feat: enable document orientation detection for scanned PDFs
- Enable PP-StructureV3's use_doc_orientation_classify feature - Detect rotation angle from doc_preprocessor_res.angle - Swap page dimensions (width <-> height) for 90°/270° rotations - Output PDF now correctly displays landscape-scanned content Also includes: - Archive completed openspec proposals - Add simplify-frontend-ocr-config proposal (pending) - Code cleanup and frontend simplification 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# Design: Simple Text Positioning
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## Architecture
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### Current Flow (Complex)
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```
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Raw OCR → PP-Structure Analysis → Table Detection → HTML Parsing →
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Column Correction → Cell Positioning → PDF Generation
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```
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### New Flow (Simple)
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```
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Raw OCR → Text Region Extraction → Bbox Processing →
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Rotation Calculation → Font Size Estimation → PDF Text Rendering
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```
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## Core Components
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### 1. TextRegionRenderer
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New service class to handle raw OCR text rendering:
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```python
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class TextRegionRenderer:
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"""Render raw OCR text regions to PDF."""
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def render_text_region(
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self,
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canvas: Canvas,
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region: Dict,
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scale_factor: float
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) -> None:
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"""
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Render a single OCR text region.
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Args:
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canvas: ReportLab canvas
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region: Raw OCR region with text and bbox
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scale_factor: Coordinate scaling factor
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"""
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```
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### 2. Bbox Processing
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Raw OCR bbox format (quadrilateral - 4 corner points):
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```json
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{
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"text": "LOCTITE",
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"bbox": [[116, 76], [378, 76], [378, 128], [116, 128]],
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"confidence": 0.98
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}
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```
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Processing steps:
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1. **Center point**: Average of 4 corners
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2. **Width/Height**: Distance between corners
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3. **Rotation angle**: Angle of top edge from horizontal
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4. **Font size**: Approximate from bbox height
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### 3. Rotation Calculation
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```python
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def calculate_rotation(bbox: List[List[float]]) -> float:
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"""
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Calculate text rotation from bbox quadrilateral.
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Returns angle in degrees (counter-clockwise from horizontal).
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"""
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# Top-left to top-right vector
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dx = bbox[1][0] - bbox[0][0]
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dy = bbox[1][1] - bbox[0][1]
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# Angle in degrees
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angle = math.atan2(dy, dx) * 180 / math.pi
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return angle
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```
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### 4. Font Size Estimation
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```python
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def estimate_font_size(bbox: List[List[float]], text: str) -> float:
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"""
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Estimate font size from bbox dimensions.
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Uses bbox height as primary indicator, adjusted for aspect ratio.
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"""
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# Calculate bbox height (average of left and right edges)
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left_height = math.dist(bbox[0], bbox[3])
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right_height = math.dist(bbox[1], bbox[2])
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avg_height = (left_height + right_height) / 2
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# Font size is approximately 70-80% of bbox height
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return avg_height * 0.75
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```
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## Integration Points
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### PDFGeneratorService
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Modify `draw_ocr_content()` to use simple text positioning:
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```python
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def draw_ocr_content(self, canvas, content_data, page_info):
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"""Draw OCR content using simple text positioning."""
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# Use raw OCR regions directly
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raw_regions = content_data.get('raw_ocr_regions', [])
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for region in raw_regions:
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self.text_renderer.render_text_region(
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canvas, region, scale_factor
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)
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```
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### Configuration
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Add config option to enable/disable simple mode:
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```python
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class OCRSettings:
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simple_text_positioning: bool = Field(
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default=True,
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description="Use simple text positioning instead of table reconstruction"
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)
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```
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## File Changes
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| File | Change |
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|------|--------|
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| `app/services/text_region_renderer.py` | New - Text rendering logic |
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| `app/services/pdf_generator_service.py` | Modify - Integration |
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| `app/core/config.py` | Add - Configuration option |
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## Edge Cases
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1. **Overlapping text**: Regions may overlap slightly - render in reading order
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2. **Very small text**: Minimum font size threshold (6pt)
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3. **Rotated pages**: Handle 90/180/270 degree page rotation
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4. **Empty regions**: Skip regions with empty text
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5. **Unicode text**: Ensure font supports CJK characters
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# Simple Text Positioning from Raw OCR
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## Summary
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Simplify OCR track PDF generation by rendering raw OCR text at correct positions without complex table structure reconstruction.
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## Problem
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Current OCR track processing has multiple failure points:
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1. PP-Structure table structure recognition fails for borderless tables
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2. Multi-column layouts get merged incorrectly into single tables
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3. Table HTML reconstruction produces wrong cell positions
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4. Complex column correction algorithms still can't fix fundamental structure errors
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Meanwhile, raw OCR (`raw_ocr_regions.json`) correctly identifies all text with accurate bounding boxes.
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## Solution
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Replace complex table reconstruction with simple text positioning:
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1. Read raw OCR regions directly
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2. Position text at bbox coordinates
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3. Calculate text rotation from bbox quadrilateral shape
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4. Estimate font size from bbox height
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5. Skip table HTML parsing entirely for OCR track
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## Benefits
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- **Reliability**: Raw OCR text positions are accurate
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- **Simplicity**: Eliminates complex table parsing logic
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- **Performance**: Faster processing without structure analysis
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- **Consistency**: Predictable output regardless of table type
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## Trade-offs
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- No table borders in output
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- No cell structure (colspan, rowspan)
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- Visual layout approximation rather than semantic structure
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## Scope
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- OCR track PDF generation only
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- Direct track remains unchanged (uses native PDF text extraction)
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# Tasks: Simple Text Positioning
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## Phase 1: Core Implementation
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- [x] Create `TextRegionRenderer` class in `app/services/text_region_renderer.py`
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- [x] Implement `calculate_rotation()` from bbox quadrilateral
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- [x] Implement `estimate_font_size()` from bbox height
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- [x] Implement `render_text_region()` main method
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- [x] Handle coordinate system transformation (OCR → PDF)
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## Phase 2: Integration
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- [x] Add `simple_text_positioning_enabled` config option
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- [x] Modify `PDFGeneratorService._generate_ocr_track_pdf()` to use `TextRegionRenderer`
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- [x] Ensure raw OCR regions are loaded correctly via `load_raw_ocr_regions()`
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## Phase 3: Image/Chart/Formula Support
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- [x] Add image element type detection (`figure`, `image`, `chart`, `seal`, `formula`)
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- [x] Render image elements from UnifiedDocument to PDF
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- [x] Handle image path resolution (result_dir, imgs/ subdirectory)
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- [x] Coordinate transformation for image placement
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## Phase 4: Text Straightening & Overlap Avoidance
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- [x] Add rotation straightening threshold (default 10°)
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- Small rotation angles (< 10°) are treated as 0° for clean output
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- Only significant rotations (e.g., 90°) are preserved
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- [x] Add IoA (Intersection over Area) overlap detection
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- IoA threshold default 0.3 (30% overlap triggers skip)
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- Text regions overlapping with images/charts are skipped
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- [x] Collect exclusion zones from image elements
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- [x] Pass exclusion zones to text renderer
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## Phase 5: Chart Axis Label Deduplication
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- [x] Add `is_axis_label()` method to detect axis labels
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- Y-axis: Vertical text immediately left of chart
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- X-axis: Horizontal text immediately below chart
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- [x] Add `is_near_zone()` method for proximity checking
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- [x] Position-aware deduplication in `render_text_region()`
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- Collect texts inside zones + axis labels
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- Skip matching text only if near zone or is axis label
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- Preserve matching text far from zones (e.g., table values)
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- [x] Test results:
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- "Temperature, C" and "Syringe Thaw Time, Minutes" correctly skipped
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- Table values like "10" at top of page correctly rendered
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- Page 2: 128/148 text regions rendered (12 overlap + 8 dedupe)
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## Phase 6: Testing
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- [x] Test with scan.pdf task (064e2d67-338c-4e54-b005-204c3b76fe63)
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- Page 2: Chart image rendered, axis labels deduplicated
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- PDF is searchable and selectable
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- Text is properly straightened (no skew artifacts)
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- [ ] Compare output quality vs original scan visually
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- [ ] Test with documents containing seals/formulas
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