polygon_to_xyxy
 
 <div class="md-typeset">
-    <h2>filter_polygons_by_area</h2>
+  <h2><a href="#supervision.detection.utils.filter_polygons_by_area">filter_polygons_by_area</a></h2>
 </div>
 
 :::supervision.detection.utils.filter_polygons_by_area
 
 <div class="md-typeset">
-    <h2>move_boxes</h2>
+  <h2><a href="#supervision.detection.utils.move_boxes">move_boxes</a></h2>
 </div>
 
 :::supervision.detection.utils.move_boxes
 
 <div class="md-typeset">
-    <h2>scale_boxes</h2>
+  <h2><a href="#supervision.detection.utils.scale_boxes">scale_boxes</a></h2>
 </div>
 
 :::supervision.detection.utils.scale_boxes
diff --git a/docs/keypoint/annotators.md b/docs/keypoint/annotators.md
index 3efc5b032..b5f998bc0 100644
--- a/docs/keypoint/annotators.md
+++ b/docs/keypoint/annotators.md
@@ -5,6 +5,56 @@ status: new
 
 # Annotators
 
+=== "VertexAnnotator"
+
+    ```python
+    import supervision as sv
+
+    image = ...
+    key_points = sv.KeyPoints(...)
+
+    vertex_annotator = sv.VertexAnnotator(color=sv.Color.GREEN, radius=10)
+    annotated_frame = vertex_annotator.annotate(
+        scene=image.copy(),
+        key_points=key_points
+    )
+    ```
+
+    <div class="result" markdown>
+
+    ![vertex-annotator-example](https://media.roboflow.com/supervision-annotator-examples/vertex-annotator-example.png){ align=center width="800" }
+
+    </div>
+
+=== "EdgeAnnotator"
+
+    ```python
+    import supervision as sv
+
+    image = ...
+    key_points = sv.KeyPoints(...)
+
+    edge_annotator = sv.EdgeAnnotator(color=sv.Color.GREEN, thickness=5)
+    annotated_frame = edge_annotator.annotate(
+        scene=image.copy(),
+        key_points=key_points
+    )
+    ```
+
+    <div class="result" markdown>
+
+    ![edge-annotator-example](https://media.roboflow.com/supervision-annotator-examples/edge-annotator-example.png){ align=center width="800" }
+
+    </div>
+
+<div class="md-typeset">
+  <h2><a href="#supervision.keypoint.annotators.VertexAnnotator">VertexAnnotator</a></h2>
+</div>
+
 :::supervision.keypoint.annotators.VertexAnnotator
 
+<div class="md-typeset">
+  <h2><a href="#supervision.keypoint.annotators.EdgeAnnotator">EdgeAnnotator</a></h2>
+</div>
+
 :::supervision.keypoint.annotators.EdgeAnnotator
diff --git a/supervision/assets/list.py b/supervision/assets/list.py
index 0866431a8..8a01b7585 100644
--- a/supervision/assets/list.py
+++ b/supervision/assets/list.py
@@ -19,6 +19,7 @@ class VideoAssets(Enum):
     | `MARKET_SQUARE`        | `market-square.mp4`        | [Link](https://media.roboflow.com/supervision/video-examples/market-square.mp4)       |
     | `PEOPLE_WALKING`       | `people-walking.mp4`       | [Link](https://media.roboflow.com/supervision/video-examples/people-walking.mp4)      |
     | `BEACH`                | `beach-1.mp4`              | [Link](https://media.roboflow.com/supervision/video-examples/beach-1.mp4)             |
+    | `BASKETBALL`           | `basketball-1.mp4`         | [Link](https://media.roboflow.com/supervision/video-examples/basketball-1.mp4)        |
     """  # noqa: E501 // docs
 
     VEHICLES = "vehicles.mp4"
diff --git a/supervision/keypoint/annotators.py b/supervision/keypoint/annotators.py
index 5cadc3773..4d6df72ca 100644
--- a/supervision/keypoint/annotators.py
+++ b/supervision/keypoint/annotators.py
@@ -63,12 +63,15 @@ def annotate(self, scene: ImageType, key_points: KeyPoints) -> ImageType:
             image = ...
             key_points = sv.KeyPoints(...)
 
-            vertex_annotator = sv.VertexAnnotator()
+            vertex_annotator = sv.VertexAnnotator(color=sv.Color.GREEN, radius=10)
             annotated_frame = vertex_annotator.annotate(
                 scene=image.copy(),
                 key_points=key_points
             )
             ```
+
+        ![vertex-annotator-example](https://media.roboflow.com/
+        supervision-annotator-examples/vertex-annotator-example.png)
         """
         if len(key_points) == 0:
             return scene
@@ -133,12 +136,15 @@ def annotate(self, scene: ImageType, key_points: KeyPoints) -> ImageType:
             image = ...
             key_points = sv.KeyPoints(...)
 
-            edge_annotator = sv.EdgeAnnotator()
+            edge_annotator = sv.EdgeAnnotator(color=sv.Color.GREEN, thickness=5)
             annotated_frame = edge_annotator.annotate(
                 scene=image.copy(),
                 key_points=key_points
             )
             ```
+
+        ![edge-annotator-example](https://media.roboflow.com/
+        supervision-annotator-examples/edge-annotator-example.png)
         """
         if len(key_points) == 0:
             return scene

From 908f3d14c6d0dd622211434c23bfd63a3e2fa720 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 16:28:48 +0200
Subject: [PATCH 179/188] improved docs linking

---
 docs/utils/image.md     | 12 ++++++------
 docs/utils/iterables.md |  4 ++--
 docs/utils/notebook.md  |  5 ++---
 docs/utils/video.md     | 10 +++++-----
 4 files changed, 15 insertions(+), 16 deletions(-)

diff --git a/docs/utils/image.md b/docs/utils/image.md
index 87fd1943e..8f170d353 100644
--- a/docs/utils/image.md
+++ b/docs/utils/image.md
@@ -6,37 +6,37 @@ status: new
 # Image Utils
 
 <div class="md-typeset">
-  <h2>crop_image</h2>
+    <h2><a href="#supervision.utils.image.crop_image">crop_image</a></h2>
 </div>
 
 :::supervision.utils.image.crop_image
 
 <div class="md-typeset">
-  <h2>scale_image</h2>
+    <h2><a href="#supervision.utils.image.scale_image">crop_image</a></h2>
 </div>
 
 :::supervision.utils.image.scale_image
 
 <div class="md-typeset">
-  <h2>resize_image</h2>
+    <h2><a href="#supervision.utils.image.resize_image">resize_image</a></h2>
 </div>
 
 :::supervision.utils.image.resize_image
 
 <div class="md-typeset">
-  <h2>letterbox_image</h2>
+    <h2><a href="#supervision.utils.image.letterbox_image">letterbox_image</a></h2>
 </div>
 
 :::supervision.utils.image.letterbox_image
 
 <div class="md-typeset">
-  <h2>overlay_image</h2>
+    <h2><a href="#supervision.utils.image.overlay_image">overlay_image</a></h2>
 </div>
 
 :::supervision.utils.image.overlay_image
 
 <div class="md-typeset">
-  <h2>ImageSink</h2>
+    <h2><a href="#supervision.utils.image.ImageSink">ImageSink</a></h2>
 </div>
 
 :::supervision.utils.image.ImageSink
diff --git a/docs/utils/iterables.md b/docs/utils/iterables.md
index 3ccf98e59..b65cd954b 100644
--- a/docs/utils/iterables.md
+++ b/docs/utils/iterables.md
@@ -6,13 +6,13 @@ status: new
 # Iterables Utils
 
 <div class="md-typeset">
-  <h2>create_batches</h2>
+    <h2><a href="#supervision.utils.iterables.create_batches">create_batches</a></h2>
 </div>
 
 :::supervision.utils.iterables.create_batches
 
 <div class="md-typeset">
-  <h2>fill</h2>
+    <h2><a href="#supervision.utils.iterables.fill">fill</a></h2>
 </div>
 
 :::supervision.utils.iterables.fill
diff --git a/docs/utils/notebook.md b/docs/utils/notebook.md
index d09b9bbd8..3eab046ab 100644
--- a/docs/utils/notebook.md
+++ b/docs/utils/notebook.md
@@ -5,14 +5,13 @@ comments: true
 # Notebooks Utils
 
 <div class="md-typeset">
-  <h2>plot_image</h2>
+    <h2><a href="#supervision.utils.notebook.plot_image">plot_image</a></h2>
 </div>
 
 :::supervision.utils.notebook.plot_image
 
 <div class="md-typeset">
-  <h2>plot_images_grid
-</h2>
+    <h2><a href="#supervision.utils.notebook.plot_images_grid">plot_images_grid</a></h2>
 </div>
 
 :::supervision.utils.notebook.plot_images_grid
diff --git a/docs/utils/video.md b/docs/utils/video.md
index 1f58450f5..f9a5821d6 100644
--- a/docs/utils/video.md
+++ b/docs/utils/video.md
@@ -5,31 +5,31 @@ comments: true
 # Video Utils
 
 <div class="md-typeset">
-  <h2>VideoInfo</h2>
+    <h2><a href="#supervision.utils.video.VideoInfo">VideoInfo</a></h2>
 </div>
 
 :::supervision.utils.video.VideoInfo
 
 <div class="md-typeset">
-  <h2>VideoSink</h2>
+    <h2><a href="#supervision.utils.video.VideoSink">VideoSink</a></h2>
 </div>
 
 :::supervision.utils.video.VideoSink
 
 <div class="md-typeset">
-  <h2>FPSMonitor</h2>
+    <h2><a href="#supervision.utils.video.FPSMonitor">FPSMonitor</a></h2>
 </div>
 
 :::supervision.utils.video.FPSMonitor
 
 <div class="md-typeset">
-  <h2>get_video_frames_generator</h2>
+    <h2><a href="#supervision.utils.video.get_video_frames_generator">get_video_frames_generator</a></h2>
 </div>
 
 :::supervision.utils.video.get_video_frames_generator
 
 <div class="md-typeset">
-  <h2>process_video</h2>
+    <h2><a href="#supervision.utils.video.process_video">process_video</a></h2>
 </div>
 
 :::supervision.utils.video.process_video

From 1c42838ca1c529532af7583d7979d647e04a1045 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 16:35:34 +0200
Subject: [PATCH 180/188] improved docs linking

---
 docs/utils/draw.md     | 21 ++++++++++-----------
 docs/utils/file.md     |  2 +-
 docs/utils/geometry.md |  4 +++-
 3 files changed, 14 insertions(+), 13 deletions(-)

diff --git a/docs/utils/draw.md b/docs/utils/draw.md
index 7b47a6a76..84758e06f 100644
--- a/docs/utils/draw.md
+++ b/docs/utils/draw.md
@@ -5,62 +5,61 @@ comments: true
 # Draw Utils
 
 <div class="md-typeset">
-  <h2>draw_line</h2>
+    <h2><a href="#supervision.draw.utils.draw_line">draw_line</a></h2>
 </div>
 
 :::supervision.draw.utils.draw_line
 
 <div class="md-typeset">
-  <h2>draw_rectangle</h2>
+    <h2><a href="#supervision.draw.utils.draw_rectangle">draw_rectangle</a></h2>
 </div>
 
 :::supervision.draw.utils.draw_rectangle
 
 <div class="md-typeset">
-  <h2>draw_filled_rectangle</h2>
+    <h2><a href="#supervision.draw.utils.draw_filled_rectangle">draw_filled_rectangle</a></h2>
 </div>
 
 :::supervision.draw.utils.draw_filled_rectangle
 
 <div class="md-typeset">
-  <h2>draw_polygon</h2>
+    <h2><a href="#supervision.draw.utils.draw_polygon">draw_polygon</a></h2>
 </div>
 
 :::supervision.draw.utils.draw_polygon
 
 <div class="md-typeset">
-  <h2>draw_text</h2>
+    <h2><a href="#supervision.draw.utils.draw_text">draw_text</a></h2>
 </div>
 
 :::supervision.draw.utils.draw_text
 
 <div class="md-typeset">
-  <h2>draw_image</h2>
+    <h2><a href="#supervision.draw.utils.draw_image">draw_image</a></h2>
 </div>
 
 :::supervision.draw.utils.draw_image
 
 <div class="md-typeset">
-  <h2>calculate_optimal_font_scale</h2>
+    <h2><a href="#supervision.draw.utils.calculate_optimal_font_scale">calculate_optimal_font_scale</a></h2>
 </div>
 
 :::supervision.draw.utils.calculate_optimal_text_scale
 
 <div class="md-typeset">
-  <h2>calculate_optimal_line_thickness</h2>
+    <h2><a href="#supervision.draw.utils.calculate_optimal_line_thickness">calculate_optimal_line_thickness</a></h2>
 </div>
 
 :::supervision.draw.utils.calculate_optimal_line_thickness
 
 <div class="md-typeset">
-  <h2>Color</h2>
+    <h2><a href="#supervision.draw.color.Color">Color</a></h2>
 </div>
 
 :::supervision.draw.color.Color
 
 <div class="md-typeset">
-  <h2>ColorPalette</h2>
+    <h2><a href="#supervision.draw.color.ColorPalette">ColorPalette</a></h2>
 </div>
 
 :::supervision.draw.color.ColorPalette
-
diff --git a/docs/utils/file.md b/docs/utils/file.md
index 2ba5a0154..a2a08185f 100644
--- a/docs/utils/file.md
+++ b/docs/utils/file.md
@@ -5,7 +5,7 @@ comments: true
 # File Utils
 
 <div class="md-typeset">
-  <h2>list_files_with_extensions</h2>
+    <h2><a href="#supervision.utils.file.list_files_with_extensions">list_files_with_extensions</a></h2>
 </div>
 
 :::supervision.utils.file.list_files_with_extensions
diff --git a/docs/utils/geometry.md b/docs/utils/geometry.md
index ca99b6260..8c92f5627 100644
--- a/docs/utils/geometry.md
+++ b/docs/utils/geometry.md
@@ -2,6 +2,8 @@
 comments: true
 ---
 
-# Position
+<div class="md-typeset">
+    <h2><a href="#supervision.geometry.core.Position">Position</a></h2>
+</div>
 
 :::supervision.geometry.core.Position

From 263420758e6b509c069f29005fd7d1b75e2d8817 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 14:36:15 +0000
Subject: [PATCH 181/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/core.py      | 4 ++--
 supervision/keypoint/annotators.py | 5 +++--
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 3e3d01140..8df11eca1 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -231,7 +231,7 @@ def from_ultralytics(cls, ultralytics_results) -> Detections:
             results = model(image)[0]
             detections = sv.Detections.from_ultralytics(results)
             ```
-            
+
         !!! tip
 
             Class names values can be accessed using `detections["class_name"]`.
@@ -461,7 +461,7 @@ class names. If provided, the resulting Detections object will contain
                 id2label=model.config.id2label
             )
             ```
-        
+
         !!! tip
 
             Class names values can be accessed using `detections["class_name"]`.
diff --git a/supervision/keypoint/annotators.py b/supervision/keypoint/annotators.py
index 4d6df72ca..4b43765c2 100644
--- a/supervision/keypoint/annotators.py
+++ b/supervision/keypoint/annotators.py
@@ -91,9 +91,10 @@ def annotate(self, scene: ImageType, key_points: KeyPoints) -> ImageType:
 
 class EdgeAnnotator(BaseKeyPointAnnotator):
     """
-     A class that specializes in drawing skeleton edges on images using specified key
-     points. It connects key points with lines to form the skeleton structure.
+    A class that specializes in drawing skeleton edges on images using specified key
+    points. It connects key points with lines to form the skeleton structure.
     """
+
     def __init__(
         self,
         color: Color = Color.ROBOFLOW,

From 895562d444959e140bf8f82a3e8dd4b2a40c4d5e Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 16:37:41 +0200
Subject: [PATCH 182/188] make pre-commit happy

---
 supervision/detection/core.py | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 3e3d01140..b1ded4d61 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -34,7 +34,8 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Inference"
 
-        Use [`sv.Detections.from_inference`](/detection/core/#supervision.detection.core.Detections.from_inference) method, which accepts model results from both detection and segmentation models.
+        Use [`sv.Detections.from_inference`](/detection/core/#supervision.detection.core.Detections.from_inference) 
+        method, which accepts model results from both detection and segmentation models.
 
         ```python
         import cv2
@@ -49,7 +50,8 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Ultralytics"
 
-        Use [`sv.Detections.from_ultralytics`](/detection/core/#supervision.detection.core.Detections.from_ultralytics) method, which accepts model results from both detection and segmentation models.
+        Use [`sv.Detections.from_ultralytics`](/detection/core/#supervision.detection.core.Detections.from_ultralytics) 
+        method, which accepts model results from both detection and segmentation models.
 
         ```python
         import cv2
@@ -64,7 +66,8 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Transformers"
 
-        Use [`sv.Detections.from_transformers`](/detection/core/#supervision.detection.core.Detections.from_transformers) method, which accepts model results from both detection and segmentation models.
+        Use [`sv.Detections.from_transformers`](/detection/core/#supervision.detection.core.Detections.from_transformers) 
+        method, which accepts model results from both detection and segmentation models.
 
         ```python
         import torch
@@ -104,7 +107,7 @@ class simplifies data manipulation and filtering, providing a uniform API for
         data (Dict[str, Union[np.ndarray, List]]): A dictionary containing additional
             data where each key is a string representing the data type, and the value
             is either a NumPy array or a list of corresponding data.
-    """
+    """  # noqa: E501 // docs
 
     xyxy: np.ndarray
     mask: Optional[np.ndarray] = None

From 383c1a1d8d0fae16fac712667551b01ed4695d5f Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 14:39:01 +0000
Subject: [PATCH 183/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/detection/core.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index f305385d2..1900954de 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -34,7 +34,7 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Inference"
 
-        Use [`sv.Detections.from_inference`](/detection/core/#supervision.detection.core.Detections.from_inference) 
+        Use [`sv.Detections.from_inference`](/detection/core/#supervision.detection.core.Detections.from_inference)
         method, which accepts model results from both detection and segmentation models.
 
         ```python
@@ -50,7 +50,7 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Ultralytics"
 
-        Use [`sv.Detections.from_ultralytics`](/detection/core/#supervision.detection.core.Detections.from_ultralytics) 
+        Use [`sv.Detections.from_ultralytics`](/detection/core/#supervision.detection.core.Detections.from_ultralytics)
         method, which accepts model results from both detection and segmentation models.
 
         ```python
@@ -66,7 +66,7 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Transformers"
 
-        Use [`sv.Detections.from_transformers`](/detection/core/#supervision.detection.core.Detections.from_transformers) 
+        Use [`sv.Detections.from_transformers`](/detection/core/#supervision.detection.core.Detections.from_transformers)
         method, which accepts model results from both detection and segmentation models.
 
         ```python

From d7da00c55b8dc47034f5f4e49d0493fa1a98c1b9 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 16:43:40 +0200
Subject: [PATCH 184/188] make pre-commit happy

---
 supervision/keypoint/core.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/supervision/keypoint/core.py b/supervision/keypoint/core.py
index b44d3b7c0..ed5d698ea 100644
--- a/supervision/keypoint/core.py
+++ b/supervision/keypoint/core.py
@@ -21,7 +21,8 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Ultralytics"
 
-        Use [`sv.KeyPoints.from_ultralytics`](/keypoint/core/#supervision.keypoint.core.KeyPoints.from_ultralytics) method, which accepts model results.
+        Use [`sv.KeyPoints.from_ultralytics`](/keypoint/core/#supervision.keypoint.core.KeyPoints.from_ultralytics) 
+        method, which accepts model results.
 
         ```python
         import cv2
@@ -44,7 +45,7 @@ class simplifies data manipulation and filtering, providing a uniform API for
         data (Dict[str, Union[np.ndarray, List]]): A dictionary containing additional
             data where each key is a string representing the data type, and the value
             is either a NumPy array or a list of corresponding data.
-    """
+    """  # noqa: E501 // docs
 
     xy: npt.NDArray[np.float32]
     class_id: Optional[npt.NDArray[np.int_]] = None

From f4fca3339ded4c33379a6609b0f8c441ac4e6808 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 14:45:18 +0000
Subject: [PATCH 185/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/keypoint/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/supervision/keypoint/core.py b/supervision/keypoint/core.py
index ed5d698ea..8a97b51c3 100644
--- a/supervision/keypoint/core.py
+++ b/supervision/keypoint/core.py
@@ -21,7 +21,7 @@ class simplifies data manipulation and filtering, providing a uniform API for
 
     === "Ultralytics"
 
-        Use [`sv.KeyPoints.from_ultralytics`](/keypoint/core/#supervision.keypoint.core.KeyPoints.from_ultralytics) 
+        Use [`sv.KeyPoints.from_ultralytics`](/keypoint/core/#supervision.keypoint.core.KeyPoints.from_ultralytics)
         method, which accepts model results.
 
         ```python

From 7a90eefd5b63f7aafba3adf90a839178e3a8684b Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 19:22:59 +0200
Subject: [PATCH 186/188] changelog updated version bump from `0.20.0rc2` to
 `0.20.0`

---
 docs/changelog.md                 | 65 +++++++++++++++++++++++++++++++
 docs/deprecated.md                |  1 +
 docs/utils/geometry.md            |  6 +++
 pyproject.toml                    |  2 +-
 supervision/detection/annotate.py |  8 ++--
 supervision/geometry/utils.py     | 15 +++----
 6 files changed, 82 insertions(+), 15 deletions(-)

diff --git a/docs/changelog.md b/docs/changelog.md
index 2c5d7ae19..f8d301cd1 100644
--- a/docs/changelog.md
+++ b/docs/changelog.md
@@ -1,3 +1,68 @@
+### 0.20.0 <small>April 24, 2024</small>
+
+- Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.KeyPoints`](/0.20.0/keypoint/core/#supervision.keypoint.core.KeyPoints) to provide initial support for pose estimation and broader keypoint detection models. 
+
+- Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.EdgeAnnotator`](/0.20.0/keypoint/annotators/#supervision.keypoint.annotators.EdgeAnnotator) and [`sv.VertexAnnotator`](/0.20.0/keypoint/annotators/#supervision.keypoint.annotators.VertexAnnotator) to enable rendering of results from keypoint detection models.
+
+```python
+import cv2
+import supervision as sv
+from ultralytics import YOLO
+
+image = cv2.imread(<SOURCE_IMAGE_PATH>)
+model = YOLO('yolov8l-pose')
+
+result = model(image, verbose=False)[0]
+keypoints = sv.KeyPoints.from_ultralytics(result)
+
+edge_annotators = sv.EdgeAnnotator(color=sv.Color.GREEN, thickness=5)
+annotated_image = edge_annotators.annotate(image.copy(), keypoints)
+```
+
+- Changed [#1037](https://github.com/roboflow/supervision/pull/1037): [`sv.LabelAnnotator`](/0.20.0/annotators/#supervision.annotators.core.LabelAnnotator) by adding an additional `corner_radius` argument that allows for rounding the corners of the bounding box.
+
+- Changed [#1109](https://github.com/roboflow/supervision/pull/1109): [`sv.PolygonZone`](/0.20.0/detection/tools/polygon_zone/#supervision.detection.tools.polygon_zone.PolygonZone) such that the `frame_resolution_wh` argument is no longer required to initialize `sv.PolygonZone`.
+
+!!! failure "Deprecated"
+
+    The `frame_resolution_wh` parameter in `sv.PolygonZone` is deprecated and will be removed in `supervision-0.24.0`.
+
+- Changed [#1084](https://github.com/roboflow/supervision/pull/1084): [`sv.get_polygon_center`](/0.20.0/utils/geometry/#supervision.geometry.core.utils.get_polygon_center) to calculate a more accurate polygon centroid.
+
+- Changed [#1069](https://github.com/roboflow/supervision/pull/1069): [`sv.Detections.from_transformers`](/0.20.0/detection/core/#supervision.detection.core.Detections.from_transformers) by adding support for Transformers segmentation models and extract class names values.
+
+```python
+import torch
+import supervision as sv
+from PIL import Image
+from transformers import DetrImageProcessor, DetrForSegmentation
+
+processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50-panoptic")
+model = DetrForSegmentation.from_pretrained("facebook/detr-resnet-50-panoptic")
+
+image = Image.open(<SOURCE_IMAGE_PATH>)
+inputs = processor(images=image, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model(**inputs)
+
+width, height = image.size
+target_size = torch.tensor([[height, width]])
+results = processor.post_process_segmentation(
+    outputs=outputs, target_sizes=target_size)[0]
+detections = sv.Detections.from_transformers(results, id2label=model.config.id2label)
+
+mask_annotator = sv.MaskAnnotator()
+label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+
+annotated_image = mask_annotator.annotate(
+    scene=image, detections=detections)
+annotated_image = label_annotator.annotate(
+    scene=annotated_image, detections=detections)
+```
+
+- Fixed [#787](https://github.com/roboflow/supervision/pull/787): [`sv.ByteTrack.update_with_detections`](/0.20.0/trackers/#supervision.tracker.byte_tracker.core.ByteTrack.update_with_detections) which was removing segmentation masks while tracking. Now, `ByteTrack` can be used alongside segmentation models.
+
 ### 0.19.0 <small>March 15, 2024</small>
 
 - Added [#818](https://github.com/roboflow/supervision/pull/818): [`sv.CSVSink`](/0.19.0/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) allowing for the straightforward saving of image, video, or stream inference results in a `.csv` file.
diff --git a/docs/deprecated.md b/docs/deprecated.md
index cc1e96498..5834b05fd 100644
--- a/docs/deprecated.md
+++ b/docs/deprecated.md
@@ -16,3 +16,4 @@ These features are phased out due to better alternatives or potential issues in
 - The method [`FPSMonitor.__call__`](utils/video.md/#supervision.utils.video.FPSMonitor.__call__) is deprecated and will be removed in `supervision-0.22.0`. Use the attribute [`FPSMonitor.fps`](utils/video.md/#supervision.utils.video.FPSMonitor.fps) instead.
 - The `track_buffer`, `track_thresh`, and `match_thresh` parameters in [`ByterTrack`](trackers.md/#supervision.tracker.byte_tracker.core.ByteTrack) are deprecated and will be removed in `supervision-0.23.0`. Use `lost_track_buffer,` `track_activation_threshold`, and `minimum_matching_threshold` instead.
 - The `triggering_position ` parameter in [`sv.PolygonZone`](detection/tools/polygon_zone.md/#supervision.detection.tools.polygon_zone.PolygonZone) is deprecated and will be removed in `supervision-0.23.0`. Use `triggering_anchors ` instead.
+- The `frame_resolution_wh ` parameter in [`sv.PolygonZone`](detection/tools/polygon_zone.md/#supervision.detection.tools.polygon_zone.PolygonZone) is deprecated and will be removed in `supervision-0.24.0`.
diff --git a/docs/utils/geometry.md b/docs/utils/geometry.md
index 8c92f5627..d79bcfeb5 100644
--- a/docs/utils/geometry.md
+++ b/docs/utils/geometry.md
@@ -2,6 +2,12 @@
 comments: true
 ---
 
+<div class="md-typeset">
+    <h2><a href="#supervision.geometry.core.utils.get_polygon_center">get_polygon_center</a></h2>
+</div>
+
+:::supervision.geometry.utils.get_polygon_center
+
 <div class="md-typeset">
     <h2><a href="#supervision.geometry.core.Position">Position</a></h2>
 </div>
diff --git a/pyproject.toml b/pyproject.toml
index 7be53b6c2..de0df7485 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "supervision"
-version = "0.20.0rc2"
+version = "0.20.0"
 description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
 authors = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
 maintainers = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
diff --git a/supervision/detection/annotate.py b/supervision/detection/annotate.py
index f32c73440..f496b2487 100644
--- a/supervision/detection/annotate.py
+++ b/supervision/detection/annotate.py
@@ -9,10 +9,6 @@
 from supervision.utils.internal import deprecated
 
 
-@deprecated(
-    "`BoxAnnotator` is deprecated and will be removed in "
-    "`supervision-0.22.0`. Use `BoundingBoxAnnotator` and `LabelAnnotator` instead"
-)
 class BoxAnnotator:
     """
     A class for drawing bounding boxes on an image using detections provided.
@@ -46,6 +42,10 @@ def __init__(
         self.text_thickness: int = text_thickness
         self.text_padding: int = text_padding
 
+    @deprecated(
+        "`BoxAnnotator` is deprecated and will be removed in "
+        "`supervision-0.22.0`. Use `BoundingBoxAnnotator` and `LabelAnnotator` instead"
+    )
     @convert_for_annotation_method
     def annotate(
         self,
diff --git a/supervision/geometry/utils.py b/supervision/geometry/utils.py
index 9cf717e49..8a0ca35c5 100644
--- a/supervision/geometry/utils.py
+++ b/supervision/geometry/utils.py
@@ -5,12 +5,7 @@
 
 def get_polygon_center(polygon: np.ndarray) -> Point:
     """
-    Calculate the center of a polygon.
-
-    This function takes in a polygon as a 2-dimensional numpy ndarray and
-    returns the center of the polygon as a Point object.
-
-    The center is calculated as the center
+    Calculate the center of a polygon. The center is calculated as the center
     of the solid figure formed by the points of the polygon
 
     Parameters:
@@ -23,12 +18,12 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
 
     Examples:
         ```python
-        from supervision.geometry.utils import get_polygon_center
         import numpy as np
+        import supervision as sv
 
-        vertices = np.array([[0, 0], [0, 2], [2, 2], [2, 0]])
-        get_polygon_center(vertices)
-        Point(x=1, y=1)
+        polygon = np.array([[0, 0], [0, 2], [2, 2], [2, 0]])
+        sv.get_polygon_center(polygon=polygon)
+        # Point(x=1, y=1)
         ```
     """
 

From 6ae99444b543d005c2b48104b90f826c37cfa02d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 24 Apr 2024 17:24:16 +0000
Subject: [PATCH 187/188] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20aut?=
 =?UTF-8?q?o=20format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/changelog.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/changelog.md b/docs/changelog.md
index f8d301cd1..47d160aa6 100644
--- a/docs/changelog.md
+++ b/docs/changelog.md
@@ -1,6 +1,6 @@
 ### 0.20.0 <small>April 24, 2024</small>
 
-- Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.KeyPoints`](/0.20.0/keypoint/core/#supervision.keypoint.core.KeyPoints) to provide initial support for pose estimation and broader keypoint detection models. 
+- Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.KeyPoints`](/0.20.0/keypoint/core/#supervision.keypoint.core.KeyPoints) to provide initial support for pose estimation and broader keypoint detection models.
 
 - Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.EdgeAnnotator`](/0.20.0/keypoint/annotators/#supervision.keypoint.annotators.EdgeAnnotator) and [`sv.VertexAnnotator`](/0.20.0/keypoint/annotators/#supervision.keypoint.annotators.VertexAnnotator) to enable rendering of results from keypoint detection models.
 

From 5c4ed2650e0a6b1e2ef3d3de36b3c9ae0fafb5f6 Mon Sep 17 00:00:00 2001
From: SkalskiP <piotr.skalski92@gmail.com>
Date: Wed, 24 Apr 2024 19:25:45 +0200
Subject: [PATCH 188/188] drop accidentally committed `from_inference`

---
 supervision/keypoint/core.py | 31 -------------------------------
 1 file changed, 31 deletions(-)

diff --git a/supervision/keypoint/core.py b/supervision/keypoint/core.py
index 7019aa958..8a97b51c3 100644
--- a/supervision/keypoint/core.py
+++ b/supervision/keypoint/core.py
@@ -100,37 +100,6 @@ def __eq__(self, other: KeyPoints) -> bool:
             ]
         )
 
-    @classmethod
-    def from_inference(cls, inference_result: dict) -> KeyPoints:
-        if not inference_result.get("predictions"):
-            return cls.empty()
-
-        xy = []
-        confidence = []
-        class_id = []
-        class_names = []
-
-        for prediction in inference_result["predictions"]:
-            prediction_xy = []
-            prediction_confidence = []
-            for keypoint in prediction["keypoints"]:
-                prediction_xy.append([keypoint["x"], keypoint["y"]])
-                prediction_confidence.append(keypoint["confidence"])
-            xy.append(prediction_xy)
-            confidence.append(prediction_confidence)
-
-            class_id.append(prediction["class_id"])
-            class_names.append(prediction["class"])
-
-        data = {CLASS_NAME_DATA_FIELD: np.array(class_names)}
-
-        return cls(
-            xy=np.array(xy, dtype=np.float32),
-            confidence=np.array(confidence, dtype=np.float32),
-            class_id=np.array(class_id, dtype=int),
-            data=data,
-        )
-
     @classmethod
     def from_ultralytics(cls, ultralytics_results) -> KeyPoints:
         """