This software recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.
- Download the fer2013.tar.gz file from here
- Move the downloaded file to the datasets directory inside this repository.
- Untar the file:
tar -xzf fer2013.tar - Download train_emotion_classifier.py from orriaga's repo here
- Run the train_emotion_classification.py file:
python3 train_emotion_classifier.py
The model used is from this research paper written by Octavio Arriaga, Paul G. Plöger, and Matias Valdenegro.
- Computer vision powered by OpenCV.
- Neural network scaffolding powered by Keras with Tensorflow.
- Convolutional Neural Network (CNN) deep learning architecture is from this research paper.
- Pretrained Keras model and much of the OpenCV code provided by GitHub user oarriaga.