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Code style: black PyPI Version

deepstack-python

Unofficial python API for DeepStack. Provides classes for making requests to the object detection & face detection/recognition endpoints. Also includes some helper functions for processing the results. See the Jupyter notebooks for usage.

Run Deepstack with all three endpoints active (CPU mode):

docker run \
      -e VISION-SCENE=True \
      -e VISION-DETECTION=True \
      -e VISION-FACE=True \
      -v localstorage:/datastore \
      -p 80:5000 \
      -e API-KEY="" \
      --name deepstack deepquestai/deepstack

Check deepstack is running using curl (from root of this repo):

curl -X POST -F image=@tests/images/test-image3.jpg 'http://localhost:5000/v1/vision/detection'

If all goes well you should see the following returned:

{"success":true,"predictions":[{"confidence":0.9998661,"label":"person","y_min":0,"x_min":258,"y_max":676,"x_max":485},{"confidence":0.9996547,"label":"person","y_min":0,"x_min":405,"y_max":652,"x_max":639},{"confidence":0.99745613,"label":"dog","y_min":311,"x_min":624,"y_max":591,"x_max":825}]}

Development

  • Create venv -> python3.7 -m venv venv
  • Use venv -> source venv/bin/activate
  • pip3 install -r requirements.txt and pip3 install -r requirements-dev.txt
  • Run tests with venv/bin/pytest tests/*
  • Black format with venv/bin/black .

Jupyter

  • Docs are created using Jupyter notebooks
  • Install in venv with -> pip3 install jupyterlab
  • Run -> venv/bin/jupyter lab