Face and Emotion Recognition

This software recognizes person's faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV, Dlib, face_recognition and Deep Learning.

Demo

Dependencies

• Opencv
• Dlib
• face_recognition
• Keras

Usage

• Download a shape_predictor_68_face_landmarks.dat file from here and put in the folder.
• test folder contain images or video that we will feed to the model.
• images folder contain only images of person face to perform face recognition.
• models contain the pre-trained model for emotion classifier.
• emotion.py can to run to classify emotions of person's face.
• face-rec-emotion.py can recognise faces and classify emotion at a time.
• face_recognition library uses the FaceNet Implementation for face recognition.For more details please visit here

python emotion.py

python face-rec-emotion.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: python 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.
• FaceNet Research Paper
• 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.