🏥 Hospital Grade Vision Screening System

A comprehensive eye vision screening system with 8 medical-grade tests, real-time eye tracking, and automatic diagnosis. Built with Python, OpenCV, and Flask for hospitals, clinics, and home use.

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📋 Table of Contents

• Features
• Screenshots
• Quick Start
• Installation
• How to Use
• Test Descriptions
• Results Interpretation
• Sample Output
• Project Structure
• Deployment Options
• Troubleshooting
• Requirements
• Contributing
• License
• Contact

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✨ Features

8 Complete Vision Tests

1. Myopia Test - Near-sightedness detection using Snellen chart letters (E, H, N, O, S...)
2. Hyperopia Test - Far-sightedness detection using reading text passages
3. Astigmatism Test - Line pattern detection (horizontal, vertical, diagonal, grid)
4. Contrast Sensitivity Test - Gray scale pattern recognition
5. Color Vision Test - Ishihara-style colored number plates
6. Visual Field Test - Peripheral vision assessment with position dots
7. Eye Alignment Test - Phoria and binocular vision evaluation
8. Accommodation Test - Focusing ability at different distances

Real-time Analysis

• Live camera feed with face and eye detection
• Eye movement tracking with left/right eye graphs
• Automatic response recording and scoring
• Progress tracking for each test level

Comprehensive Reporting

• Overall vision score calculation
• Test-by-test results grid
• Automatic medical diagnosis
• Personalized recommendations
• Three visual graphs:
  • Eye Tracking Analysis
  • Test Results Bar Chart
  • Vision Health Overview Pie Chart
• Print-ready reports
• CSV and TXT export

User Interface

• Professional hospital-grade design
• Mobile responsive layout
• Real-time pattern display
• One-click test reset
• On-screen results (no download needed)

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📸 Screenshots

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🚀 Quick Start

# Clone the repository
git clone https://github.com/ifrahgul/vision-ai.git

# Navigate to project folder
cd vision-ai

# Create virtual environment
python -m venv venv

# Activate virtual environment (Windows)
venv\Scripts\activate
# Activate virtual environment (Mac/Linux)
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run the application
python app.py

# Open browser and visit
http://localhost:5000