# abdullahtarek/football_analysis

This repository contains a comprehensive computer vision/machine learning football project that uses YOLO for object detection, Kmeans for pixel segmentation, optical flow for motion tracking, and perspective transformation to analyze player movements in football videos

Repository: https://github.com/abdullahtarek/football_analysis
Canonical: https://ross.abutalabs.com/products/football_analysis
Language: Jupyter Notebook
License Family: other
Last push: 2024-04-23T09:06:13+00:00

## Health v2 (maintenance only)
Score: 24/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 61
- inputs: {"age_days": 867, "days_push": 862, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1003, forks 337 (observed 2026-09-03T02:15:08.756109+00:00)

## Summary
No AI-extracted summary yet.

## Member repositories
- abdullahtarek/football_analysis (main) score 24

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:08.756109+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Data as of 2026-08-30T08:39:29.467469+00:00.