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 eitherimage
for image demo,webcam
for webcam demo orvideo
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 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
- 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