Emotion Detection System

This project is an Emotion Detection System implemented in Python. It uses computer vision and deep learning techniques to detect and classify emotions in real-time from webcam feed.

Features

• Real-time emotion detection from webcam feed
• User interface for starting emotion detection sessions
• Emotion frequency visualization
• Saving emotion detection results for individual users

Components

1. Main Application (main.py)

   • Implements a simple graphical user interface using tkinter
   • Allows users to enter their name and start an emotion detection session

2. Emotion Detection (detection.py)

   • Loads a pre-trained convolutional neural network model
   • Performs real-time face detection and emotion classification

3. Emotion Detection Session (start_detection.py)

   • Manages the emotion detection process
   • Handles webcam feed and user interactions during the session
   • Saves emotion frequency graphs for individual users

4. Graph Visualization (show_graph.py)

   • Provides functionality to display emotion frequency graphs

5. Model Training (training.py)

   • Defines and trains the convolutional neural network for emotion detection
   • Uses image data generators for efficient training
   • Saves the trained model weights

Requirements

• Python 3.x
• OpenCV
• TensorFlow
• Tkinter
• Matplotlib
• NumPy