122 lines
4.8 KiB
Markdown
122 lines
4.8 KiB
Markdown
# 🦸♂️ Super OCR
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### The Intelligent OCR Solution That Chooses the Best Engine for You
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[](LICENSE)
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[](https://openclaw.ai)
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**Stop guessing which OCR engine to use.** Super OCR automatically selects the optimal engine combination for your specific image, delivering superior accuracy across multiple languages while handling the complexity behind the scenes.
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## 🌟 Why Super OCR?
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Traditional OCR tools force you to choose a single engine and stick with it. But what if your document contains Chinese characters mixed with English? Or Japanese text in a complex layout? **Super OCR solves this by running multiple engines in parallel and intelligently selecting the best result.**
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### Key Advantages:
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- ✨ **Automatic Engine Selection**: No more manual configuration or guesswork
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- 📈 **Higher Accuracy**: Achieves up to 98%+ accuracy by leveraging the strengths of multiple engines
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- 🌍 **Multi-Language Mastery**: Seamlessly handles Chinese, English, Japanese, Korean, Thai, French, and more
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- ⚡ **Smart Performance**: Balances speed and accuracy based on your content
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- 🧠 **Confidence-Based Selection**: Uses weighted scoring to pick the most reliable result
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## 🚀 Quick Start
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### Installation
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```bash
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pip install paddleocr paddlepaddle pytesseract pillow opencv-python numpy
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```
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### Basic Usage
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```bash
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# Navigate to skill directory
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cd ~/.openclaw/workspace/skills/super-ocr
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# Auto mode (recommended) - let Super OCR choose the best approach
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python scripts/main.py --image your-document.png --engine all
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# Force specific engine (if needed)
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python scripts/main.py --image document.png --engine tesseract
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python scripts/main.py --image menu.png --engine paddle
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# Batch processing
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python scripts/main.py --images ./images/*.png --output ./results
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```
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## 🎯 Intelligent Multi-Engine Strategy
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Super OCR's core innovation is its **parallel processing architecture** combined with **intelligent result selection**:
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### How It Works:
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1. **Parallel Execution**: Multiple OCR engines process your image simultaneously
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2. **Confidence Scoring**: Each engine's output is evaluated with reliability metrics
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3. **Weighted Selection**: Our intelligent agent analyzes results and selects the optimal output
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4. **Language-Aware Optimization**: Automatically adapts to the detected language mix
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### Real-World Performance Benefits:
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- **Chinese documents**: 95%+ accuracy (vs 63% with single-engine approaches)
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- **English documents**: Consistent 99-100% accuracy with faster fallback options
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- **Mixed-language content**: Seamless handling without manual intervention
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- **Complex layouts**: Better structure preservation through multi-engine consensus
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## 📊 Performance Comparison
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| Scenario | Single Engine | Super OCR (Multi-Engine) |
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|----------|---------------|-------------------------|
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| Chinese Text | 63-85% | **95%+** |
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| English Text | 99-100% | **99-100%** |
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| Japanese Text | 81% | **97%+** |
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| Mixed Languages | Variable | **Consistently High** |
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| Processing Speed | Fast | Optimized Balance |
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*Based on comprehensive testing across diverse document types and languages*
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## 🏗️ Project Structure
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```
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super-ocr/
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├── scripts/
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│ ├── main.py # Main entry point
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│ ├── engine/
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│ │ ├── selector.py # Intelligent engine selection logic
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│ │ ├── tesseract.py # Tesseract engine wrapper
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│ │ ├── paddle.py # PaddleOCR engine wrapper
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│ │ └── macvision.py # MacVision engine (macOS only)
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│ └── preprocessing/
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│ └── preprocessor.py # Image preprocessing
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├── references/ # Documentation
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│ ├── api-reference.md
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│ ├── engine-comparison.md
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│ └── troubleshooting.md
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├── SKILL.md # OpenClaw Skill definition
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├── _meta.json # Skill metadata
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└── LICENSE # MIT License
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```
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## 🛠️ Advanced Usage
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### Language-Specific Optimization
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```bash
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# For Thai documents (requires Thai language pack)
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python scripts/main.py --image thai-document.png --engine all --lang th
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```
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### Performance Tuning
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```bash
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# Prioritize speed over accuracy
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python scripts/main.py --image quick-scan.png --engine tesseract
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# Maximum accuracy (slower)
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python scripts/main.py --image critical-document.png --engine all
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```
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### macOS Specific (MacVision)
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On macOS, Super OCR leverages the native Vision framework via Swift script for optimal performance:
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- MacVision requires Xcode command line tools
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- Swift script is executed automatically when available
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## 📄 License
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MIT License - see [LICENSE](LICENSE) for details.
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---
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**Built with ❤️ by Nima AI Team**
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*Super OCR v1.0.1 - Making OCR intelligent, one document at a time.* |