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
Cmake
Dlib
face_recognition
Keras

Note : If you are facing issues installing dlib in your system then use google collab its comes as pre-installed.

Usage

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.

Model

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.