SixtySevenDetector

A high-performance computer vision system designed to detect the 67 gesture and trigger real-time multimedia responses. The system uses YOLO-Pose for motion tracking and provides live performance analytics.

Features

• Real-time Gesture Detection: Uses advanced pose estimation to track wrist oscillation.
• Multimedia Integration: Automatically plays audio and displays image overlays upon successful detection.
• Performance Analytics: Tracks total detections and frequency (67s per minute).
• Optimized Pipeline: Non-blocking audio playback and efficient frame processing.

Setup

Prerequisites

• Python 3.8+
• macOS (required for native audio playback via afplay)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/SixtySevenDetector.git
   cd SixtySevenDetector

2. Install dependencies:

   pip install -r requirements.txt

3. Add your assets: Create an assets/ directory in the root and add the following files:

   • assets/sound.mp3: The sound effect to play.
   • assets/67_kid.jpg: The image to overlay.

Usage

Run the main detection script:

python3 main.py

Perform the 67 gesture (rapid up-and-down wrist movement) in front of the camera to trigger the system.

Configuration

• Detection Sensitivity: Adjusted in src/detector.py via MIN_MOVEMENT_PIXELS.
• Audio Cooldown: Managed in src/action.py (default: 10 seconds).
• Image Duration: Managed in main.py (default: 0.5 seconds).

Development

The project is structured modularly:

• main.py: Entry point and UI overlay logic.
• src/detector.py: Core gesture analysis.
• src/action.py: Multimedia trigger handling.
• src/vision.py: Camera stream management.

License

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

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Disclaimer: This project is for educational and entertainment purposes.