Implement critical fixes for image and table rendering in PDF generation.
**Image Handling Fixes**:
- Implemented _save_image() in pp_structure_enhanced.py
- Creates imgs/ subdirectory for saved images
- Handles both file paths and numpy arrays
- Returns relative path for reference
- Adds proper error handling and logging
- Added saved_path field to image elements for path tracking
- Created _get_image_path() helper with fallback logic
- Checks saved_path, path, image_path in content
- Falls back to metadata fields
- Logs warnings for missing paths
**Table Rendering Fixes**:
- Fixed table rendering to use element's own bbox directly
- No longer depends on fake table_*.png references
- Supports both bbox and bbox_polygon formats
- Inline conversion for different bbox formats
- Maintains backward compatibility with legacy approach
- Improved error handling for missing bbox data
**Status**:
- Phase 1 tasks 1.1 and 1.2: ✅ Completed
- Phase 1 tasks 2.1, 2.2, and 2.3: ✅ Completed
- Testing pending due to backend availability
These fixes resolve the critical issues where images never appeared
and tables never rendered in generated PDFs.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Problem:
- Backend failed to start with ModuleNotFoundError for torch module
- torch was imported as hard dependency but not in requirements.txt
- Project uses PaddlePaddle which has its own CUDA implementation
Changes:
- Make torch import optional with try/except in ocr_service.py
- Make torch import optional in pp_structure_enhanced.py
- Add cleanup_gpu_memory() method using PaddlePaddle's memory management
- Add check_gpu_memory() method to monitor available GPU memory
- Use paddle.device.cuda.empty_cache() for GPU cleanup
- Use torch.cuda only if TORCH_AVAILABLE flag is True
- Add cleanup calls after OCR processing to prevent OOM errors
- Add memory checks before GPU-intensive operations
Benefits:
- Backend can start without torch installed
- GPU memory is properly managed using PaddlePaddle
- Optional torch support provides additional memory monitoring
- Prevents GPU OOM errors during document processing
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implements the converter that transforms PP-StructureV3 OCR results into
the UnifiedDocument format, enabling consistent output for both OCR and
direct extraction tracks.
- Create OCRToUnifiedConverter class with full element type mapping
- Handle both enhanced (parsing_res_list) and standard markdown results
- Support 4-point and simple bbox formats for coordinates
- Establish element relationships (captions, lists, headers)
- Integrate converter into OCR service dual-track processing
- Update tasks.md marking section 3.3 complete
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
