c65df754cf
Add TableData.from_dict() and TableCell.from_dict() methods to convert JSON table dicts to proper TableData objects during UnifiedDocument parsing. Modified _json_to_document_element() to detect TABLE elements with dict content containing 'cells' key and convert to TableData. Note: This fix ensures table elements have proper to_html() method available but the rendered output still needs investigation - tables may still render incorrectly in OCR track PDFs. Files changed: - unified_document.py: Add from_dict() class methods - pdf_generator_service.py: Convert table dicts during JSON parsing - Add fix-ocr-track-table-rendering proposal 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
109 lines
4.3 KiB
Markdown
109 lines
4.3 KiB
Markdown
# Fix OCR Track Table Rendering
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## Summary
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OCR track PDF generation produces tables with incorrect format and layout. Tables appear without proper structure - cell content is misaligned and the visual format differs significantly from the original document. Image placement is correct, but table rendering is broken.
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## Problem Statement
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When generating PDF from OCR track results (via `scan.pdf` processed by PP-StructureV3), the output tables have:
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1. **Wrong cell alignment** - content not positioned in proper cells
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2. **Missing table structure** - rows/columns don't match original document layout
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3. **Incorrect content distribution** - all content seems to flow linearly instead of maintaining grid structure
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Reference: `backend/storage/results/af7c9ee8-60a0-4291-9f22-ef98d27eed52/`
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- Original: `af7c9ee8-60a0-4291-9f22-ef98d27eed52_scan_page_1.png`
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- Generated: `scan_layout.pdf`
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- Result JSON: `scan_result.json` - Tables have correct `{rows, cols, cells}` structure
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## Root Cause Analysis
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### Issue 1: Table Content Not Converted to TableData Object
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In `_json_to_document_element` (pdf_generator_service.py:1952):
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```python
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element = DocumentElement(
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...
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content=elem_dict.get('content', ''), # Raw dict, not TableData
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...
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)
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```
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Table elements have `content` as a dict `{rows: 5, cols: 4, cells: [...]}` but it's not converted to a `TableData` object.
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### Issue 2: OCR Track HTML Conversion Fails
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In `convert_unified_document_to_ocr_data` (pdf_generator_service.py:464-467):
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```python
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elif isinstance(element.content, dict):
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html_content = element.content.get('html', str(element.content))
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```
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Since there's no 'html' key in the cells-based dict, it falls back to `str(element.content)` = `"{'rows': 5, 'cols': 4, ...}"` - invalid HTML.
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### Issue 3: Different Table Rendering Paths
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- **Direct track** uses `_draw_table_element_direct` which properly handles dict with cells via `_build_rows_from_cells_dict`
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- **OCR track** uses `draw_table_region` which expects HTML strings and fails with dict content
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## Proposed Solution
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### Option A: Convert dict to TableData during JSON loading (Recommended)
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In `_json_to_document_element`, when element type is TABLE and content is a dict with cells, convert it to a `TableData` object:
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```python
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# For TABLE elements, convert dict to TableData
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if elem_type == ElementType.TABLE and isinstance(content, dict) and 'cells' in content:
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content = self._dict_to_table_data(content)
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```
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This ensures `element.content.to_html()` works correctly in `convert_unified_document_to_ocr_data`.
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### Option B: Fix conversion in convert_unified_document_to_ocr_data
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Handle dict with cells properly by converting to HTML:
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```python
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elif isinstance(element.content, dict):
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if 'cells' in element.content:
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# Convert cells-based dict to HTML
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html_content = self._cells_dict_to_html(element.content)
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elif 'html' in element.content:
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html_content = element.content['html']
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else:
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html_content = str(element.content)
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```
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## Impact on Hybrid Mode
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Hybrid mode uses Direct track rendering (`_generate_direct_track_pdf`) which already handles dict content properly via `_build_rows_from_cells_dict`. The proposed fixes should not affect hybrid mode negatively.
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However, testing should verify:
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1. Hybrid mode continues to work with combined Direct + OCR elements
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2. Table rendering quality is consistent across all tracks
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## Success Criteria
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1. OCR track tables render with correct structure matching original document
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2. Cell content positioned in proper grid locations
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3. Table borders/grid lines visible
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4. No regression in Direct track or Hybrid mode table rendering
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5. All test files (scan.pdf, img1.png, img2.png, img3.png) produce correct output
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## Files to Modify
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1. `backend/app/services/pdf_generator_service.py`
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- `_json_to_document_element`: Convert table dict to TableData
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- `convert_unified_document_to_ocr_data`: Improve dict handling (if Option B)
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2. `backend/app/models/unified_document.py` (optional)
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- Add `TableData.from_dict()` class method for cleaner conversion
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## Testing Plan
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1. Test scan.pdf with OCR track - verify table structure matches original
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2. Test img1.png, img2.png, img3.png with OCR track
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3. Test PDF files with Direct track - verify no regression
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4. Test Hybrid mode with files that trigger OCR fallback
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