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Project description

Python 3.6 License

Access Face Vision

Face detection and recognition Application.

With pip

  • Installation
pip install access-face-vision
  • Training/Creating FaceGroup
python -m access_face_vision --mode train --img_dir samples/celebrities --face_group celebrities

# Directory structure
# **/Images/
#          A/
#           A_K_01.jpg
#           A_K_02.jpg
#          B/
#           B_S_01.jpg
#           B_S_02.jpg
  • Running Inferences
# Live video feed
>python -m access_face_vision --mode live-video --camera-index 0 --camera_wait 30 --face_group celebrities

# server mode
python -m access_face_vision --mode server

Use access-client to make requests to this server

Docker image

  • Docker Image build
docker build -t access_face_vision:latest .
  • Docker run
# we will use it as root directory for access_face_vision application
mkdir -p accessai/afv

# Start server
docker run -v $(pwd)/afv:/accessai/afv python -m access_face_vision --mode server

# Start camera feed processor
docker run -v $(pwd)/afv:/accessai/af v python -m access_face_vision --mode server

Contribution

Contributions are welcome. Feel free to raise PRs! with any improvements.

Credit

Face Encoder model: https://github.com/nyoki-mtl/keras-facenet

Project details


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