Emotion-detection

Introduction

This project aims to classify the emotion on a person's face into one of seven categories, using deep convolutional neural networks. This repo is an implementation of this research paper.

Dependencies:

• Python 3.5+, OpenCV 3.0, TFlearn.

Usage

• Clone the repository and download the trained model files from here, extract it and copy the files into the current working directory.

• To run the program to detect emotions only in one face, type python em_model.py singleface.

• To run the program to detect emotions on all faces close to camera, type python em_model.py multiface.

Algorithm

• First, we use haar cascade to detect faces in each frame of the webcam feed.

• The region of image containing the face is resized to 48x48 and is passed as input to the ConvNet.

• The network outputs a list of softmax scores for the seven classes.

• The emotion with maximum score is displayed.

Example Output