Football Vision Analyzer is a real-time football match analysis system leveraging computer vision and deep learning to detect and track players, the ball, and key in-game events. Using a pre-trained object detection model fine-tuned for football, the application processes live match footage to identify player positions, track ball movement, and extract tactical patterns. The system provides rich, structured datasets that can be used for performance analytics, tactical reviews, and automated highlight generation. Designed for real-time performance, the project combines optimized video processing pipelines with advanced model inference, enabling instant feedback during matches.
Player Detection
Automatically detects and identifies all players on the field using deep learning models.
Ball Tracking
Tracks the ball’s position and movement in real-time, even during fast plays.
Tactical Analysis
Generates live positional data to analyze team formations and movement patterns.
Real-Time Processing
Optimized for low-latency analysis, delivering insights as the game unfolds.