https://github.com/shib-sankar-das/eye-mouse-controller

🖱️👀 Eye-Controlled Mouse uses OpenCV 🎥, MediaPipe 💡, and PyAutoGUI 🖥️ to track eye movements for hands-free control. It detects facial landmarks, maps eye positions 📌, and enables clicks via blinks 👁️. Ideal for accessibility ♿ with real-time response ⚡. Just install, run, and control your computer with your eyes! 🚀
https://github.com/shib-sankar-das/eye-mouse-controller

ai computer-vision mediapipe opencv pyautogui python

Last synced: 3 months ago
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🖱️👀 Eye-Controlled Mouse uses OpenCV 🎥, MediaPipe 💡, and PyAutoGUI 🖥️ to track eye movements for hands-free control. It detects facial landmarks, maps eye positions 📌, and enables clicks via blinks 👁️. Ideal for accessibility ♿ with real-time response ⚡. Just install, run, and control your computer with your eyes! 🚀

• Host: GitHub
• URL: https://github.com/shib-sankar-das/eye-mouse-controller
• Owner: Shib-Sankar-Das
• License: mit
• Created: 2024-11-12T11:43:44.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-12T11:56:42.000Z (over 1 year ago)
• Last Synced: 2025-03-02T18:27:03.167Z (over 1 year ago)
• Topics: ai, computer-vision, mediapipe, opencv, pyautogui, python
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# 👀 Eye-Mouse-Controller 🖱️ 

Welcome to the **Eye-Controlled Mouse** project! This project leverages computer vision and machine learning to create a hands-free mouse control system powered by eye and facial landmarks. Using your webcam, this system detects and tracks eye movements, translating them into mouse actions such as movement, left-click, and right-click. It's a unique way to control your computer—just with your eyes! 🖱️

---

## 🧠 Project Approach

This project combines several tools to achieve eye-tracking mouse control:

1. **OpenCV**: Captures real-time video from your webcam.

2. **MediaPipe**: Tracks facial landmarks, particularly focusing on eye regions.

3. **PyAutoGUI**: Controls the mouse based on the processed eye movement data.

### Step-by-Step Process:

1. **Face Detection and Landmark Extraction**: Uses MediaPipe's FaceMesh model to identify and refine facial landmarks.

2. **Eye Region Identification**: Tracks specific landmark points around the eyes to detect gaze direction and eye closure.

3. **Mouse Movement**: Maps eye positions to the screen’s coordinates.

4. **Click Detection**: Uses the distance between key eye landmarks to determine blinking, allowing left and right-click actions.

---

## 💡 Key Features

- **Hands-Free Control**: Move the mouse cursor with your eye movements, left-click by blinking, and right-click with a specific eye gesture.

- **Real-Time Processing**: Uses a webcam feed, giving quick and responsive cursor control.

- **Enhanced Accessibility**: Ideal for users with mobility limitations, providing an alternative interaction method with computers.

---

## 🔧 Installation

### Requirements

- **Python 3.7+**

- **OpenCV**

- **MediaPipe**

- **PyAutoGUI**

### Setup

1. Clone the repository:

   ```bash

   git clone https://github.com/Shib-Sankar-Das/Eye-Controlled-Mouse.git

2. Install the required packages:

  ```bash

    pip install opencv-python mediapipe pyautogui

  ```

3. Run the project:

  ```bash

    python EyeMouseController.py