🌾 AgriStack OCR: Digital Land Registry & Dispute Management System

A comprehensive platform for digitizing land records, managing disputed lands, and resolving partition-era ownership issues across India and Pakistan. Built with React, Flask, and powered by Google Vision AI.

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📋 Table of Contents

• Overview
• Key Features
• Tech Stack
• Prerequisites
• Installation Guide
• Configuration
• Running the Application
• Usage Guide
• Project Structure
• Troubleshooting
• Contributing
• License

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🎯 Overview

AgriStack OCR addresses critical challenges in land administration:

• 70%+ of land records exist only in paper format (Urdu, Hindi, Punjabi)
• 1947 Partition disputes: 14.5 million displaced people with unresolved land claims
• Multi-parcel farmers: No centralized system to track ownership across districts
• Language barriers: Documents inaccessible to non-native speakers

What This System Does

1. Digitizes land records using AI-powered OCR (Google Vision API)
2. Translates documents between Urdu, Hindi, Punjabi, and English
3. Manages disputed lands with interactive map visualization
4. Tracks partition-era claims (refugee/muhajireen land disputes)
5. Generates formatted PDFs with AI-powered summaries (Google Gemini)
6. Provides centralized database for farmers with multiple parcels

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✨ Key Features

🔍 Intelligent OCR

• Google Vision API for handwritten & printed text
• Multi-language support: Urdu, Hindi, Punjabi, English
• PDF generation with formatted output
• Batch processing for large-scale digitization

🌐 Multi-Language Translation

• AI4Bharat IndicTrans2 for Indic languages
• Legal terminology preservation
• 4 languages: Urdu ↔ Hindi ↔ Punjabi ↔ English

🗺️ Disputed Lands Management

• Interactive OpenStreetMap visualization
• Partition-era dispute tracking (1947 refugee claims)
• Multi-claimant support with CNIC verification
• Court case management with hearing dates
• Geographic filtering by district/tehsil

🤖 AI-Powered Analysis

• Document summarization (5 types: brief, detailed, key points, legal, action items)
• Q&A functionality using Google Gemini
• Smart data extraction from complex documents

👨‍🌾 Farmer Dashboard

• Centralized view of all land parcels (multi-district)
• Document repository with search & filters
• Real-time processing status
• Mobile-responsive design

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🛠️ Tech Stack

Frontend

• React 18.x - UI framework
• TypeScript - Type safety
• Vite - Build tool
• Tailwind CSS - Styling
• React Leaflet - Map visualization
• Framer Motion - Animations

Backend

• Python 3.11 - Core language
• Flask 3.1.2 - Web framework
• SQLAlchemy 2.0 - Database ORM
• PostgreSQL (via Supabase) - Production database
• SQLite - Development database

AI & APIs

• Google Cloud Vision API - OCR
• Google Gemini AI - Document analysis
• AI4Bharat IndicTrans2 - Translation
• OpenStreetMap - Map tiles

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📦 Prerequisites

Before you begin, ensure you have the following installed on your computer:

Required Software

Software	Version	Download Link	Purpose
Python	3.11 or higher	python.org	Backend runtime
Node.js	18.0 or higher	nodejs.org	Frontend build tool
Git	Latest	git-scm.com	Version control
VS Code	Latest	code.visualstudio.com	Code editor (recommended)

API Keys (Required)

1. Google Vision API Key

   • Go to Google Cloud Console
   • Create a new project or select existing
   • Enable "Cloud Vision API"
   • Create API Key
   • Copy the key (format: AIzaSy...)

2. Google Gemini API Key (for AI features)

   • Go to Google AI Studio
   • Click "Get API Key"
   • Copy the key

3. Supabase Account (optional - for production)

   • Sign up at supabase.com
   • Create a new project
   • Get URL and API key from Project Settings

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🚀 Installation Guide (For Beginners)

Follow these steps exactly as written. Each command is explained.

Step 1: Install Python

1. Download Python 3.11+ from python.org
2. During installation:
   • ✅ Check "Add Python to PATH" (VERY IMPORTANT!)
   • Click "Install Now"
3. Verify installation:

   # Open PowerShell (Windows) or Terminal (Mac/Linux)
   python --version
   # Should show: Python 3.11.x

Step 2: Install Node.js

1. Download Node.js 18+ from nodejs.org
2. Run the installer (just click "Next" through all options)
3. Verify installation:

   node --version
   # Should show: v18.x.x or higher
   
   npm --version
   # Should show: 9.x.x or higher

Step 3: Install Git

1. Download Git from git-scm.com
2. Install with default settings
3. Verify installation:

   git --version
   # Should show: git version 2.x.x

Step 4: Download the Project

1. Open PowerShell/Terminal

2. Navigate to where you want the project (e.g., Desktop):

   # Windows
   cd C:\Users\YourUsername\Desktop
   
   # Mac/Linux
   cd ~/Desktop

3. Clone the repository:

   git clone https://github.com/ronitrai27/OCR_python_Google-Vison.git
   cd OCR_python_Google-Vison

   OR if you downloaded a ZIP file:

   • Extract the ZIP
   • Open PowerShell in that folder
   • Run: cd OCR_python_Google-Vison

Step 5: Setup Backend

1. Navigate to backend folder:

   cd backend

2. Create a virtual environment (isolated Python environment):

   # Windows
   python -m venv venv
   
   # Mac/Linux
   python3 -m venv venv

3. Activate the virtual environment:

   # Windows PowerShell
   .\venv\Scripts\Activate.ps1
   
   # Windows CMD
   venv\Scripts\activate.bat
   
   # Mac/Linux
   source venv/bin/activate

   You should see (venv) at the start of your command line

4. Install Python dependencies:

   pip install -r requirements.txt

   ⏳ This will take 2-5 minutes. You'll see lots of packages being installed.

5. Create .env file:

   # Windows
   copy .env.example .env
   
   # Mac/Linux
   cp .env.example .env

6. Edit the .env file:

   • Open .env in Notepad or VS Code
   • Add your API keys:

   GOOGLE_VISION_API_KEY=AIzaSyXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
   GOOGLE_GEMINI_API_KEY=AIzaSyYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY
   
   # Optional (for production):
   SUPABASE_URL=https://xxxxx.supabase.co
   SUPABASE_KEY=your-key-here
   DATABASE_URL=postgresql://...

   • Save the file

Step 6: Setup Frontend

1. Open a NEW PowerShell/Terminal window (keep backend terminal open)

2. Navigate to frontend folder:

   cd C:\Users\YourUsername\Desktop\OCR_python_Google-Vison\frontend
   # (Adjust path to match your location)

3. Install Node dependencies:

   npm install

   ⏳ This will take 3-7 minutes. Lots of packages will be downloaded.

4. Create frontend .env file:

   # Windows
   copy .env.example .env
   
   # Mac/Linux
   cp .env.example .env

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⚙️ Configuration

Enable Google Vision API

IMPORTANT: Your API key won't work until you enable the service!

1. Go to: https://console.cloud.google.com/apis/library/vision.googleapis.com
2. Select your project from the dropdown (top bar)
3. Click the blue "ENABLE" button
4. Wait 1-2 minutes for activation
5. Enable billing (required, but first 1000 requests/month are FREE)

Generate Sample Data (Optional)

To test the system with realistic data:

# In backend folder (with venv activated)
python generate_disputed_lands_data.py

This creates 50 sample disputed land records with map coordinates.

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▶️ Running the Application

Start Backend Server

1. Open PowerShell in backend folder
2. Activate virtual environment:

   .\venv\Scripts\Activate.ps1

3. Run the server:

   python app.py

4. You should see:

   * Running on http://127.0.0.1:5000
   ✓ Google Vision API Key loaded
   

Keep this terminal window open!

Start Frontend Server

1. Open a NEW PowerShell in frontend folder

2. Run the dev server:

   npm run dev

3. You should see:

   ➜  Local:   http://localhost:5173/
   

4. Open your browser and go to: http://localhost:5173

🎉 The application should now be running!

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📖 Usage Guide

1. OCR Document Processing

1. Click "Dashboard" in the navbar (or login first)
2. Go to "OCR Scanner" tab
3. Upload a document:
   • Drag & drop OR click "Browse Files"
   • Supported: PDF, JPG, PNG
4. Toggle "Use Google Vision API" (recommended for Urdu/Hindi)
5. Click "Process Document"
6. Wait for processing (10-30 seconds)
7. View results:
   • Extracted text
   • Confidence score
   • Detected language
8. Actions:
   • 📄 Generate PDF - Creates formatted document
   • 💾 Save to Database - Permanent storage
   • 🤖 Get AI Summary - Gemini-powered analysis
   • 💬 Ask Question - Q&A about document

2. Translation

1. Go to "Translation" tab
2. Upload document (Urdu, Hindi, Punjabi)
3. Select languages:
   • Source: Urdu (auto-detected)
   • Target: English
4. Click "Translate"
5. View side-by-side comparison
6. Download translated PDF

3. Disputed Lands Management

1. Click "Disputed Lands" in navbar
2. Toggle between:
   • 🗺️ Map View - Interactive OpenStreetMap
   • 📊 List View - Sortable table
3. Filter by:
   • District
   • Tehsil
   • Dispute Type (Refugee, Muhajireen, Overlapping, etc.)
   • Status (Pending, Court Hearing, Resolved)
4. Click on marker/row to view full details:
   • Location (Khasra, Mauza, Tehsil)
   • All claimants with CNIC
   • Historical ownership
   • Court case information
   • Hearing dates

4. Farmer Registration

1. Go to "Farmer Registration"
2. Fill in details:
   • CNIC (National ID)
   • Name, Father's Name
   • Contact (Phone, Address)
   • Land parcels (can add multiple)
3. Submit
4. View registered farmers in dashboard

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📁 Project Structure

OCR_python_Google-Vison/
├── backend/
│   ├── app.py                 # Flask application entry point
│   ├── config.py              # Configuration & environment variables
│   ├── models.py              # Database models (SQLAlchemy)
│   ├── extensions.py          # Flask extensions (CORS, DB)
│   ├── requirements.txt       # Python dependencies
│   ├── .env                   # Environment variables (API keys)
│   │
│   ├── ocr/                   # OCR processing modules
│   │   ├── google_vision_ocr.py    # Google Vision API integration
│   │   ├── lightweight_ocr.py      # Tesseract-based OCR
│   │   ├── image_processing.py     # Image preprocessing
│   │   └── confidence_scorer.py    # Accuracy calculation
│   │
│   ├── translation/           # Translation services
│   │   ├── ai4bharat_translator.py # Indic language translation
│   │   ├── language_detector.py    # Auto-detect language
│   │   └── transliterator.py       # Script conversion
│   │
│   ├── document/              # Document handling
│   │   ├── pdf_generator.py        # PDF creation
│   │   ├── upload_handler.py       # File uploads
│   │   └── rag_document_processor.py # RAG for Q&A
│   │
│   ├── common/                # Shared utilities
│   │   ├── gemini_ai.py            # Google Gemini integration
│   │   ├── text_cleaner.py         # Text normalization
│   │   └── supabase_client.py      # Database client
│   │
│   └── routes/                # API endpoints
│       ├── ocr_routes.py           # OCR endpoints
│       ├── translation_routes.py   # Translation endpoints
│       ├── disputed_lands_routes.py # Disputed lands API
│       ├── rag_routes.py           # RAG/Q&A endpoints
│       └── newsletter_routes.py    # Newsletter subscription
│
├── frontend/
│   ├── src/
│   │   ├── App.tsx            # Main application component
│   │   ├── main.jsx           # Entry point
│   │   │
│   │   ├── pages/             # Page components
│   │   │   ├── LandingPage.tsx
│   │   │   ├── DashboardPage.jsx      # Main dashboard (OCR, Translation)
│   │   │   ├── DisputedLandsPage.jsx  # Disputed lands with map
│   │   │   ├── FarmerRegistrationPage.jsx
│   │   │   ├── LoginPage.jsx
│   │   │   └── SignupPage.jsx
│   │   │
│   │   ├── components/        # Reusable components
│   │   │   ├── Navbar.tsx
│   │   │   ├── Footer.tsx
│   │   │   ├── ImageUpload.jsx
│   │   │   └── GuidedTour.jsx
│   │   │
│   │   └── services/          # API service layer
│   │       └── ocrService.js  # Backend API calls
│   │
│   ├── package.json           # Node dependencies
│   └── vite.config.js         # Vite configuration
│
├── PPT.md                     # Comprehensive project presentation
├── PROJECT_STATUS.md          # Current status & issues
├── OCR_ENHANCEMENT_GUIDE.md   # Implementation guide
└── README.md                  # This file

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🐛 Troubleshooting

Backend Issues

Error: "ModuleNotFoundError: No module named 'flask'"

Solution:

# Make sure virtual environment is activated (you should see (venv))
pip install -r requirements.txt

Error: "Vision API error: Requests to this API are blocked"

Solution:

1. Go to https://console.cloud.google.com/apis/library/vision.googleapis.com
2. Click "ENABLE"
3. Enable billing (first 1000 requests are free)
4. Wait 2 minutes, then try again

Error: "GOOGLE_VISION_API_KEY not found"

Solution:

1. Open backend/.env
2. Add line: GOOGLE_VISION_API_KEY=your-actual-key-here
3. Save file
4. Restart backend server

Error: "Port 5000 already in use"

Solution:

# Windows - Kill process on port 5000
netstat -ano | findstr :5000
taskkill /PID <PID> /F

# Mac/Linux
lsof -ti:5000 | xargs kill -9

Frontend Issues

Error: "npm: command not found"

Solution:

• Reinstall Node.js from nodejs.org
• Make sure to check "Add to PATH" during installation
• Restart PowerShell/Terminal

Error: "Failed to fetch" when uploading documents

Solution:

• Ensure backend is running (check http://127.0.0.1:5000 in browser)
• Check CORS configuration in backend/app.py
• Try restarting both servers

Error: "Module not found" during npm install

Solution:

# Delete node_modules and reinstall
rm -rf node_modules package-lock.json
npm install

Database Issues

Error: "No such table: disputed_land"

Solution:

# Recreate database
cd backend
python
>>> from app import app, db
>>> with app.app_context():
...     db.create_all()
>>> exit()

Generate sample data:

python generate_disputed_lands_data.py

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🤝 Contributing

We welcome contributions! Here's how:

1. Fork the repository
2. Create a feature branch:

   git checkout -b feature/your-feature-name

3. Make your changes
4. Commit with clear messages:

   git commit -m "feat: Add PDF export functionality"

5. Push to your fork:

   git push origin feature/your-feature-name

6. Create a Pull Request on GitHub

Commit Message Convention

• feat: - New feature
• fix: - Bug fix
• docs: - Documentation changes
• style: - Code formatting
• refactor: - Code restructuring
• test: - Adding tests
• chore: - Maintenance tasks

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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📞 Support & Contact

• GitHub Issues: Report bugs or request features
• Email: your-email@example.com
• Documentation: See PPT.md for comprehensive project overview

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🙏 Acknowledgments

• Google Cloud Vision API - OCR engine
• Google Gemini AI - Document analysis
• AI4Bharat - Indic language translation
• OpenStreetMap - Map data
• React Community - UI framework
• Flask Team - Backend framework

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📊 Project Stats

• Lines of Code: ~15,000+
• Languages: Python, TypeScript, JavaScript
• API Endpoints: 25+
• Database Tables: 5
• Supported Languages: 4 (Urdu, Hindi, Punjabi, English)
• Map Markers: Unlimited with clustering

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🗺️ Roadmap

✅ Completed (v1.0)

• OCR processing with Google Vision API
• Multi-language translation
• Disputed lands management with map
• Farmer registration & dashboard
• PDF generation
• AI-powered summarization

🚧 In Progress (v1.1)

• Mobile app (React Native)
• Offline OCR mode
• WhatsApp bot integration

📅 Planned (v2.0)

• Blockchain-based land registry
• Drone boundary mapping
• Carbon credit integration
• Multilingual voice commands

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💡 Quick Tips

1. Always activate the virtual environment before running backend
2. Use Google Vision API for Urdu/Hindi documents (better accuracy)
3. Generate sample data to test disputed lands features
4. Check backend logs if frontend shows errors
5. Keep API keys secret - never commit .env files to Git
6. Use VS Code with Python & ESLint extensions for best experience

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Built with ❤️ for farmers and land administrators across South Asia