Facial Emotion Detector

Table of Contents

• Introduction
• Installation
• Usage
• Repository Structure

Introduction

Facial Emotion Detector is a deep learning project that can detect human emotions from facial expressions in real-time using a computer's webcam. This README file provides an overview of the project, instructions for installation and usage, and details on how the model was trained.

Installation

1. Clone this repository to your local machine.

git clone https://github.com/your-username/Facial-Emotion-Detector.git

Usage

Training the Model

1. The images folder contains the required dataset

2. Get trained model from Train_CNN.ipynb notebook.

Detecting Emotions in Real-time

To detect emotions in real-time using your computer's webcam:

1. Ensure you have a trained model (model.h5) in the project directory.

2. Run the main script.

   python main.py

The webcam feed will open, and the emotions detected from the facial expressions will be displayed in real-time.

Repository Structure

The repository structure is as follows:

• images/: This directory should contain the Face Expression Recognition Dataset.

• train_CNN.ipynb: Jupyter notebook for training the emotion detection model.

• main.py: Python script for real-time emotion detection using the trained model.