Introduction

This project is a facial emotion detection system that uses a convolutional neural network to detect facial emotions. The model is trained on the FER-2013 dataset which consists of 48x48 pixel grayscale images of faces with 7 different emotions:

• Angry
• Disgust
• Fear
• Happy
• Sad
• Surprise
• Neutral

Web Application

The web application backend is built using Flask and the front-end is created using SvelteJS. The application allows the user to either capture an image of themselves or upload an image and the model will predict the emotion of the person in the image.

The application is live and can be accessed at https://fer.rohand.in.