Emotion

This software recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.

Installation

Clone the repository:

git clone https://github.com/petercunha/Emotion.git
cd Emotion/

Install these dependencies with pip3 install <module name>

• tensorflow
• numpy
• scipy
• opencv-python
• pillow
• pandas
• matplotlib
• h5py
• keras

Once the dependencies are installed, you can run the project. python3 emotions.py

To train new models for emotion classification

• 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

Deep Learning Model

The model used is from this research paper written by Octavio Arriaga, Paul G. Plöger, and Matias Valdenegro.

Credit

• 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.