VisionAI

AI-Based Eye Disease Detection System

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Overview

VisionAI is a full-stack AI-powered web application designed to assist in the early detection of eye diseases through retina image analysis. The platform combines deep learning, cloud-based data management, and an intuitive user interface to provide users with real-time predictions, eye wellness assessments, and personalized health insights.

The application enables users to securely upload retina scans, receive AI-generated predictions, track their eye wellness, interact with an AI-powered chatbot, and manage their medical reports through a centralized dashboard.

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Features

AI-Based Retina Image Analysis

• Upload retina images for analysis
• Deep learning model for eye disease detection
• Real-time prediction results through REST APIs
• Supports early diagnosis assistance (not a replacement for professional medical advice)

Eye Wellness Assessment

• Interactive lifestyle-based questionnaire
• Personalized eye wellness score
• Health recommendations based on user inputs

AI-Powered Chatbot

• Answers basic eye-health related queries
• Provides preventive eye-care guidance
• Offers general wellness recommendations

Secure User Management

• User registration and authentication
• Secure login using Supabase Authentication
• Personalized dashboard for each user

Cloud Storage

• Secure storage of retina images
• Medical report management
• Cloud-based user data storage using Supabase

Downloadable Reports

• Generate structured medical reports
• Download prediction reports
• Maintain previous analysis history

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🛠️ Tech Stack

Category	Technologies
Frontend	React, TypeScript, Vite
Styling	Tailwind CSS
Backend	FastAPI (Python)
AI/ML	Deep Learning Model
Database & Authentication	Supabase
API Communication	REST APIs

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🚀 Installation

Prerequisites

• Node.js (v18 or later)
• Python 3.9+
• Git
• Supabase Account

Clone the Repository

git clone https://github.com/sharadhiadiga/Vision-AI.git

cd Vision-AI

cd VisionAI-main

Install Frontend Dependencies

npm install

Start the Frontend

npm run dev

Install Backend Dependencies

pip install -r requirements.txt

Run the Backend

uvicorn main:app --reload

Configure Environment Variables

Create a .env file:

VITE_SUPABASE_URL=your_supabase_url
VITE_SUPABASE_ANON_KEY=your_supabase_anon_key
API_BASE_URL=http://localhost:8000

Access the Application

Frontend:

http://localhost:5173

Backend:

http://localhost:8000

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🚀 Future Work

• Support for additional eye diseases
• Explainable AI (Grad-CAM) visualizations
• Real-time camera-based retina analysis
• Doctor dashboard for patient management
• Historical health analytics
• Mobile application support
• Appointment scheduling
• Multi-language chatbot
• Telemedicine integration
• AI-powered disease progression tracking