- Download FER2013 dataset from kaggle and put
train.csvtest.csvunder./dataset. Note that you need to manually add label column intest.csv. - Then run
python generate_data.py, which will create training, validation and test images set under./dataset/images.
- SVM: run
python svm.py. Refer to the code to change some settings. - CNN: run
python train_cnn.pyto train. runpython test_cnn.pyto test. You can set your own arguments (please refer to the code).demo.pyprovides a simple demo to predict expression probability given an image.