技能备份 - 2026-04-15 (40个技能)

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+# API Reference for Super OCR
+
+This document provides complete API documentation for using Super OCR as a Python library.
+
+## Quick Start
+
+```python
+from super_ocr import OCRProcessor
+
+# Auto mode (recommended)
+processor = OCRProcessor(engine='auto')
+result = processor.extract('image.png')
+
+print(result['text'])
+print(f"Confidence: {result['confidence']:.2%}")
+print(f"Engine: {result['engine']}")
+```
+
+## OCRProcessor Class
+
+### `__init__(engine: str = 'auto', verbose: bool = False)`
+
+Initialize the OCR processor.
+
+**Parameters:**
+- `engine` (str): 'auto', 'tesseract', or 'paddle'. Default: 'auto'
+- `verbose` (bool): Enable detailed logging. Default: False
+
+### `extract(image_path: str) -> Dict`
+
+Extract text from a single image.
+
+**Parameters:**
+- `image_path` (str): Path to the input image
+
+**Returns:**
+```python
+{
+    'text': str,                    # Extracted text
+    'confidence': float,           # Confidence score (0.0 - 1.0)
+    'engine': str,                 # 'tesseract' or 'paddle'
+    'processing_time_ms': float,   # Processing time in milliseconds
+    'error': Optional[str],        # Error message if failed
+    'results': List[Dict],         # Detailed results (PaddleOCR only)
+    'line_count': int              # Number of lines detected
+}
+```
+
+### `batch_extract(image_paths: List[str]) -> List[Dict]`
+
+Process multiple images.
+
+**Parameters:**
+- `image_paths` (List[str]): List of image file paths
+
+**Returns:**
+- List of result dictionaries (same structure as `extract()`)
+
+## Engine Selection
+
+### Auto Mode (Default)
+
+The processor automatically selects the best engine based on:
+
+1. **Image filename heuristics:**
+   - `screenshot`, `snap`, `capture` → Tesseract
+   - `menu`, `invoice`, `certificate`, `receipt` → PaddleOCR
+   - Default → PaddleOCR (better accuracy)
+
+2. **Quality fallback:**
+   - If Tesseract returns low confidence, PaddleOCR is used
+
+### Force Mode
+
+You can explicitly choose an engine:
+
+```python
+# Force Tesseract
+processor = OCRProcessor(engine='tesseract')
+
+# Force PaddleOCR
+processor = OCRProcessor(engine='paddle')
+```
+
+## Preprocessing
+
+For advanced users, you can preprocess images before OCR:
+
+```python
+from super_ocr.preprocessing import preprocess_pipeline
+
+# Load image
+import cv2
+image = cv2.imread('input.png')
+
+# Preprocess
+processed = preprocess_pipeline(
+    image,
+    denoise=True,
+    enhance=True,
+    binarize=True,
+    deskew=True,
+    resize_scale=2.0
+)
+
+# Save processed image
+cv2.imwrite('processed.png', processed)
+```
+
+## Output Formats
+
+The skill supports multiple output formats:
+
+| Format | Description |
+|--------|-------------|
+| `text` | Clean extracted text only |
+| `json` | Full JSON with metadata |
+| `structured` | Human-readable formatted output |
+| `verbose` | Debug information with confidence scores |
+
+## Configuration
+
+You can customize behavior by creating a `config.yaml`:
+
+```yaml
+default_engine: auto
+confidence_threshold: 0.8
+output_format: json
+preprocess:
+  denoise: true
+  enhance_contrast: true
+```
+
+## Error Handling
+
+```python
+try:
+    result = processor.extract('image.png')
+    
+    if result.get('error'):
+        print(f"Error: {result['error']}")
+    else:
+        print(result['text'])
+        
+except Exception as e:
+    print(f"Unexpected error: {e}")
+```
+
+## CLI Usage
+
+```bash
+# Single image
+python scripts/main.py --image image.png
+
+# Multiple images
+python scripts/main.py --images ./images/*.png --output ./results
+
+# Force engine
+python scripts/main.py --image doc.png --engine paddle --verbose
+
+# Different output format
+python scripts/main.py --image img.png --format text
+```