Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
| Date | Stars |
|---|---|
| 2026-07-31 | 255 |
| 2026-08-04 | 255 |
| 2026-08-06 | 255 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Football Analytics with Deep Learning and Computer Vision
**Project goal:** Create a web application to automate football analysis, and provide useful information that helps in decision making.
**Current stage:** Developing a streamlit web application for football object detection with tactical map representation.
## Installation & How to use?
Steps:
1. Clone the repository using the command `git clone https://github.com/Hmzbo/Football-Analytics-with-Deep-Learning-and-Computer-Vision.git `
2. Install the required libraries listed in the file `requirement.txt`, you can use the command `conda env create -f environment.yml` to create the conda env I use but make sure the pytorch installation is compatible with your machine.
3. Use the command `steamlit run main.py` to start the application.
## Dataset Used
- Players detection: [link](https://www.kaggle.com/datasets/hamzaboulahia/football-players-detection-dataset)
- Field keypoints detection: [link](https://www.kaggle.com/datasets/hamzaboulahia/football-field-keypoints-dataset)
## Features
- Detect players, referees and ball.
- Predict players teams based on predefined team colors.
- Build a tactical map representation.
- Track ball movements.
## Application Workflow
The journey of the input video and different functionalities are illustrated in the workflow diagram below.
Excerpt of 1,520 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e000ab53addd7e8e, name:computer vision