The emotions being classified are Neutral, Anger, Contempt, Disgust, Fear, Happy, Sad, Surprise
The emotions being classified are Neutral, Anger, Contempt, Disgust, Fear, Happy, Sad, Surprise
To train the model from scratch -
- Download the Cohn-Kanade dataset.
- Create a folder named "data" in the project directory.
- And paste the dataset with the name "Dataset_images" and emotions with the name "Emotion" in the above created folder.
- Finally, open terminal in the project directory and then type in-
python train.py
After training or if you directly want to try the trained model -
python main.py
Dependencies -
- Numpy
- Pandas
- scikit-learn
- opencv
The emotions being classified are Neutral, Anger, Contempt, Disgust, Fear, Happy, Sad, Surprise
Currently the accuracy on the test data is 53.42% and live feed is not performing great.
The size of the dataset is not large enough to classify 8 different emotions, so probably train on less number of classes?
Currently under development