PoseCheck Pro: AI-Powered Exercise Trainer

PoseCheck Pro is an AI-powered web app that guides you through home workouts with real-time posture correction, audio instructions, and personalized stats. Built for a hackathon, it ensures safe exercise form using computer vision, helping prevent injuries from improper squats or arm raises. Whether you're a fitness enthusiast or a developer exploring health tech, PoseCheck Pro offers a seamless, webcam-based fitness experience.

Features

• Real-Time Posture Correction: Uses Mediapipe to track pose landmarks, providing instant feedback (e.g., "Level your shoulders") for arm raises (150-210° angles) and squats (50-90° knee angle).
• Audio Guidance: Delivers step-by-step instructions (e.g., "Hold arms up for 3 seconds") via gTTS, cached as MP3s, played without a visible play bar using JavaScript.
• Personalized Stats: Tracks reps, exercise duration (starts when camera activates), and calories burned (MET-based) based on user height and weight.
• Intuitive UI: Streamlit-powered interface with a two-column layout (webcam feed/debug on left, feedback on right) and sidebar for exercise selection (Arm Raise, Squat) and reps.
• Webcam-Only: Runs on any device with a webcam, with calibration tips for optimal tracking (e.g., "Stand 3-6 feet from camera").

Screenshots

Technologies

• Python: Core language for app logic.
• Streamlit: Web framework for the UI.
• Mediapipe: Pose estimation for landmark tracking.
• OpenCV: Webcam video capture and processing.
• gTTS: Text-to-speech for audio instructions.
• pydub: Audio processing and MP3 caching.
• FFmpeg: Backend for pydub audio operations.
• JavaScript: Audio playback via Streamlit components.
• NumPy: Coordinate and angle calculations.
• Math: Angle computations (atan2, degrees).

Prerequisites

• Python 3.8+
• A webcam (built-in or external)
• FFmpeg installed and added to system PATH
• Git (for cloning the repository)

Installation

1. Clone the Repository:

   git clone https://github.com/Pythonpreran/Posecheck-Pro.git
   cd Posecheck-Pro

2. Install Python Dependencies:

   pip install streamlit opencv-python mediapipe gTTS pydub

3. Install FFmpeg:

   • Windows:
     1. Download FFmpeg from ffmpeg.org or a trusted source (e.g., gyan.dev).
     2. Extract the archive (e.g., to C:\ffmpeg).
     3. Add C:\ffmpeg\bin to your system PATH:
        • Right-click 'This PC' > Properties > Advanced system settings > Environment Variables.
        • Edit 'Path' under System variables, add C:\ffmpeg\bin, and click OK.
     4. Verify: Open Command Prompt and run ffmpeg -version.
   • macOS:

     brew install ffmpeg

   • Linux:

     sudo apt-get install ffmpeg

4. Verify Setup:

   • Ensure a webcam is connected.
   • Check Python version: python --version (should be 3.8+).
   • Confirm FFmpeg: ffmpeg -version.

Usage

1. Run the App:

   streamlit run main.py

2. Interact with the App:

   • Open the provided URL (e.g., http://localhost:8501) in a browser.
   • In the sidebar:
     • Select an exercise (Arm Raise or Squat).
     • Set number of repetitions (1-20).
     • Enter height (100-250 cm) and weight (30-200 kg).
   • Click Start Exercise to begin.
   • Follow calibration tips (good lighting, 3-6 feet from camera, full body visible).
   • Watch the webcam feed for pose landmarks and listen to audio instructions.
   • View real-time feedback and workout summary (reps, time, calories) upon completion.

3. Reset or Stop:

   • Click Reset Exercise in the sidebar to restart.
   • Close the terminal to stop the app.

Project Structure

Posecheck-Pro/
├── main.py             # Main Streamlit app
├── audio_cache/        # Directory for cached MP3 audio files (auto-generated)
├── README.md           # This file
└── requirements.txt    # Optional: List of dependencies (recommended)

Troubleshooting

• Webcam Not Found: Ensure a webcam is connected and accessible. Check cv2.VideoCapture(0); try 1 or 2 if multiple cameras exist.
• FFmpeg Error: Verify FFmpeg is in PATH (ffmpeg -version). Reinstall if needed.
• Mediapipe Warnings: Ensure frame dimensions are set (640x480 in code). Update Mediapipe if errors persist (pip install --upgrade mediapipe).
• Audio Not Playing: Check browser autoplay settings. Ensure audio_cache directory is writable.
• Performance Lag: Reduce webcam resolution or use a lower model_complexity in Mediapipe (e.g., 0 instead of 1).

Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a branch: git checkout -b feature/your-feature.
3. Commit changes: git commit -m "Add your feature".
4. Push to the branch: git push origin feature/your-feature.
5. Open a pull request with a clear description.

Please follow the Code of Conduct and report issues via GitHub Issues.

License

This project is licensed under the MIT License. See LICENSE for details.

Acknowledgments

• Built for the hackathon Neural Nexus to explore health tech and AI.
• Inspired by the need for safe home workouts.
• Thanks to Mediapipe, Streamlit, and gTTS communities for amazing tools.

Contact

For questions or feedback, reach out via GitHub Issues or connect on LinkedIn.