Commit Graph

5 Commits

Author SHA1 Message Date
黄仁欢 52f283c7c9 feat(seal): add double verification and institution name cleaning
Key improvements:
1. Double verification mechanism for OCR failures
   - When unwarp OCR fails (empty text), automatically try PaddleOCRVL backup on crop
   - Fixes issue where correct seal was ignored due to unwarp image distortion
   - Test result: 4% → 93.8% similarity on problematic PDFs

2. Institution name cleaning
   - Remove unwanted suffixes: 检验检测专用章, 专用章, etc.
   - Clean names before adding to results and similarity calculation
   - Improves matching accuracy

3. Enhanced logging for institution selection
   - Show all extracted institutions with similarity scores
   - Track why specific institution was selected
   - Better debugging and transparency

Example impact:
- Before: "成都虹之川科技有限公司" (wrong seal, 4% similarity)
- After: "中科测试技术(广东)集团有限公司" (correct seal, 93.8% similarity)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-08 13:46:56 +08:00
黄仁欢 5a493b8d67 feat(seal): fix seal text extraction for edge cases
- Add extent limit (max 350°) to prevent polar unwarp distortion
- Add polygon count check (<3 polygons → use PaddleOCRVL backup)
- Add imwrite_safe() to handle Chinese paths on Windows
- Add --pdf-names parameter for targeted debugging

Fixes issue where seal extraction returned empty string when:
- Arc extent exceeded 360° causing severe image distortion
- Too few text polygons detected leading to inaccurate arc calculation

Test results:
- Before: 0% similarity (empty string)
- After: 52.4% similarity (partial extraction)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-07 23:13:03 +08:00
黄仁欢 8b416e9f5a feat: integrate PaddleOCRVL for seal text recognition
- Add PaddleOCRVL as optional OCR model for seal text recognition
  - New parameter: --ocr-model {ppocr_v5,paddleocr_vl}
  - PaddleOCRVL achieves 100% accuracy on test cases (vs 84% for PP-OCRv5)
  - Backward compatible: defaults to PP-OCRv5

- Fix CMA recognition regression
  - Ensure ocr_engine is always initialized for CMA extraction
  - PaddleOCRVL only used for seal text, not CMA recognition

- Add comprehensive integration guide
  - PADDLEOCRVL_INTEGRATION.md with usage examples
  - test_paddleocr_vl_quick.py for validation

Implementation details:
- run_ocr_recognition_vl(): New function for PaddleOCRVL recognition
- extract_seals_and_institutions(): Enhanced with OCR model selection
- Automatic fallback to PP-OCRv5 if PaddleOCRVL unavailable

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-07 14:03:10 +08:00
黄仁欢 2c8ab7379c 暂存 2026-02-05 13:57:22 +08:00
黄仁欢 68b6881c5a feat: implement RBAC with Sa-Token, institution switch, and backend integration tests 2026-01-28 16:15:09 +08:00