/pytch

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Pytch

Pytch is an innovative open-source platform designed to revolutionize the world of soccer analytics. Developed at Texas A&M University's Department of Computer Science and Engineering, this project utilizes state-of-the-art machine learning and computer vision techniques to offer accessible, in-depth soccer match analysis to fans, analysts, and enthusiasts.

Features

  • Analytics: Pytch provides a range of soccer analytics including shotmaps, heatmaps, and passmaps.
  • User Uploads: Users can upload soccer footage to receive detailed analytics.
  • Custom Visualizations: Supports custom visualizations, allowing users to tailor their analytics experience.
  • Open-Source: Encourages community collaboration and innovation.

Getting Started

Prerequisites

  • Ensure you have Python and Node.js installed on your machine.
  • Basic knowledge of machine learning and computer vision concepts is beneficial.

frontend setup

  • cd frontend

  • Fill out env vars: cp .env.example .env

  • Install packages: npm install or pnpm i

  • database setup

    • Have docker running
      • start server: docker-compose up -d
      • if you want to stop: docker-compose down or in the docker app
    • push schema to db server: npx prisma db push or pnpm prisma db push
    • view database: npx prisma studio or pnpm prisma studio

  • start frontend: npm run dev or pnpm dev

backend setup

  • pip install cython
  • cd tracker/track
  • python -m pip install --upgrade pip==22.0.4
  • pip install -r requirements.txt
  • rm -rf ByteTrack
  • git clone git@github.com:ifzhang/ByteTrack.git --force
  • cd ByteTrack
  • pip install -r requirements.txt
  • python setup.py develop
  • cd ../..

Project Structure

  • db/: Contains database-related configurations and files.
  • docs/: Includes comprehensive documentation for the project.
  • frontend/: Houses the front-end code of the application.
  • tracker/: contains Yolov8 identification, ByteTrack, Team Detection, and Localization start with :flask --app app run -p 8080

Contributing

Contributions are what make the open-source community an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

Team

  • Gabriel Diaz - Computer Vision Engineer
  • Ryan Kutz - Computer Vision Engineer
  • Anthony Pasala - Backend Engineer
  • Joseph Quismorio - Frontend Development Head
  • Ryan Son - Project Manager
  • Shurui Xu - Database and Analytics Engineer