AI Virtual Mouse Project

This project implements an AI-based virtual mouse using computer vision and hand tracking. The system uses a webcam to detect hand gestures and translates them into mouse movements and clicks, enabling hands-free control of the computer.

Video Demonstration

Watch the video below to see the AI Virtual Mouse in action: also uploaded in youtube

Features

• Hand Tracking: Detects and tracks hand landmarks using the Mediapipe library.
• Mouse Movement: Moves the mouse cursor based on the position of the index finger.
• Click Detection: Simulates mouse clicks when specific gestures are detected.
• Smooth Movement: Implements smoothening to reduce jitter in cursor movement.
• Real-Time Performance: Displays the webcam feed with real-time hand tracking and gesture recognition.

Requirements

• Python 3.8.0 or higher
• Libraries:
  • opencv-python
  • mediapipe
  • numpy
  • autopy

Installation

1. Clone the repository or download the project files.

2. Install the required Python libraries using the requirements.txt file:

   pip install -r requirements.txt

   This will install the following libraries with their specific versions:

   • opencv-python==4.5.5.64
   • mediapipe==0.9.1.0
   • numpy==1.21.6
   • autopy==4.0.0

   Please go with the Following command lines:

   pip install opencv-contrib-python
   pip install opencv-contrib-python
   pip install opencv-python mediapipe numpy autopy

3. Ensure your webcam is connected and functional.

Usage

1. Run the AiVirtualMouseProject.py script:

   python AiVirtualMouseProject.py

2. The webcam feed will open, and the system will start detecting your hand gestures.
3. Use the following gestures to control the mouse:
   • Move Cursor: Raise only the index finger and move it to control the cursor.
   • Left Click: Raise both the index and middle fingers, and bring them close together to simulate a click.
4. Press the q key to exit the program.

File Structure

• AiVirtualMouseProject.py: Main script for the virtual mouse functionality.
• HandTrackingModule.py: Module for hand detection and gesture recognition.
• requirements.txt: File containing the required libraries and their versions.
• ReadMe: Documentation for the project.

How It Works

1. Hand Detection: The HandTrackingModule uses Mediapipe to detect hand landmarks in the webcam feed.
2. Gesture Recognition: The system identifies which fingers are raised using the fingersUp method.
3. Mouse Control:
   • The index finger's position is mapped to the screen coordinates to move the cursor.
   • The distance between the index and middle fingers is calculated to detect clicks.
4. Smoothening: Cursor movement is smoothened using a weighted average to reduce jitter.

Troubleshooting

• Camera Not Detected: Ensure your webcam is connected and accessible. Check the cv2.VideoCapture index (0 or 1) in the code.
• Dependencies Missing: Install the required libraries using pip install -r requirements.txt.
• Performance Issues: Reduce the webcam resolution or frame rate for better performance.

Future Improvements

• Add support for right-click and drag gestures.
• Enhance accuracy and robustness of hand tracking.
• Implement multi-hand support for additional gestures.

License

This project is open-source and available for educational and personal use.

Acknowledgments

• Mediapipe for hand tracking.
• OpenCV for image processing.
• Autopy for mouse control.