EyeKon is an advanced, AI-driven digital eye care system designed to promote healthier screen usage and prevent digital eye strain. By leveraging computer vision and machine learning, EyeKon monitors the user's physical and mental state in real-time, providing actionable feedback and automated workspace adjustments.
It monitors key indicators like fatigue, stress, and focus to ensure a safer, more productive workflow.
- Real-Time Eye & Gaze Tracking: Uses OpenCV and dlib for accurate detection of blinks, gaze direction, and focus duration.
- Fatigue Detection: Calculates a scientifically backed, real-time fatigue score to signal when a rest is needed.
- Stress Analysis: Analyzes micro-expressions to estimate and track user stress levels throughout the workday.
- Screen Automation: Dynamically adjusts screen brightness and color temperature (e.g., activating a blue-light filter) based on lighting and user state.
- Workspace Optimization: Provides contextual, ergonomic suggestions for improved posture and eye-screen distance.
- Proactive Break Reminders: Sends timely audio alerts to ensure the user takes necessary breaks and follows the 20-20-20 rule.
EyeKon is a full-stack application with a modular, event-driven architecture.
| Component | Technology | Role |
|---|---|---|
| Core Logic/Backend | Python (3.x) | Computer Vision, AI models, Data Processing, System Automation. |
| Vision Libraries | OpenCV, dlib, NumPy | Facial and Eye Landmark Detection, Image Processing. |
| Frontend/UI | TypeScript, JavaScript, CSS | User Interface, Configuration, Real-time Dashboard Display. |
| Architecture | Modular & Event-Driven | Ensures high responsiveness and scalability. |
To get EyeKon running locally, follow these steps:
- Python 3.8+
- Node.js & npm (for the frontend)
- Clone the repository:
git clone [https://github.com/Adi030609/EyeKon.git](https://github.com/Adi030609/EyeKon.git) cd EyeKon/backend - Install Python dependencies:
pip install -r requirements.txt # This file should contain: opencv-python, dlib, numpy, etc.
- Navigate to the frontend directory:
cd ../frontend - Install Node dependencies:
npm install
- Start the Backend (Vision/Core):
# From the main 'EyeKon' directory python main/main_script.py - Start the Frontend (Dashboard):
The system will start running and should be accessible via your browser at
# From the 'frontend' directory npm run devhttp://localhost:3000(or similar, depending on your frontend setup).
Customize settings like reminder frequency, sensitivity of fatigue detection, and screen automation limits within the frontend dashboard.
Contributions are welcome! Please follow these steps to contribute:
- Fork the Project.
- Create your Feature Branch (
git checkout -b feature/AmazingFeature). - Commit your Changes (
git commit -m 'Add some AmazingFeature'). - Push to the Branch (
git push origin feature/AmazingFeature). - Open a Pull Request.
Distributed under the MIT License. See LICENSE.txt for more information.
- Adi030609 - GitHub Profile
- Project Link: https://github.com/Adi030609/EyeKon