Face Recognition and Emotion Detection

Trained a CNN classifier using 'FER-2013 dataset' with Keras and tensorflow backened. The classifier sucessfully predicted the various types of emotions of human. And the highest accuracy obtained with the model was 60.1%. Then used Open-CV to detect the face in an image and then pass the face to the classifer to predict the emotion of a person.