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Analze emotions and see the result in real time

  1. Pull docker images and start containers
docker-compose up
  1. Load models, gear and script into redis
cd ai/
cat blazeface_back_converted.onnx | redis-cli -h redis -x AI.MODELSTORE blazeface:model ONNX CPU BLOB
cat emotion.onnx | redis-cli -h redis -x AI.MODELSTORE emotion ONNX CPU BLOB
cat blazeface-script.py | redis-cli -h redis -x AI.SCRIPTSET blazeface:script CPU SOURCE
cat gears-emotion.py | redis-cli -x RG.PYEXECUTE
  1. Add camera frames to redis stream
cd camera/
python3 edge-camera.py -u redis://redis:6379
  1. Visit the dashboard (Click refresh in the upper right corner to see frame latency updates)