تحليل مباراة التنس في الوقت الحقيقي باستخدام الرؤية الحاسوبية

This project leverages advanced computer vision techniques to provide real-time analytics for tennis matches. The system delivers precise and insightful data on player movements, ball trajectories, and court dynamics, enabling a detailed understanding of the game.

Key Features:

Player and Ball Detection:

Accurate real-time detection and tracking of players and the tennis ball.

Recognition of key events such as ball hits and bounces.

Court Analysis:

Detection and mapping of the tennis court for precise spatial understanding.

Integration of court boundaries for enhanced accuracy in tracking.

Heatmap Generation:

Detailed heatmaps showing player movement patterns throughout the match.

Visualization of ball bounces to analyze gameplay strategy and shot effectiveness.

High Accuracy and Speed:

Designed for real-time performance with minimal latency.

Achieves high detection precision even during fast-paced gameplay.

Technologies Used:

Computer Vision: OpenCV and deep learning models for real-time detection and tracking.

Frameworks: PyTorch for model training and optimization.

Hardware: Optimized for GPU acceleration to ensure real-time processing.

Visualization: Heatmaps and analytics generated using Matplotlib and custom visualization tools.

Impact:

This system is a game-changer for tennis analytics, providing valuable insights for players, coaches, and broadcasters. By combining real-time performance with detailed visualizations, it enhances understanding of player strategies and match dynamics, paving the way for data-driven decision-making in the world of sports.