openface/docs/demo-1-web.md

Demo 1: Real-Time Web Demo

See our YouTube video of using this in a real-time web application for face recognition. The source is available in demos/web. The browser portions have been tested on Google Chrome 46 in OSX.

This demo does the full face recognition pipeline on every frame. In practice, object tracking like dlib's should be used once the face recognizer has predicted a face.

In the edge case when a single person is trained, the classifier has no knowledge of other people and labels anybody with the name of the trained person.

The web demo does not predict unknown users. If you're interested in predicting unknown people, one idea is to use a probabilistic classifier to predict confidence scores and then call the prediction unknown if the confidence is too low. See the classification demo for an example of using a probabilistic classifier.

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Setup

To run on your system, first follow the Setup Guide and make sure you can run a simpler demo, like the comparison demo.

Next, install the requirements for the web demo with ./install-deps.sh and sudo pip install -r requirements.txt from the demos/web directory. This is currently not included in the Docker container. The application is split into a processing server and static web pages that communicate via web sockets.

Start the HTTP and WebSocket servers on ports 8000 and 9000, respectively, with ./demos/web/start-servers.sh. If you wish to use other ports, pass them as ./demos/web/start-servers.sh HTTP_PORT WEBSOCKET_PART. You should now be able to send a request to the websocket connection with curl your-server:9000 (localhost:9000 if running on your machine), which should inform you that it's' a WebSocket endpoint and not a web server. Please check routing between your client and server if you get connection refused issues. You should now also be able to access the demo from your browser at http://your-server:8000. The saved faces are only available for the browser session.

If you experience issues running these commands, please post the WebSocket log contents from /tmp/openface.websocket.log to our mailing list.