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Using open cv facial landmark detection for identifying yawns and blinking of eyes to determine drowsiness.

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drowsiness_detection

Capturing 120 frames Time taken : 3.99575185776 seconds Estimated frames per second : 30.0318949404

For running on local

-- to get embeddings from the face dataset

python extract_embeddings.py --dataset dataset
--embeddings output/embeddings.pickle
--detector face_detection_model
--embedding-model openface_nn4.small2.v1.t7

-- for training the model

python train_model.py --embeddings output/embeddings.pickle
--recognizer output/recognizer.pickle
--le output/le.pickle

-- for final video to show all

python inside_camera.py --detector face_detection_model
--embedding-model openface_nn4.small2.v1.t7
--recognizer output/recognizer.pickle
--le output/le.pickle
--shape-predictor shape_predictor_68_face_landmarks.dat

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Using open cv facial landmark detection for identifying yawns and blinking of eyes to determine drowsiness.

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