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 📈.
- 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 🎾
- Ball detector: ✅ Yes
- Player detector: ✅ Yes
- Keypoint detector: ✅ Yes
- Ball speed: 🚧 Planned
- Player run distance and average speed: 🚧 Planned*
- Clone the repository:
git clone https://github.com/yourusername/tennis-yolo.git
- Navigate to the project directory:
cd tennis-yolo - Install the required dependencies:
pip install -r requirements.txt
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.
This project is licensed under the MIT License. See the LICENSE file for details.
- The YOLO algorithm by Joseph Redmon and Ali Farhadi
- OpenCV for computer vision functionalities
- PyTorch for deep learning support
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