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State of Art detection and monitoring system for football video feed. . This project is capable of being deployed in industrial purposes upon improvements and adaptions. It is well sectioned and easy to interpret and provides excellent accuracy and performance.

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chiragHimself/FootballAnalyserYolo

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Football Player Detection and Monitoring System Using YOLO.

Welcome to the Football Player Detection and Monitoring System! This project is an industry-level endeavor aimed at providing precise detection and monitoring capabilities for football players, referees, and the ball using state-of-the-art YOLO models and various utility libraries.

Demo Demo

Features

  • Player Tracking: Track individual players with high precision.
  • Team Separation: Distinguish between players from different teams.
  • Camera Movement Tracking: Monitor camera movements for enhanced analysis.
  • Distance and Speed Monitoring: Calculate distance covered by players and their speed during movement.
  • Ball Tracking: Accurately trace the movement of the ball.
  • Team Possession Analysis: Analyze team possession based on player movements.

Libraries Used

  • Python
  • OpenCV
  • Supervision
  • NumPy
  • Pandas
  • Matplotlib
  • YOLO

Installation

Clone the repository:

 <bash>

git clone https://github.com/chiragHimself/FootballAnalyserYolo.git

Folder Structure

  • models: Contains YOLO model weights.
  • scripts: Houses all the Python scripts.
  • output: Stores the output generated by the system.

Usage

  1. Configure the system by modifying parameters in the scripts if needed.
  2. Run the main script to start the detection and monitoring process.
  3. View the output generated in the output folder.

Demo

Demo

Contribution

Contributions are welcome! Feel free to submit issues, feature requests, or pull requests to improve the system.

Credits

This project was created by [Chirag Sharma]. Reference : Abdullah Tarek - Youtube

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State of Art detection and monitoring system for football video feed. . This project is capable of being deployed in industrial purposes upon improvements and adaptions. It is well sectioned and easy to interpret and provides excellent accuracy and performance.

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