AIR TRACKER

AIR TRACKER is an innovative application that enables gesture-based control for PowerPoint presentations and other functionalities. It uses computer vision and hand gesture recognition to provide a seamless, touch-free experience.

Features

• Gesture Based Control: Navigate slides, zoom in/out, and toggle video playback using hand gestures.
• Virtual Canvas: Draw, highlight, or erase on a virtual canvas overlay.
• Camera Feed Overlay: Display a live camera feed during presentations.
• PowerPoint Integration: Open, control, and close PowerPoint presentations programmatically.
• Customizable Tools: Switch between pen, highlighter, and eraser tools with ease.

Installation

1. Clone the repository:

   git clone https://github.com/saadkhi/AIR-TRACKER.git
   cd AIR-TRACKER

2. Install the required dependencies:

   pip install -r requirements.txt

3. Ensure you have a webcam connected for gesture detection.

Usage

1. Run the application:

   python main.py

2. Use the graphical unit to upload a PowerPoint file and start the presentation.

3. Use the following gestures for control:

   • Index and Pinky Fingers Up: Toggle the virtual canvas.
   • Thumb Up: Move to the previous slide.
   • Pinky Up: Move to the next slide.
   • Four Fingers Up: Zoom out.
   • Three Middle Fingers Up: Zoom in.
   • Thumb and Pinky Up: Close the application.

4. Use the virtual canvas to draw, highlight, or erase using the tools provided.

Project Structure

AIR-TRACKER/
├── main.py               # Main GUI application
├── utils.py              # Utility functions for PowerPoint control
├── canvas_handler.py     # Virtual canvas overlay functionality
├── camera.py             # Camera feed and gesture processing
├── requirements.txt      # Project dependencies
├── media/                # Media assets (icons, images)
├── models/               # Models
└── README.md             # Project documentation

Requirements

• Python 3.8 or higher
• A webcam for gesture detection
• Windows OS (for PowerPoint integration only )

Dependencies

The project uses the following Python libraries:

• customtkinter
• Pillow
• opencv-python
• cvzone
• mediapipe
• numpy
• keras
• pyautogui
• pynput
• comtypes
• pywin32
• matplotlib
• scipy

Refer to requirements.txt for exact versions.

Known Issues

• Ensure the PowerPoint file is valid and accessible.
• The application is optimized for Windows OS and may not work on other platforms.

License

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

Acknowledgments

• Mediapipe for hand tracking.
• OpenCV for image processing.
• CustomTkinter for the modern GUI.

Feel free to contribute to the project by submitting issues or pull requests! Thank you.