#Overview Using Extended Cohn-Kanade AU-Coded Facial Expression Database to classify basic human facial emotion expressions using ann
#Installation
The necessary dependencies are in the requirements.txt file so just run this before running the actual code to get them installed. May require some extra effort for OpenCV though.
pip3 install -r requirements.txt
#Usage
If you want a facial emotion classifier you can just download the Cohn-Kanade database and serialize the dataset according to your need and if you can you should also use another dataset with ck.
apply_haar_cascade.py => To apply the haar cascade for face detection it will overwrite the directory with 100x100 pixels images of faces. If face couldn't be detected then print the filename to console.
pickle_dataset.py => Pickles the dataset containing 100*100 images of faces
cnn.py => Convolution neural Network to train the the classifier
cohn-kanade-images.txt => contains some basic info about the dataset
#Credits
- Kanade, T., Cohn, J. F., & Tian, Y. (2000). Comprehensive database for facial expression analysis. Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), Grenoble, France, 46-53.
- Lucey, P., Cohn, J. F., Kanade, T., Saragih, J., Ambadar, Z., & Matthews, I. (2010). The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotion-specified expression. Proceedings of the Third International Workshop on CVPR for Human Communicative Behavior Analysis (CVPR4HB 2010), San Francisco, USA, 94-101.