chore: backup before code cleanup

Backup commit before executing remove-unused-code proposal.
This includes all pending changes and new features.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

openspec/changes/archive/2025-12-08-fix-ocr-cell-overdetection/proposal.md

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+# Change: Fix OCR Track Cell Over-Detection
+
+## Why
+
+PP-StructureV3 is over-detecting table cells in OCR Track processing, incorrectly identifying regular text content (key-value pairs, bullet points, form labels) as table cells. This results in:
+- 4 tables detected instead of 1 on sample document
+- 105 cells detected instead of 12 (expected)
+- Broken text layout and incorrect font sizing in PDF output
+- Poor document reconstruction quality compared to Direct Track
+
+Evidence from task comparison:
+- Direct Track (`cfd996d9`): 1 table, 12 cells - correct representation
+- OCR Track (`62de32e0`): 4 tables, 105 cells - severe over-detection
+
+## What Changes
+
+- Add post-detection cell validation pipeline to filter false-positive cells
+- Implement table structure validation using geometric patterns
+- Add text density analysis to distinguish tables from key-value text
+- Apply stricter confidence thresholds for cell detection
+- Add cell clustering algorithm to identify isolated false-positive cells
+
+## Root Cause Analysis
+
+PP-StructureV3's cell detection models over-detect cells in structured text regions. Analysis of page 1:
+
+| Table | Cells | Density (cells/10000px²) | Avg Cell Area | Status |
+|-------|-------|--------------------------|---------------|--------|
+| 1 | 13 | 0.87 | 11,550 px² | Normal |
+| 2 | 12 | 0.44 | 22,754 px² | Normal |
+| **3** | **51** | **6.22** | **1,609 px²** | **Over-detected** |
+| 4 | 29 | 0.94 | 10,629 px² | Normal |
+
+**Table 3 anomalies:**
+- Cell density 7-14x higher than normal tables
+- Average cell area only 7-14% of normal
+- 150px height with 51 cells = ~3px per cell row (impossible)
+
+## Proposed Solution: Post-Detection Cell Validation
+
+Apply metric-based filtering after PP-Structure detection:
+
+### Filter 1: Cell Density Check
+- **Threshold**: Reject tables with density > 3.0 cells/10000px²
+- **Rationale**: Normal tables have 0.4-1.0 density; over-detected have 6+
+
+### Filter 2: Minimum Cell Area
+- **Threshold**: Reject tables with average cell area < 3,000 px²
+- **Rationale**: Normal cells are 10,000-25,000 px²; over-detected are ~1,600 px²
+
+### Filter 3: Cell Height Validation
+- **Threshold**: Reject if (table_height / cell_count) < 10px
+- **Rationale**: Each cell row needs minimum height for readable text
+
+### Filter 4: Reclassification
+- Tables failing validation are reclassified as TEXT elements
+- Original text content is preserved
+- Reading order is recalculated
+
+## Impact
+
+- Affected specs: `ocr-processing`
+- Affected code:
+  - `backend/app/services/ocr_service.py` - Add cell validation pipeline
+  - `backend/app/services/processing_orchestrator.py` - Integrate validation
+  - New file: `backend/app/services/cell_validation_engine.py`
+
+## Success Criteria
+
+1. OCR Track cell count matches Direct Track within 10% tolerance
+2. No false-positive tables detected from non-tabular content
+3. Table structure maintains logical row/column alignment
+4. PDF output quality comparable to Direct Track for documents with tables