139 lines
3.6 KiB
Markdown
139 lines
3.6 KiB
Markdown
# 🚀 DeepSeek OCR - React + FastAPI
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Modern OCR web application powered by DeepSeek-OCR with a stunning React frontend and FastAPI backend.
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> **Note**: This was a quickly vibe-coded project to test out DeepSeek-OCR! It basically works quite nice on an RTX 5090. The "Find" mode grounding boxes aren't quite working yet - probably my fault in not interpreting the dimensions correctly, but the core OCR functionality is pretty nice so far.
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## Quick Start
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```bash
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docker compose up --build
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```
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Then open:
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- **Frontend**: http://localhost:3000
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- **Backend API**: http://localhost:8000
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- **API Docs**: http://localhost:8000/docs
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## Features
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### 4 OCR Modes
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- **Plain OCR** - Raw text extraction
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- **Describe** - Generate image descriptions
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- **Find** - Locate specific terms (grounding boxes WIP)
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- **Freeform** - Custom prompts for anything
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### UI Features
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- 🎨 Glass morphism design with animated gradients
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- 🎯 Drag & drop file upload
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- 📦 Grounding box visualization (WIP - dimensions need fixing)
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- ✨ Smooth animations (Framer Motion)
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- 📋 Copy/Download results
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- 🎛️ Advanced settings dropdown
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- 📝 Markdown rendering for formatted output
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## Tech Stack
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- **Frontend**: React 18 + Vite 5 + TailwindCSS 3 + Framer Motion 11
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- **Backend**: FastAPI + PyTorch + Transformers 4.46 + DeepSeek-OCR
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- **Server**: Nginx (reverse proxy)
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- **Container**: Docker + Docker Compose with multi-stage builds
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- **GPU**: NVIDIA CUDA support (tested on RTX 5090)
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## Project Structure
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```
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deepseek-ocr/
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├── backend/ # FastAPI backend
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│ ├── main.py
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│ ├── requirements.txt
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│ └── Dockerfile
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├── frontend/ # React frontend
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│ ├── src/
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│ │ ├── components/
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│ │ ├── App.jsx
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│ │ └── main.jsx
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│ ├── package.json
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│ ├── nginx.conf
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│ └── Dockerfile
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├── models/ # Model cache
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└── docker-compose.yml
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```
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## Development
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### Backend
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```bash
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cd backend
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pip install -r requirements.txt
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uvicorn main:app --reload --host 0.0.0.0 --port 8000
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```
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### Frontend
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```bash
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cd frontend
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npm install
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npm run dev
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```
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## Requirements
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- Docker & Docker Compose
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- NVIDIA GPU with CUDA support (tested on RTX 5090)
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- nvidia-docker runtime
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- ~8-12GB VRAM for model
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## Known Issues
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- 📦 **Find mode grounding boxes**: Not rendering correctly - likely dimension scaling issue in the canvas overlay logic. Boxes are detected and returned by the backend, but the frontend visualization needs work.
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## API Usage
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### POST /api/ocr
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**Parameters:**
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- `image` (file, required)
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- `mode` (string): plain_ocr | describe | find_ref | freeform
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- `prompt` (string): Custom prompt for freeform mode
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- `grounding` (bool): Enable bounding boxes (auto-enabled for find_ref)
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- `find_term` (string): Term to locate in find_ref mode
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- `base_size` (int): Base processing size (default: 1024)
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- `image_size` (int): Image size (default: 640)
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- `crop_mode` (bool): Enable crop mode (default: true)
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**Response:**
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```json
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{
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"success": true,
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"text": "Extracted text...",
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"boxes": [{"label": "field", "box": [x1, y1, x2, y2]}],
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"image_dims": {"w": 1920, "h": 1080},
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"metadata": {...}
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}
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```
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## Troubleshooting
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### GPU not detected
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```bash
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nvidia-smi
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docker run --rm --gpus all nvidia/cuda:11.8.0-base-ubuntu22.04 nvidia-smi
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```
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### Port conflicts
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```bash
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sudo lsof -i :3000
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sudo lsof -i :8000
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```
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### Frontend build issues
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```bash
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cd frontend
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rm -rf node_modules package-lock.json
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docker-compose build frontend
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```
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## License
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This project uses the DeepSeek-OCR model. Refer to the model's license terms.
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