AI-GYM: AI-Powered Workout Assistant 💪

Intelligent Fitness Assistant Based on RTMPose

English | 中文

🆕 Changelog

• 2024-06-07: Major update! Dropped YOLO models and all GPU support. Now uses only RTMPose for pose detection, and runs on CPU only. Simpler, more compatible, and easier to use.

---

🌟 Features

• Real-time Exercise Counting - Automatically counts your repetitions
• Multiple Exercise Support - Including squats, push-ups, sit-ups, bicep curls, and many more
• Advanced Pose Detection - Powered by RTMPose for accurate tracking
• CPU Only - No GPU required, works on most computers
• Visual Feedback - Live skeleton visualization with angle measurements
• Workout Statistics - Track your progress over time
• User-friendly Interface - Clean PyQt5 GUI with intuitive controls
• Works with any webcam - No special hardware required
• Runs locally - Complete privacy

📦 Direct Download

• If you don't want to set up a Python environment, you can download our pre-packaged executable:

  Windows EXE package:

  Baidu Netdisk Link code: 8866

  Google Drive

  Note: Windows version requires an NVIDIA GPU and proper drivers to run

📝 Usage Guide

Controls

• Use the interface buttons to select different exercises
• Real-time feedback shows your current form and repetition count
• Press the "Reset" button to reset the counter
• Use manual adjustment buttons to correct the count if needed
• Toggle skeleton visualization on/off
• View your workout statistics over time

📋 Requirements

• Python 3.9
• Webcam
• Windows/Mac/Linux: CPU only, no GPU required. Performance may vary by hardware.

🚀 Environment Setup

Installation

1. Clone and install

   git clone https://github.com/buke18/AI-gym.git
   cd Good-GYM
   
   # Create virtual environment
   python -m venv venv
   # Activate (Windows)
   .\venv\Scripts\activate
   # or (Mac/Linux)
   source venv/bin/activate
   
   # Install dependencies
   pip install -r requirements.txt

2. Run the application

   python workout_qt_modular.py

🖼️ Screenshots

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔮 Future Development

• Add support for more exercise types
• Improve pose detection accuracy
• Add voice feedback
• Multi-language interface