Gaze Detection with Visual Feedback

This project is a Python-based implementation of gaze detection using Mediapipe's Face Mesh solution. The program detects and tracks the position of the eyes and irises in real-time using a webcam, providing visual feedback by overlaying markers on the video feed.

Features

• Real-time detection of facial landmarks using Mediapipe's Face Mesh.
• Identification of eye and iris positions.
• Visual feedback with circles drawn around eye and iris landmarks.
• Visualization of the average iris center for both eyes.

Requirements

To run this project, you need the following:

• Python 3.7 or higher
• OpenCV
• Mediapipe
• NumPy

Installation

1. Clone the repository:

   git clone https://github.com/Real-J/gaze-detection.git
   cd gaze-tracking

2. Install the required dependencies:

   pip install opencv-python mediapipe numpy

Usage

1. Run the Python script:

   python gazeupdate.py

2. Allow access to your webcam.

3. The program will display a window showing the live webcam feed with the following visual feedback:

   • Green circles: Eye landmarks
   • Red circles: Iris landmarks
   • Yellow circle: Combined center of the left and right irises

4. Press the q key to exit the program.

Code Overview

The main script (gazeupdate.py) includes the following components:

• Initialization: Setting up Mediapipe Face Mesh and OpenCV.
• Eye and Iris Landmark Detection: Extracting facial landmarks corresponding to the eyes and irises.
• Visual Feedback: Drawing circles on eye and iris landmarks, and calculating the average iris center.
• Webcam Loop: Continuously processing frames from the webcam and displaying visual feedback.

Contributing

Contributions are welcome! Feel free to open an issue or submit a pull request if you have suggestions or improvements.

License

This project is licensed under the MIT License.

Acknowledgements

• Mediapipe for the Face Mesh solution.
• OpenCV for real-time video processing.
• NumPy for numerical computations.