v0.9.8
What's Changed
- Add changes that eliminate mistakes spotted while initial e2e tests by @PawelPeczek-Roboflow in #204
- Add ZoomInfo integration by @capjamesg in #205
- Added Kubernetes helm chart by @bigbitbus in #206
- Wrap lambda deployment with AL model manager by @PawelPeczek-Roboflow in #207
- Emable SSL on Redis connection based on env config (to enable AWS lambda connectivity) by @PawelPeczek-Roboflow in #209
- Add Grounding DINO to Inference by @capjamesg in #107
- Extend inference SDK with client for (almost all) core models by @PawelPeczek-Roboflow in #212
- API Key Not Required by Methods by @paulguerrie in #211
- Expose InferencePipeline at the top level by @yeldarby in #210
- Built In Jupyter Notebook by @paulguerrie in #213
- Fix problem with keyless access and Active Learning by @PawelPeczek-Roboflow in #214
Highlights
Grounding DINO
Support for a new core model, Grounding DINO has been added. Grounding DINO is a zero-shot object detection model that you can use to identify objects in images and videos using arbitrary text prompts.
Inference SDK For Core Models
You can now use the Inference SDK with core models (like CLIP). No more complicated request and payload formatting. See the docs here.
Built In Jupyter Notebook
Roboflow Inference Server containers now include a built in Jupyter notebook for development and testing. This notebook can be accessed via the inference server landing page. To use it, go to localhost:9001 in your browser after starting an inference server. Then select "Jump Into An Inference Enabled Notebook". This will open a new tab with a Jupyterlab session, preloaded with example notebooks and all of the inference dependancies.
New Contributors
- @bigbitbus made their first contribution in #206
Full Changelog: v0.9.7...v0.9.8
