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Mlface compares an image (containing a face) and compares it to a list of known 'people' and returns the name of the person or 'None'.

mlface can be run as a Docker container or as a standalone, systemd managed application. It listens on a websocket on port 4785. A base64 encoded jpg is sent to '/' path. A json response is returned which contains the name if matched. A face enclosing rectangle is returned, assume there is a face.

{'details': {'plug': 'face', 'name': 'face', 'reason': 'face', 'matrices': [{'x': 64, 'y': 333, 'width': 132, 'height': 265, 'tag': 'cecil', 'confidence': 1.0}], 'imgWidth': 640, 'imgHeight': 480, 'time': 0.041136} }

Docker required the ccoupe:dlib image with requires the

$ nvidia-docker build -t ccoupe:mlface .

$ nvidia-docker run -dp 4785:4785 -v /home/ccoupe/known_faces:/known_faces
--name=mlface ccoupe:mlface

known_faces//.jpg, known_faces//.jpg,,, known_faces//.jpg,,, known_faces//.jpg,,,

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Face Recognition with Python and Websocket

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