✨ Hand Gesture Recognition System | Task 3 - Prodigy InfoTech ML Internship ✨

🌟 Project Overview

Welcome to our cutting-edge Hand Gesture Recognition System! This project harnesses the power of deep learning to recognize and classify different hand gestures in real-time, creating an intuitive bridge between human movements and computer interactions.

🎯 Features

• Real-time hand gesture recognition
• Support for 10 different hand gestures
• User-friendly Streamlit interface
• High accuracy deep learning model
• Comprehensive data preprocessing pipeline

🚀 Quick Start

1. Clone this repository

git clone https://github.com/yourusername/hand-gesture-recognition.git
cd hand-gesture-recognition

2. Install dependencies

pip install -r requirements.txt

3. Run the application

streamlit run app.py

📁 Project Structure

hand-gesture-recognition/
├── data/                  # Dataset directory
├── models/               # Trained model files
├── src/
│   ├── preprocessing.py  # Data preprocessing utilities
│   ├── model.py         # Model architecture
│   ├── train.py         # Training script
│   └── utils.py         # Helper functions
├── app.py               # Streamlit application
├── requirements.txt     # Project dependencies
└── README.md           # Project documentation

🛠️ Technologies Used

• Python 3.8+
• TensorFlow/Keras
• OpenCV
• Streamlit
• NumPy
• Pandas

📈 Model Performance

• Training Accuracy: ~95%
• Validation Accuracy: ~93%
• Supports 10 different gesture classes

🎮 Supported Gestures

1. Palm
2. L Gesture
3. Fist
4. Thumb Up
5. Index Point
6. OK Sign
7. Down Sign
8. Peace Sign
9. Stop Sign
10. Victory Sign

🌟 About Prodigy InfoTech Internship

This project was developed as Task 3 of the Prodigy InfoTech Machine Learning Internship program. The internship focuses on building practical, real-world applications using cutting-edge machine learning technologies.

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page.

👏 Acknowledgments

• Prodigy InfoTech for the amazing internship opportunity
• The original dataset creators and researchers
• The open-source community for their invaluable tools and libraries

Made by AbdElKader Seif El Islem RAHMANI