Demo project to detect if eye is open or closed

python -m demo --process image --path /path/to-image --json_path /path/to-model/json/file --weights /path/to/weights of the model

Where

• --process demo type. It can be either image for image demo, webcam for webcam demo or video for video demo.
• --path is full path to image.
• --json_path path to model's json file
• --weights path to weights of model(h5 file)

python -m demo  --process video --path /path-to-video/video-file --json_path /path/to-model/json/file --weights /path/to/weights of the model

Where --path is full path to video.

python -m demo --process webcam --json_path /path/to-model/json/file --weights /path/to/weights of the model

• tensorflow >= 1.0

• keras >= 2.0

• opencv >= 3.0

• dlib

• numpy

• shape_predictor_68_face_landmarks.dat

• opencv should be compiled with ffmpeg support.
• Conda virtual environment can be created using the following command.

conda env create -f requirements.yml -n emopy_2

• shape_predictor should be inside root directory of this project. Shape predictor can be downloaded to project using the following script.

cd /path-to-project
wget "http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2"
bzip2 -d shape_predictor_68_face_landmarks.dat.bz2