zakroum-hicham/football-analysis-CV
This repository contains a computer vision/machine learning football project that uses YOLO for object detection, Kmeans for pixel segmentation, and perspective transformation to analyze player movements in football videos
This project helps football coaches, analysts, and scouts deeply understand team and player performance by analyzing match footage. It takes raw football video as input and outputs detailed metrics on ball possession, individual player movements (in meters), and team assignments. It's designed for anyone needing to extract actionable insights from game film beyond what standard statistics provide.
No commits in the last 6 months.
Use this if you need to automatically extract quantitative data like ball possession percentages and exact player distances moved from football match videos.
Not ideal if you're looking for real-time analysis during a live game, as it's built for post-match video processing.
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Last pushed
Oct 24, 2024
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