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 --face_group_dir ./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 serverContribution
Contributions are welcome. Feel free to raise PRs! with any improvements.
Credit
Face Encoder model: https://github.com/nyoki-mtl/keras-facenet
