c12ea0b9f6
Problem: PP-Structure misses tables with faint lines/borders Solution: Preprocess images (contrast, sharpen) for layout detection - Preprocessed image only used for layout detection - Original image preserved for element extraction (quality) Includes: proposal.md, design.md, tasks.md, spec delta 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
55 lines
2.0 KiB
Markdown
55 lines
2.0 KiB
Markdown
# Tasks: Add Image Preprocessing for Layout Detection
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## 1. Configuration
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- [ ] 1.1 Add preprocessing configuration to `backend/app/core/config.py`
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- `layout_preprocessing_enabled: bool = True` - Enable/disable preprocessing
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- `layout_preprocessing_contrast: str = "clahe"` - Options: none, histogram, clahe
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- `layout_preprocessing_sharpen: bool = True` - Enable sharpening for faint lines
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- `layout_preprocessing_binarize: bool = False` - Optional binarization (aggressive)
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## 2. Preprocessing Service
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- [ ] 2.1 Create `backend/app/services/preprocessing_service.py`
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- Image loading utility (supports PIL, OpenCV)
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- Contrast enhancement methods (histogram equalization, CLAHE)
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- Sharpening filter for line enhancement
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- Optional adaptive binarization
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- Return preprocessed image as numpy array or PIL Image
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- [ ] 2.2 Implement `enhance_for_layout_detection()` function
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- Input: Original image path or PIL Image
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- Output: Preprocessed image (same format as input)
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- Steps: contrast → sharpen → (optional) binarize
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## 3. Integration with OCR Service
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- [ ] 3.1 Update `backend/app/services/ocr_service.py`
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- Import preprocessing service
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- Before `_run_ppstructure()`, preprocess image if enabled
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- Pass preprocessed image to PP-Structure for layout detection
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- Keep original image reference for image extraction
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- [ ] 3.2 Ensure image element extraction uses original
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- Verify `saved_path` and `img_path` in elements reference original
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- Bbox coordinates from preprocessed detection applied to original crop
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## 4. Testing
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- [ ] 4.1 Unit tests for preprocessing_service
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- Test contrast enhancement methods
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- Test sharpening filter
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- Test binarization
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- Test with various image formats (PNG, JPEG)
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- [ ] 4.2 Integration tests
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- Test OCR track with preprocessing enabled/disabled
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- Verify image element quality is preserved
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- Test with known problematic documents (faint table borders)
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## 5. Documentation
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- [ ] 5.1 Update API documentation
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- Document new configuration options
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- Explain preprocessing behavior
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