https://github.com/mozturan/fc_ai

Football Match Analysing Tool
https://github.com/mozturan/fc_ai

analytics computer-vision deep-learning image-processing kmeans optical-flow supervision ultralytics yolo

Last synced: 3 months ago
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Football Match Analysing Tool

• Host: GitHub
• URL: https://github.com/mozturan/fc_ai
• Owner: mozturan
• Created: 2024-06-25T09:40:29.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-06-26T18:47:55.000Z (over 1 year ago)
• Last Synced: 2025-04-09T09:49:20.693Z (6 months ago)
• Topics: analytics, computer-vision, deep-learning, image-processing, kmeans, optical-flow, supervision, ultralytics, yolo
• Language: Python
• Homepage:
• Size: 58.6 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Football Match Analising Tool

Goal is to detect players, ball, referees and extract some features and values using **computer vision techniques** to analyse the match. What implemented so far is:

- Train **YOLOv5** with a proper football match dataset to find objects

- **Kmeans** for pixel segmentation and clustering to detect t-shirt color

- Using **optical flow** to estimate camera movement to improve analysis

- **Perspective transformation** to respresent scenes depth for better

- **Speed and distance calculation** for the players

- Different drawing styles than bbox

![11](https://github.com/mozturan/fc_AI/assets/89272933/8bf87054-c5ea-4a88-8b05-50cffa773b80)

NOTE: The software implemented on this [dataset on Kaggle](https://www.kaggle.com/competitions/dfl-bundesliga-data-shootout/data?select=clips) and **Yolov5** is trained with this [dataset on Roboflow](https://universe.roboflow.com/roboflow-jvuqo/football-players-detection-3zvbc/dataset/1)