實作 GPU 加速支援,自動偵測並啟用 CUDA GPU 加速 OCR 處理
主要變更:
1. 環境設置增強 (setup_dev_env.sh)
- 新增 GPU 和 CUDA 版本偵測功能
- 自動安裝對應的 PaddlePaddle GPU/CPU 版本
- CUDA 11.2+ 安裝 GPU 版本,否則安裝 CPU 版本
- 安裝後驗證 GPU 可用性並顯示設備資訊
2. 配置更新
- .env.local: 加入 GPU 配置選項
* FORCE_CPU_MODE: 強制 CPU 模式選項
* GPU_MEMORY_FRACTION: GPU 記憶體使用比例
* GPU_DEVICE_ID: GPU 裝置 ID
- backend/app/core/config.py: 加入 GPU 配置欄位
3. OCR 服務 GPU 整合 (backend/app/services/ocr_service.py)
- 新增 _detect_and_configure_gpu() 方法自動偵測 GPU
- 新增 get_gpu_status() 方法回報 GPU 狀態和記憶體使用
- 修改 get_ocr_engine() 支援 GPU 參數和錯誤降級
- 修改 get_structure_engine() 支援 GPU 參數和錯誤降級
- 自動 GPU/CPU 切換,GPU 失敗時自動降級到 CPU
4. 健康檢查與監控 (backend/app/main.py)
- /health endpoint 加入 GPU 狀態資訊
- 回報 GPU 可用性、裝置名稱、記憶體使用等資訊
5. 文檔更新 (README.md)
- Features: 加入 GPU 加速功能說明
- Prerequisites: 加入 GPU 硬體要求(可選)
- Quick Start: 更新自動化設置說明包含 GPU 偵測
- Configuration: 加入 GPU 配置選項和說明
- Notes: 加入 GPU 支援注意事項
技術特性:
- 自動偵測 NVIDIA GPU 和 CUDA 版本
- 支援 CUDA 11.2-12.x
- GPU 初始化失敗時優雅降級到 CPU
- GPU 記憶體分配控制防止 OOM
- 即時 GPU 狀態監控和報告
- 完全向後相容 CPU-only 環境
預期效能:
- GPU 系統: 3-10x OCR 處理速度提升
- CPU 系統: 無影響,維持現有效能
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
262 lines
7.2 KiB
Markdown
262 lines
7.2 KiB
Markdown
# Tool_OCR
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**OCR Batch Processing System with Structure Extraction**
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A web-based solution to extract text, images, and document structure from multiple files efficiently using PaddleOCR-VL.
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## Features
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- 🔍 **Multi-Language OCR**: Support for 109 languages (Chinese, English, Japanese, Korean, etc.)
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- 📄 **Document Structure Analysis**: Intelligent layout analysis with PP-StructureV3
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- 🖼️ **Image Extraction**: Preserve document images alongside text content
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- 📑 **Batch Processing**: Process multiple files concurrently with progress tracking
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- 📤 **Multiple Export Formats**: TXT, JSON, Excel, Markdown with images, searchable PDF
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- 📋 **Office Documents**: DOC, DOCX, PPT, PPTX support via LibreOffice conversion
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- 🚀 **GPU Acceleration**: Automatic CUDA GPU detection with graceful CPU fallback
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- 🔧 **Flexible Configuration**: Rule-based output formatting
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- 🌐 **Translation Ready**: Reserved architecture for future translation features
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## Tech Stack
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### Backend
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- **Framework**: FastAPI 0.115.0
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- **OCR Engine**: PaddleOCR 3.0+ with PaddleOCR-VL
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- **Database**: MySQL via SQLAlchemy
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- **PDF Generation**: Pandoc + WeasyPrint
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- **Image Processing**: OpenCV, Pillow, pdf2image
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- **Office Conversion**: LibreOffice (headless mode)
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### Frontend
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- **Framework**: React 19 with TypeScript
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- **Build Tool**: Vite 7
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- **Styling**: Tailwind CSS v4 + shadcn/ui
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- **State Management**: React Query + Zustand
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- **HTTP Client**: Axios
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## Prerequisites
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- **OS**: WSL2 Ubuntu 24.04
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- **Python**: 3.12+
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- **Node.js**: 24.x LTS
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- **MySQL**: External database server (provided)
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- **GPU** (Optional): NVIDIA GPU with CUDA 11.2+ for hardware acceleration
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## Quick Start
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### 1. Automated Setup (Recommended)
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```bash
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# Run automated setup script
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./setup_dev_env.sh
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```
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This script automatically:
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- Detects NVIDIA GPU and CUDA version (if available)
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- Installs Python development tools (pip, venv, build-essential)
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- Installs system dependencies (pandoc, LibreOffice, fonts, etc.)
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- Installs Node.js (via nvm)
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- Installs PaddlePaddle GPU version (if GPU detected) or CPU version
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- Installs other Python packages
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- Installs frontend dependencies
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- Verifies GPU functionality (if GPU detected)
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### 2. Initialize Database
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```bash
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source venv/bin/activate
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cd backend
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alembic upgrade head
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python create_test_user.py
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cd ..
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```
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Default test user:
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- Username: `admin`
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- Password: `admin123`
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### 3. Start Development Servers
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**Backend (Terminal 1):**
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```bash
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./start_backend.sh
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```
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**Frontend (Terminal 2):**
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```bash
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./start_frontend.sh
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```
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### 4. Access Application
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- **Frontend**: http://localhost:5173
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- **API Docs**: http://localhost:8000/docs
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- **Health Check**: http://localhost:8000/health
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## Project Structure
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```
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Tool_OCR/
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├── backend/ # FastAPI backend
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│ ├── app/
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│ │ ├── api/v1/ # API endpoints
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│ │ ├── core/ # Configuration, database
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│ │ ├── models/ # Database models
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│ │ ├── services/ # Business logic
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│ │ └── main.py # Application entry point
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│ ├── alembic/ # Database migrations
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│ └── tests/ # Test suite
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├── frontend/ # React frontend
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│ ├── src/
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│ │ ├── components/ # UI components
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│ │ ├── pages/ # Page components
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│ │ ├── services/ # API services
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│ │ └── stores/ # State management
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│ └── public/ # Static assets
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├── .env.local # Local development config
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├── setup_dev_env.sh # Environment setup script
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├── start_backend.sh # Backend startup script
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└── start_frontend.sh # Frontend startup script
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```
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## Configuration
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Main config file: `.env.local`
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```bash
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# Database
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MYSQL_HOST=mysql.theaken.com
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MYSQL_PORT=33306
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# Application ports
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BACKEND_PORT=8000
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FRONTEND_PORT=5173
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# Token expiration (minutes)
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ACCESS_TOKEN_EXPIRE_MINUTES=1440 # 24 hours
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# Supported file formats
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ALLOWED_EXTENSIONS=png,jpg,jpeg,pdf,bmp,tiff,doc,docx,ppt,pptx
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# OCR settings
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OCR_LANGUAGES=ch,en,japan,korean
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MAX_OCR_WORKERS=4
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# GPU acceleration (optional)
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FORCE_CPU_MODE=false # Set to true to disable GPU even if available
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GPU_MEMORY_FRACTION=0.8 # Fraction of GPU memory to use (0.0-1.0)
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GPU_DEVICE_ID=0 # GPU device ID to use (0 for primary GPU)
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```
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### GPU Acceleration
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The system automatically detects and utilizes NVIDIA GPU hardware when available:
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- **Auto-detection**: Setup script detects GPU and installs appropriate PaddlePaddle version
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- **Graceful fallback**: If GPU is unavailable or fails, system automatically uses CPU mode
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- **Performance**: GPU acceleration provides 3-10x speedup for OCR processing
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- **Configuration**: Control GPU usage via `.env.local` environment variables
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Check GPU status at: http://localhost:8000/health
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## API Endpoints
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### Authentication
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- `POST /api/v1/auth/login` - User login
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### File Management
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- `POST /api/v1/upload` - Upload files
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- `POST /api/v1/ocr/process` - Start OCR processing
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- `GET /api/v1/batch/{id}/status` - Get batch status
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### Results & Export
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- `GET /api/v1/ocr/result/{id}` - Get OCR result
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- `GET /api/v1/export/pdf/{id}` - Export as PDF
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Full API documentation: http://localhost:8000/docs
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## Supported File Formats
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- **Images**: PNG, JPG, JPEG, BMP, TIFF
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- **Documents**: PDF
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- **Office**: DOC, DOCX, PPT, PPTX
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Office files are automatically converted to PDF before OCR processing.
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## Development
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### Backend
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```bash
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source venv/bin/activate
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cd backend
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# Run tests
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pytest
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# Database migration
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alembic revision --autogenerate -m "description"
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alembic upgrade head
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# Code formatting
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black app/
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```
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### Frontend
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```bash
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cd frontend
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# Development server
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npm run dev
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# Build for production
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npm run build
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# Lint code
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npm run lint
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```
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## OpenSpec Workflow
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This project follows OpenSpec for specification-driven development:
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```bash
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# View current changes
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openspec list
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# Validate specifications
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openspec validate add-ocr-batch-processing
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# View implementation tasks
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cat openspec/changes/add-ocr-batch-processing/tasks.md
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```
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## Roadmap
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- [x] **Phase 0**: Environment setup
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- [x] **Phase 1**: Core OCR backend (~98% complete)
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- [x] **Phase 2**: Frontend development (~92% complete)
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- [ ] **Phase 3**: Testing & optimization
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- [ ] **Phase 4**: Deployment automation
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- [ ] **Phase 5**: Translation feature (future)
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## Documentation
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- Development specs: [openspec/project.md](openspec/project.md)
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- Implementation status: [openspec/changes/add-ocr-batch-processing/STATUS.md](openspec/changes/add-ocr-batch-processing/STATUS.md)
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- Agent instructions: [openspec/AGENTS.md](openspec/AGENTS.md)
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## License
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Internal project use
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## Notes
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- First OCR run will download PaddleOCR models (~900MB)
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- Token expiration is set to 24 hours by default
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- Office conversion requires LibreOffice (installed via setup script)
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- Development environment: WSL2 Ubuntu 24.04 with Python venv
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- **GPU acceleration**: Automatically detected and enabled if NVIDIA GPU with CUDA 11.2+ is available
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- **WSL GPU support**: Ensure NVIDIA CUDA drivers are installed in WSL for GPU acceleration
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- GPU status can be checked via `/health` API endpoint
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