Tool_OCR

OCR Batch Processing System with Structure Extraction

A web-based solution to extract text, images, and document structure from multiple files efficiently using PaddleOCR-VL.

Features

• 🔍 Multi-Language OCR: Support for 109 languages (Chinese, English, Japanese, Korean, etc.)
• 📄 Document Structure Analysis: Intelligent layout analysis with PP-StructureV3
• 🖼️ Image Extraction: Preserve document images alongside text content
• 📑 Batch Processing: Process multiple files concurrently with progress tracking
• 📤 Multiple Export Formats: TXT, JSON, Excel, Markdown with images, searchable PDF
• 📋 Office Documents: DOC, DOCX, PPT, PPTX support via LibreOffice conversion
• 🚀 GPU Acceleration: Automatic CUDA GPU detection with graceful CPU fallback
• 🔧 Flexible Configuration: Rule-based output formatting
• 🌐 Translation Ready: Reserved architecture for future translation features

Tech Stack

Backend

• Framework: FastAPI 0.115.0
• OCR Engine: PaddleOCR 3.0+ with PaddleOCR-VL and PP-StructureV3
• Deep Learning: PaddlePaddle 3.2.1+ (GPU/CPU support)
• Database: MySQL via SQLAlchemy
• PDF Generation: Pandoc + WeasyPrint
• Image Processing: OpenCV, Pillow, pdf2image
• Office Conversion: LibreOffice (headless mode)

Frontend

• Framework: React 19 with TypeScript
• Build Tool: Vite 7
• Styling: Tailwind CSS v4 + shadcn/ui
• State Management: React Query + Zustand
• HTTP Client: Axios

Prerequisites

• OS: WSL2 Ubuntu 24.04
• Python: 3.12+
• Node.js: 24.x LTS
• MySQL: External database server (provided)
• GPU (Optional): NVIDIA GPU with CUDA 11.8+ for hardware acceleration
  • PaddlePaddle 3.2.1+ requires CUDA 11.8, 12.3, or 12.6+
  • WSL2 users: Ensure NVIDIA CUDA drivers are installed

Quick Start

1. Automated Setup (Recommended)

# Run automated setup script
./setup_dev_env.sh

This script automatically:

• Detects NVIDIA GPU and CUDA version (if available)
• Installs Python development tools (pip, venv, build-essential)
• Installs system dependencies (pandoc, LibreOffice, fonts, etc.)
• Installs Node.js (via nvm)
• Installs PaddlePaddle 3.2.1+ GPU version (if GPU detected) or CPU version
• Configures WSL CUDA library paths (for WSL2 GPU users)
• Installs other Python packages (PaddleOCR, PaddleX, etc.)
• Installs frontend dependencies
• Verifies GPU functionality and chart recognition API availability

2. Initialize Database

source venv/bin/activate
cd backend
alembic upgrade head
python create_test_user.py
cd ..

Default test user:

• Username: admin
• Password: admin123

3. Start Development Servers

Backend (Terminal 1):

./start_backend.sh

Frontend (Terminal 2):

./start_frontend.sh

4. Access Application

• Frontend: http://localhost:5173
• API Docs: http://localhost:8000/docs
• Health Check: http://localhost:8000/health

Project Structure

Tool_OCR/
├── backend/                 # FastAPI backend
│   ├── app/
│   │   ├── api/v1/         # API endpoints
│   │   ├── core/           # Configuration, database
│   │   ├── models/         # Database models
│   │   ├── services/       # Business logic
│   │   └── main.py         # Application entry point
│   ├── alembic/            # Database migrations
│   └── tests/              # Test suite
├── frontend/               # React frontend
│   ├── src/
│   │   ├── components/     # UI components
│   │   ├── pages/          # Page components
│   │   ├── services/       # API services
│   │   └── stores/         # State management
│   └── public/             # Static assets
├── .env.local              # Local development config
├── setup_dev_env.sh        # Environment setup script
├── start_backend.sh        # Backend startup script
└── start_frontend.sh       # Frontend startup script

Configuration

Main config file: .env.local

# Database
MYSQL_HOST=mysql.theaken.com
MYSQL_PORT=33306

# Application ports
BACKEND_PORT=8000
FRONTEND_PORT=5173

# Token expiration (minutes)
ACCESS_TOKEN_EXPIRE_MINUTES=1440  # 24 hours

# Supported file formats
ALLOWED_EXTENSIONS=png,jpg,jpeg,pdf,bmp,tiff,doc,docx,ppt,pptx

# OCR settings
OCR_LANGUAGES=ch,en,japan,korean
MAX_OCR_WORKERS=4

# GPU acceleration (optional)
FORCE_CPU_MODE=false         # Set to true to disable GPU even if available
GPU_MEMORY_FRACTION=0.8      # Fraction of GPU memory to use (0.0-1.0)
GPU_DEVICE_ID=0              # GPU device ID to use (0 for primary GPU)

GPU Acceleration

The system automatically detects and utilizes NVIDIA GPU hardware when available:

• Auto-detection: Setup script detects GPU and installs appropriate PaddlePaddle version
• Graceful fallback: If GPU is unavailable or fails, system automatically uses CPU mode
• Performance: GPU acceleration provides 3-10x speedup for OCR processing
• Configuration: Control GPU usage via .env.local environment variables
• WSL2 CUDA Setup: For WSL2 users, CUDA library paths are automatically configured in ~/.bashrc

Chart Recognition: Requires PaddlePaddle 3.2.0+ for full PP-StructureV3 chart recognition capabilities (chart type detection, data extraction, axis/legend parsing). The setup script installs PaddlePaddle 3.2.1+ which includes all required APIs.

Check GPU status and chart recognition availability at: http://localhost:8000/health

API Endpoints

Authentication

• POST /api/v1/auth/login - User login

File Management

• POST /api/v1/upload - Upload files
• POST /api/v1/ocr/process - Start OCR processing
• GET /api/v1/batch/{id}/status - Get batch status

Results & Export

• GET /api/v1/ocr/result/{id} - Get OCR result
• GET /api/v1/export/pdf/{id} - Export as PDF

Full API documentation: http://localhost:8000/docs

Supported File Formats

• Images: PNG, JPG, JPEG, BMP, TIFF
• Documents: PDF
• Office: DOC, DOCX, PPT, PPTX

Office files are automatically converted to PDF before OCR processing.

Development

Backend

source venv/bin/activate
cd backend

# Run tests
pytest

# Database migration
alembic revision --autogenerate -m "description"
alembic upgrade head

# Code formatting
black app/

Frontend

cd frontend

# Development server
npm run dev

# Build for production
npm run build

# Lint code
npm run lint

OpenSpec Workflow

This project follows OpenSpec for specification-driven development:

# View current changes
openspec list

# Validate specifications
openspec validate add-ocr-batch-processing

# View implementation tasks
cat openspec/changes/add-ocr-batch-processing/tasks.md

Roadmap

• Phase 0: Environment setup
• Phase 1: Core OCR backend (~98% complete)
• Phase 2: Frontend development (~92% complete)
• Phase 3: Testing & optimization
• Phase 4: Deployment automation
• Phase 5: Translation feature (future)

Documentation

• Development specs: openspec/project.md
• Implementation status: openspec/changes/add-ocr-batch-processing/STATUS.md
• Agent instructions: openspec/AGENTS.md

License

Internal project use

Notes

• First OCR run will download PaddleOCR models (~900MB)
• Token expiration is set to 24 hours by default
• Office conversion requires LibreOffice (installed via setup script)
• Development environment: WSL2 Ubuntu 24.04 with Python venv
• GPU acceleration: Automatically detected and enabled if NVIDIA GPU with CUDA 11.8+ is available
• PaddlePaddle version: System uses PaddlePaddle 3.2.1+ which includes full chart recognition support
• WSL GPU support: WSL2 CUDA library paths (/usr/lib/wsl/lib) are automatically configured in ~/.bashrc
• Chart recognition: Fully enabled with PP-StructureV3 for chart type detection, data extraction, and structure analysis
• GPU status and chart recognition availability can be checked via /health API endpoint