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INSTALL.md

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Installation

Requirements

  • Linux
  • Python 3.5+ (Say goodbye to Python2)
  • PyTorch 1.0+ or PyTorch-nightly (We have tested Pedestron using PyTorch==1.4.0)
  • CUDA 9.0+
  • NCCL 2+
  • GCC 4.9+
  • mmcv (We have tested Pedestron using mmcv==0.2.10 and 0.2.14)

We have tested the following versions of OS and softwares:

  • OS: Ubuntu 16.04/18.04 and CentOS 7.2
  • CUDA: 9.0/9.2/10.0
  • NCCL: 2.1.15/2.2.13/2.3.7/2.4.2
  • GCC: 4.9/5.3/5.4/7.3

Install mmdetection

a. Create a conda virtual environment and activate it. Then install Cython.

conda create -n open-mmlab python=3.7 -y
conda activate open-mmlab

conda install cython

b. Install PyTorch stable or nightly and torchvision following the official instructions.

c. Clone the Pedestron repository.

git clone https://github.com/hasanirtiza/Pedestron.git
cd Pedestron

d. Install Pedestron (other dependencies will be installed automatically).

  1. If your environment is cuda 10.2+/11, you need modify Pedestron code to change all AT_CHECK to TORCH_CHECK, then the following command can compile successfully.

  2. If your environment is cuda 9.0/9.2/10.0, just run the following command.

python setup.py develop
# or "pip install -v -e ."

Note:

  1. It is recommended that you run the step e each time you pull some updates from github. If there are some updates of the C/CUDA codes, you also need to run step d. The git commit id will be written to the version number with step e, e.g. 0.6.0+2e7045c. The version will also be saved in trained models.

  2. Following the above instructions, mmdetection is installed on dev mode, any modifications to the code will take effect without installing it again.

Docker Installation

  1. Setup environment by docker
sudo docker build . -t pedestron
  • Run docker image:
sudo docker run --gpus all --shm-size=8g -it --rm pedestron

CUDA 11+ instllation

  1. Please follow the tips and instructions given at this PR request.

Prepare COCO dataset.

It is recommended to symlink the dataset root to $MMDETECTION/data.

mmdetection
├── mmdet
├── tools
├── configs
├── data
│   ├── coco
│   │   ├── annotations
│   │   ├── train2017
│   │   ├── val2017
│   │   ├── test2017
│   ├── VOCdevkit
│   │   ├── VOC2007
│   │   ├── VOC2012

Scripts

Here is a script for setting up mmdetection with conda.

Notice

You can run python(3) setup.py develop or pip install -v -e . to install mmdetection if you want to make modifications to it frequently.

If there are more than one mmdetection on your machine, and you want to use them alternatively. Please insert the following code to the main file

import os.path as osp
import sys
sys.path.insert(0, osp.join(osp.dirname(osp.abspath(__file__)), '../'))

or run the following command in the terminal of corresponding folder.

export PYTHONPATH=`pwd`:$PYTHONPATH