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🎾 GrandSlamVision 🎾

GrandSlamVision is a cutting-edge computer vision project that leverages the YOLO (You Only Look Once) algorithm to detect and track tennis balls 🎾 and players 🏃‍♂️ in real-time. This project aims to provide accurate and efficient detection for various applications such as sports analytics 📊, automated refereeing ⚖️, and player performance analysis 📈.

🌟 Features

  • Real-time detection of tennis balls 🎾 and players 🏃‍♂️
  • High accuracy and efficiency using the YOLO algorithm 🚀
  • Easy integration with video feeds 📹 and camera systems 📷
  • Customizable for different tennis court environments 🎾

🗺️ Roadmap

  • Ball detector: ✅ Yes
  • Player detector: ✅ Yes
  • Keypoint detector: ✅ Yes
  • Ball speed: 🚧 Planned
  • Player run distance and average speed: 🚧 Planned*

📊 Current State

Tennis Court

🛠️ Installation

  1. Clone the repository: 
    git clone https://github.com/yourusername/tennis-yolo.git
  2. Navigate to the project directory: 
    cd tennis-yolo
  3. Install the required dependencies: 
    pip install -r requirements.txt

🤝 Contributing

We welcome contributions to improve Tennis YOLO. Please fork the repository and submit a pull request with your changes. Ensure that your code follows the project's coding standards and includes appropriate tests.

📜 License

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

🙏 Acknowledgements

  • The YOLO algorithm by Joseph Redmon and Ali Farhadi
  • OpenCV for computer vision functionalities
  • PyTorch for deep learning support

📂 Project Structure

GrandSlamVision/
├── data/                # Dataset and configuration files
├── models/              # Pre-trained models and weights
├── output/              # Output images and videos
├── utils/               # Utility scripts and helper functions
├── detect.py            # Main detection script
├── requirements.txt     # List of dependencies
├── README.md            # Project documentation
└── LICENSE              # License file

📚 Resources