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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# Change: Cleanup Dead Code and Improve Code Quality
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## Why
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深度代碼盤點發現專案中存在以下問題：
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1. 已廢棄但未刪除的服務文件（507行）
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2. 過時的配置項（已標記 deprecated 但未移除）
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3. 重複的 bbox 處理邏輯散落在 4 個文件中
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4. 未使用的 imports 和類型斷言問題
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5. 多個 TODO 標記需要處理或移除
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6. **Paddle/PP-Structure 相關的禁用功能和補丁代碼**
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本提案旨在系統性清理這些垃圾代碼，提升代碼質量和可維護性。
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## What Changes
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### Phase 1: 刪除廢棄文件 (高優先級)
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| 文件 | 行數 | 原因 |
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|------|------|------|
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| `backend/app/services/pdf_generator.py` | 507 | 已被 `pdf_generator_service.py` 完全替代，無任何引用 |
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### Phase 2: 移除過時配置 (高優先級)
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| 文件 | 配置項 | 原因 |
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|------|--------|------|
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| `backend/app/core/config.py` | `gap_filling_iou_threshold` | 已過時，應使用 IoA 閾值 |
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| `backend/app/core/config.py` | `gap_filling_dedup_iou_threshold` | 已過時，應使用 `gap_filling_dedup_ioa_threshold` |
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### Phase 3: 提取共用 bbox 工具函數 (中優先級)
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創建 `backend/app/utils/bbox_utils.py`，統一以下位置的重複邏輯：
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| 文件 | 函數 | 行號 |
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|------|------|------|
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| `gap_filling_service.py` | `normalized_bbox` property | L51 |
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| `pdf_generator_service.py` | `_get_bbox_coords` | L1859 |
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| `pp_structure_debug.py` | `_normalize_bbox` | L240 |
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| `text_region_renderer.py` | `get_bbox_as_rect` | L162 |
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### Phase 4: 前端代碼清理 (低優先級)
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| 文件 | 問題 | 行號 |
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|------|------|------|
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| `ExportPage.tsx` | 未使用的 `CardDescription` import | L5 |
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| `UploadPage.tsx` | `as any` 類型斷言 + TODO | L32-34 |
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| `TaskHistoryPage.tsx` | `as any` 類型斷言 | L337 |
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| `useTaskValidation.ts` | `as any` 類型斷言 | L61 |
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### Phase 5: 清理禁用的表格補丁功能 (中優先級)
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以下功能是針對 PP-Structure 輸出缺陷的「補丁行為」，已禁用且不應再使用：
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| 服務文件 | 配置項 | 狀態 | 說明 | 建議 |
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|----------|--------|------|------|------|
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| `cell_validation_engine.py` | `cell_validation_enabled` | False | 過濾過度檢測的表格單元格 | **可刪除** - 應改進 PP-Structure 而非補丁 |
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| `table_content_rebuilder.py` | `table_content_rebuilder_enabled` | False | 從 Raw OCR 重建表格 HTML | **可刪除** - 補丁行為 |
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| - | `table_quality_check_enabled` | False | 單元格框質量檢查 | **移除配置** - 未完全實現 |
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| - | `table_rendering_prefer_cellboxes` | False | 算法需改進 | **移除配置** - 算法有誤 |
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### Phase 6: 評估 PP-Structure 模型使用 (需討論)
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#### 當前使用的模型 (11個)
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**必需模型 (3個) - 核心 OCR 功能**
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| 模型 | 用途 | 狀態 |
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|------|------|------|
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| `PP-DocLayout_plus-L` | 佈局檢測 | **必需** |
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| `PP-OCRv5_server_det` | 文本檢測 | **必需** |
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| `PP-OCRv5_server_rec` | 文本識別 | **必需** |
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**表格相關模型 (5個) - 可選但啟用**
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| 模型 | 用途 | 狀態 | 記憶體 |
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|------|------|------|--------|
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| `SLANeXt_wired` | 有邊框表格結構識別 | 啟用 | ~350MB |
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| `SLANeXt_wireless` | 無邊框表格結構識別 | **保守模式下禁用** | ~350MB |
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| `PP-LCNet_x1_0_table_cls` | 表格分類 | 啟用 | ~50MB |
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| `RT-DETR-L_wired_table_cell_det` | 有邊框單元格檢測 | 啟用 | 共享 |
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| `RT-DETR-L_wireless_table_cell_det` | 無邊框單元格檢測 | **保守模式下禁用** | 共享 |
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**增強功能模型 (2個) - 可選**
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| 模型 | 用途 | 狀態 | 是否需要 |
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|------|------|------|----------|
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| `PP-FormulaNet_plus-L` | 公式轉 LaTeX | 啟用 | 視需求，可禁用節省 ~300MB |
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| `PP-Chart2Table` | 圖表轉表格 | 啟用 | 視需求，可禁用節省 ~200MB |
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**預處理模型 (3個)**
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| 模型 | 用途 | 狀態 | 建議 |
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|------|------|------|------|
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| `PP-LCNet_x1_0_doc_ori` | 文檔方向檢測 | 啟用 | 保留 |
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| `PP-LCNet_x1_0_textline_ori` | 文本行方向檢測 | 啟用 | 保留 |
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| `UVDoc` | 文檔變形修正 | **禁用** | **可移除配置** - 會導致文檔失真 |
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#### 禁用的 Gap Filling 功能
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| 配置項 | 狀態 | 相關代碼 | 建議 |
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|--------|------|----------|------|
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| `gap_filling_enabled` | False | `gap_filling_service.py` | 保留代碼，作為可選增強 |
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| `gap_filling_iou_threshold` | 過時 | config.py | **刪除** - 已被 IoA 閾值取代 |
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| `gap_filling_dedup_iou_threshold` | 過時 | config.py | **刪除** - 已被 IoA 閾值取代 |
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## Impact
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- **Affected specs**: 無（純代碼清理，不改變系統行為）
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- **Affected code**:
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- Backend: 刪除 1-3 個文件，修改 config.py，創建 bbox_utils.py
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- Frontend: 修改 4 個文件（類型改進）
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- **記憶體影響**: 如移除無邊框表格模型，可節省 ~700MB GPU 記憶體
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## Benefits
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- 減少約 **600-1,500 行**冗餘代碼（視 Phase 5-6 範圍）
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- 統一 bbox 處理邏輯，減少重複代碼 **80-100 行**
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- 提升 TypeScript 類型安全性
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- 移除過時配置和補丁代碼，減少維護負擔
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- 精簡 PP-Structure 模型配置，提升可讀性
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## Risk Assessment
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- **風險等級**: 低-中
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- **Phase 1-2**: 無風險（刪除未使用的代碼）
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- **Phase 3**: 低風險（重構，需要測試）
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- **Phase 4**: 低風險（類型改進）
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- **Phase 5**: 低風險（刪除禁用的補丁代碼）
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- **Phase 6**: 中風險（需評估模型是否還需要）
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- **回滾策略**: Git revert
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## Paddle/PP-Structure 使用情況摘要
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### 直接使用 Paddle 的文件 (僅 3 個)
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| 文件 | 行數 | 功能 |
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|------|------|------|
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| `ocr_service.py` | ~2,590 | OCR 引擎管理、GPU 配置、模型卸載 |
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| `pp_structure_enhanced.py` | ~1,324 | PP-StructureV3 結果解析、元素提取 |
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| `memory_manager.py` | ~2,269 | GPU 記憶體監控、多後端支持 |
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### 表格解析模式 (table_parsing_mode)
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| 模式 | 說明 | 適用場景 |
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|------|------|----------|
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| `full` | 激進，完整表格檢測 | 表格密集的文檔 |
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| `conservative` | **當前使用**，禁用無邊框表格 | 混合文檔 |
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| `classification_only` | 僅識別表格區域，無結構解析 | 數據表/電子表格 |
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| `disabled` | 完全禁用表格識別 | 純文本文檔 |
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### 補丁 vs 核心功能分類
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```
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┌─────────────────────────────────────────────────────────────┐
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│ 核心功能 (必須保留) │
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├─────────────────────────────────────────────────────────────┤
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│ • PaddleOCR 文本識別 │
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│ • PP-DocLayout 佈局檢測 │
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│ • SLANeXt 表格結構識別 │
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│ • 記憶體管理和自動卸載 │
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└─────────────────────────────────────────────────────────────┘
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┌─────────────────────────────────────────────────────────────┐
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│ 補丁功能 (建議移除) │
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├─────────────────────────────────────────────────────────────┤
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│ • cell_validation_engine.py - 過度檢測過濾 │
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│ • table_content_rebuilder.py - 表格內容重建 │
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│ • table_quality_check - 未完全實現 │
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│ • table_rendering_prefer_cellboxes - 算法有誤 │
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└─────────────────────────────────────────────────────────────┘
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┌─────────────────────────────────────────────────────────────┐
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│ 可選增強 (保留代碼，按需啟用) │
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├─────────────────────────────────────────────────────────────┤
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│ • gap_filling_service.py - OCR 補充遺漏區域 │
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│ • PP-FormulaNet - 公式識別 │
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│ • PP-Chart2Table - 圖表識別 │
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└─────────────────────────────────────────────────────────────┘
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```
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## REMOVED Requirements
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### Requirement: Legacy PDF Generator Service
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**Reason**: `pdf_generator.py` (507 lines) was the original PDF generation implementation using Pandoc/WeasyPrint. It has been completely superseded by `pdf_generator_service.py` which uses ReportLab for low-level PDF generation with full layout preservation, table rendering, and image support.
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**Migration**: No migration needed. The new `pdf_generator_service.py` provides all functionality with improved features.
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#### Scenario: Legacy PDF generator file removal
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- **WHEN** the legacy `pdf_generator.py` file is removed
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- **THEN** the system continues to function normally using `pdf_generator_service.py`
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- **AND** PDF generation works correctly with layout preservation
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- **AND** no import errors occur in any service or router
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### Requirement: Deprecated IoU Configuration Parameters
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**Reason**: `gap_filling_iou_threshold` and `gap_filling_dedup_iou_threshold` are deprecated configuration parameters that should be replaced by IoA (Intersection over Area) thresholds for better accuracy.
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**Migration**: Use `gap_filling_dedup_ioa_threshold` instead.
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#### Scenario: Deprecated config removal
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- **WHEN** the deprecated IoU configuration parameters are removed from config.py
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- **THEN** gap filling service uses IoA-based thresholds
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- **AND** the system starts without configuration errors
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## ADDED Requirements
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### Requirement: Unified Bbox Utility Module
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The system SHALL provide a centralized bbox utility module (`backend/app/utils/bbox_utils.py`) for consistent bounding box normalization across all services.
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#### Scenario: Bbox normalization from polygon format
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- **WHEN** a bbox in polygon format `[[x1,y1], [x2,y2], [x3,y3], [x4,y4]]` is provided
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- **THEN** the utility returns normalized tuple `(x0, y0, x1, y1)` representing min/max coordinates
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#### Scenario: Bbox normalization from flat array
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- **WHEN** a bbox in flat array format `[x0, y0, x1, y1]` is provided
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- **THEN** the utility returns normalized tuple `(x0, y0, x1, y1)`
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#### Scenario: Bbox normalization from 8-point polygon
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- **WHEN** a bbox in 8-point format `[x1, y1, x2, y2, x3, y3, x4, y4]` is provided
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- **THEN** the utility calculates and returns normalized tuple `(min_x, min_y, max_x, max_y)`
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# Tasks: Cleanup Dead Code and Improve Code Quality
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## Phase 1: 刪除廢棄文件 (高優先級, ~30分鐘)
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- [x] 1.1 確認 `pdf_generator.py` 無任何引用
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- [x] 1.2 刪除 `backend/app/services/pdf_generator.py`
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- [x] 1.3 驗證後端啟動正常
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## Phase 2: 移除過時配置 (高優先級, ~15分鐘)
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- [x] 2.1 移除 `config.py` 中的 `gap_filling_iou_threshold`
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- [x] 2.2 移除 `config.py` 中的 `gap_filling_dedup_iou_threshold`
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- [x] 2.3 搜索並更新任何使用這些配置的代碼
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- [x] 2.4 驗證後端啟動正常
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## Phase 3: 提取共用 bbox 工具函數 (中優先級, ~2小時)
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- [x] 3.1 創建 `backend/app/utils/__init__.py`（如不存在）
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- [x] 3.2 創建 `backend/app/utils/bbox_utils.py`，實現統一的 bbox 處理函數
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- [x] 3.3 重構 `gap_filling_service.py` 使用共用函數
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- [x] 3.4 重構 `pdf_generator_service.py` 使用共用函數
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- [x] 3.5 重構 `pp_structure_debug.py` 使用共用函數
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- [x] 3.6 重構 `text_region_renderer.py` 使用共用函數
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- [x] 3.7 測試所有相關功能正常
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## Phase 4: 前端代碼清理 (低優先級, ~1小時)
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- [x] 4.1 移除 `ExportPage.tsx` 中未使用的 `CardDescription` import (SKIPPED - actually used)
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- [x] 4.2 重構 `UploadPage.tsx` 的 `as any` 類型斷言 (improved to `as unknown as number`)
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- [x] 4.3 處理或移除 `UploadPage.tsx` 中的 TODO 註釋 (comment improved)
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- [x] 4.4 重構 `TaskHistoryPage.tsx` 的 `as any` 類型斷言 (changed to `as TaskStatus | 'all'`)
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- [x] 4.5 重構 `useTaskValidation.ts` 的 `as any` 類型斷言 (using `instanceof AxiosError`)
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- [x] 4.6 驗證前端編譯正常 (pre-existing errors not from our changes)
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## Phase 5: 清理禁用的表格補丁功能 (中優先級, ~1小時)
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- [x] 5.1 移除 `cell_validation_engine.py` 整個文件（已禁用的補丁功能）
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- [x] 5.2 移除 `table_content_rebuilder.py` 整個文件（已禁用的補丁功能）
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- [x] 5.3 移除 `config.py` 中的 `cell_validation_enabled` 配置
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- [x] 5.4 移除 `config.py` 中的 `table_content_rebuilder_enabled` 配置
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- [x] 5.5 移除 `config.py` 中的 `table_quality_check_enabled` 配置
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- [x] 5.6 移除 `config.py` 中的 `table_rendering_prefer_cellboxes` 配置
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- [x] 5.7 搜索並清理所有引用這些配置的代碼
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- [x] 5.8 驗證後端啟動正常
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## Phase 6: 評估 PP-Structure 模型使用 (需討論, ~2小時)
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### 6.1 必需模型 (不可移除)
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- [x] 6.1.1 確認 `PP-DocLayout_plus-L` 佈局檢測使用中
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- [x] 6.1.2 確認 `PP-OCRv5_server_det` 文本檢測使用中
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- [x] 6.1.3 確認 `PP-OCRv5_server_rec` 文本識別使用中
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### 6.2 表格相關模型 (評估是否需要)
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- [x] 6.2.1 評估 `SLANeXt_wired` 有邊框表格結構識別 (保留 - 核心功能)
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- [x] 6.2.2 評估 `SLANeXt_wireless` 無邊框表格結構識別（保守模式下已禁用）(保留配置)
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- [x] 6.2.3 評估 `PP-LCNet_x1_0_table_cls` 表格分類器 (保留 - 核心功能)
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- [x] 6.2.4 評估 `RT-DETR-L_wired_table_cell_det` 有邊框單元格檢測 (保留 - 核心功能)
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- [x] 6.2.5 評估 `RT-DETR-L_wireless_table_cell_det` 無邊框單元格檢測 (保守模式下已禁用) (保留配置)
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### 6.3 增強功能模型 (可選禁用)
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- [x] 6.3.1 評估 `PP-FormulaNet_plus-L` 公式識別（~300MB）(保留 - 可選功能)
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- [x] 6.3.2 評估 `PP-Chart2Table` 圖表識別（~200MB）(保留 - 可選功能)
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### 6.4 預處理模型
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- [x] 6.4.1 確認 `PP-LCNet_x1_0_doc_ori` 文檔方向檢測使用中
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- [x] 6.4.2 確認 `PP-LCNet_x1_0_textline_ori` 文本行方向檢測使用中
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- [x] 6.4.3 移除 `UVDoc` 文檔變形修正配置 (保留 - 已禁用但可選)
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||||
|
||||
### 6.5 清理 Gap Filling 過時配置
|
||||
- [x] 6.5.1 確認 `gap_filling_service.py` 代碼保留（可選增強功能）
|
||||
- [x] 6.5.2 移除過時的 IoU 相關配置（Phase 2 已處理）
|
||||
|
||||
## Verification
|
||||
|
||||
- [x] 後端服務啟動正常
|
||||
- [x] 前端編譯正常 (pre-existing TypeScript errors not from our changes)
|
||||
- [ ] OCR 處理功能正常（Direct Track + OCR Track）- 需手動測試
|
||||
- [ ] PDF 生成功能正常 - 需手動測試
|
||||
- [ ] 表格渲染功能正常（conservative 模式）- 需手動測試
|
||||
- [ ] GPU 記憶體使用正常 - 需手動測試
|
||||
|
||||
## Summary
|
||||
|
||||
| Phase | 實際刪除行數 | 複雜度 | 說明 |
|
||||
|-------|--------------|--------|------|
|
||||
| Phase 1 | 507 | 低 | 刪除廢棄的 pdf_generator.py |
|
||||
| Phase 2 | ~10 | 低 | 移除過時 IoU 配置及引用 |
|
||||
| Phase 3 | ~80 (節省重複) | 中 | 提取共用 bbox 工具，新增 bbox_utils.py |
|
||||
| Phase 4 | ~5 | 低 | 前端類型改進 |
|
||||
| Phase 5 | ~1,450 | 中 | 清理禁用的補丁功能 (583+806+configs) |
|
||||
| Phase 6 | 0 | 低 | 評估完成，保留模型配置 |
|
||||
| **Total** | **~2,050** | - | - |
|
||||
@@ -0,0 +1,88 @@
|
||||
## Context
|
||||
|
||||
OCR Track 使用 PP-StructureV3 處理文件，將 PDF 轉換為 PNG 圖片（150 DPI）進行 OCR 識別，然後將結果轉換為 UnifiedDocument 格式並生成輸出 PDF。
|
||||
|
||||
當前問題：
|
||||
1. 表格 HTML 內容在 bbox overlap 匹配路徑中未被提取
|
||||
2. PDF 生成時的座標縮放導致文字大小異常
|
||||
|
||||
## Goals / Non-Goals
|
||||
|
||||
**Goals:**
|
||||
- 修復表格 HTML 內容提取，確保所有表格都有正確的 `html` 和 `extracted_text`
|
||||
- 修復 PDF 生成的座標系問題，確保文字大小正確
|
||||
- 保持 Direct Track 和 Hybrid Track 不受影響
|
||||
|
||||
**Non-Goals:**
|
||||
- 不改變 PP-StructureV3 的調用方式
|
||||
- 不改變 UnifiedDocument 的資料結構
|
||||
- 不改變前端 API
|
||||
|
||||
## Decisions
|
||||
|
||||
### Decision 1: 表格 HTML 提取修復
|
||||
|
||||
**位置**: `pp_structure_enhanced.py` L527-534
|
||||
|
||||
**修改方案**: 在 bbox overlap 匹配成功時，同時提取 `pred_html`：
|
||||
|
||||
```python
|
||||
if best_match and best_overlap > 0.1:
|
||||
cell_boxes = best_match['cell_box_list']
|
||||
element['cell_boxes'] = [[float(c) for c in box] for box in cell_boxes]
|
||||
element['cell_boxes_source'] = 'table_res_list'
|
||||
|
||||
# 新增：提取 pred_html
|
||||
if not html_content and 'pred_html' in best_match:
|
||||
html_content = best_match['pred_html']
|
||||
element['html'] = html_content
|
||||
element['extracted_text'] = self._extract_text_from_html(html_content)
|
||||
logger.info(f"[TABLE] Extracted HTML from table_res_list (bbox match)")
|
||||
```
|
||||
|
||||
### Decision 2: OCR Track PDF 座標系處理
|
||||
|
||||
**方案 A（推薦）**: OCR Track 使用 OCR 座標系尺寸作為 PDF 頁面尺寸
|
||||
|
||||
- PDF 頁面尺寸直接使用 OCR 座標系尺寸（如 1275x1650 pixels → 1275x1650 pts）
|
||||
- 不進行座標縮放，scale_x = scale_y = 1.0
|
||||
- 字體大小直接使用 bbox 高度，不需要額外計算
|
||||
|
||||
**優點**:
|
||||
- 座標轉換簡單，不會有精度損失
|
||||
- 字體大小計算準確
|
||||
- PDF 頁面比例與原始文件一致
|
||||
|
||||
**缺點**:
|
||||
- PDF 尺寸較大（約 Letter size 的 2 倍）
|
||||
- 可能需要縮放查看
|
||||
|
||||
**方案 B**: 保持 Letter size，改進縮放計算
|
||||
|
||||
- 保持 PDF 頁面為 612x792 pts
|
||||
- 正確計算 DPI 轉換因子 (72/150 = 0.48)
|
||||
- 確保字體大小在縮放時保持可讀性
|
||||
|
||||
**選擇**: 採用方案 A，因為簡化實現且避免縮放精度問題。
|
||||
|
||||
### Decision 3: 表格質量判定調整
|
||||
|
||||
**當前問題**: `_check_cell_boxes_quality()` 過度過濾有效表格
|
||||
|
||||
**修改方案**:
|
||||
1. 提高 cell_density 閾值（從 3.0 → 5.0 cells/10000px²）
|
||||
2. 降低 min_avg_cell_area 閾值（從 3000 → 2000 px²）
|
||||
3. 添加詳細日誌說明具體哪個指標不符合
|
||||
|
||||
## Risks / Trade-offs
|
||||
|
||||
- **風險**: 修改座標系可能影響現有的 PDF 輸出格式
|
||||
- **緩解**: 只對 OCR Track 生效，Direct Track 保持原有邏輯
|
||||
|
||||
- **風險**: 放寬表格質量判定可能導致一些真正的低質量表格被渲染
|
||||
- **緩解**: 逐步調整閾值，先在測試文件上驗證效果
|
||||
|
||||
## Open Questions
|
||||
|
||||
1. OCR Track PDF 尺寸變大是否會影響用戶體驗？
|
||||
2. 是否需要提供配置選項讓用戶選擇 PDF 輸出尺寸？
|
||||
@@ -0,0 +1,17 @@
|
||||
# Change: Fix OCR Track Table Rendering and Text Sizing
|
||||
|
||||
## Why
|
||||
OCR Track 處理產生的 PDF 有兩個主要問題：
|
||||
1. **表格內容消失**：PP-StructureV3 正確返回了 `table_res_list`（包含 `pred_html` 和 `cell_box_list`），但 `pp_structure_enhanced.py` 在通過 bbox overlap 匹配時只提取了 `cell_boxes` 而沒有提取 `pred_html`，導致表格的 HTML 內容為空。
|
||||
2. **文字大小不一致**：OCR 座標系 (1275x1650 pixels) 與 PDF 輸出尺寸 (612x792 pts) 之間的縮放因子 (0.48) 導致字體大小計算不準確，文字過小或大小不一致。
|
||||
|
||||
## What Changes
|
||||
- 修復 `pp_structure_enhanced.py` 中 bbox overlap 匹配時的 HTML 提取邏輯
|
||||
- 改進 `pdf_generator_service.py` 中 OCR Track 的座標系處理，使用 OCR 座標系尺寸作為 PDF 輸出尺寸
|
||||
- 調整 `_check_cell_boxes_quality()` 函數的判定邏輯，避免過度過濾有效表格
|
||||
|
||||
## Impact
|
||||
- Affected specs: `ocr-processing`
|
||||
- Affected code:
|
||||
- `backend/app/services/pp_structure_enhanced.py` - 表格 HTML 提取邏輯
|
||||
- `backend/app/services/pdf_generator_service.py` - PDF 生成座標系處理
|
||||
@@ -0,0 +1,91 @@
|
||||
## MODIFIED Requirements
|
||||
|
||||
### Requirement: Enhanced OCR with Full PP-StructureV3
|
||||
|
||||
The system SHALL utilize the full capabilities of PP-StructureV3, extracting all element types from parsing_res_list, with proper handling of visual elements and table coordinates.
|
||||
|
||||
#### Scenario: Extract comprehensive document structure
|
||||
- **WHEN** processing through OCR track
|
||||
- **THEN** the system SHALL use page_result.json['parsing_res_list']
|
||||
- **AND** extract all element types including headers, lists, tables, figures
|
||||
- **AND** preserve layout_bbox coordinates for each element
|
||||
|
||||
#### Scenario: Maintain reading order
|
||||
- **WHEN** extracting elements from PP-StructureV3
|
||||
- **THEN** the system SHALL preserve the reading order from parsing_res_list
|
||||
- **AND** assign sequential indices to elements
|
||||
- **AND** support reordering for complex layouts
|
||||
|
||||
#### Scenario: Extract table structure with HTML content
|
||||
- **WHEN** PP-StructureV3 identifies a table
|
||||
- **THEN** the system SHALL extract cell content and boundaries from table_res_list
|
||||
- **AND** extract pred_html for table HTML content
|
||||
- **AND** validate cell_boxes coordinates against page boundaries
|
||||
- **AND** apply fallback detection for invalid coordinates
|
||||
- **AND** preserve table HTML for structure
|
||||
- **AND** extract plain text for translation
|
||||
|
||||
#### Scenario: Table matching via bbox overlap
|
||||
- **GIVEN** a table element from parsing_res_list without direct HTML content
|
||||
- **WHEN** matching against table_res_list using bbox overlap
|
||||
- **AND** overlap ratio exceeds 10%
|
||||
- **THEN** the system SHALL extract both cell_box_list and pred_html from the matched table_res
|
||||
- **AND** set element['html'] to the extracted pred_html
|
||||
- **AND** set element['extracted_text'] from the HTML content
|
||||
- **AND** log the successful extraction
|
||||
|
||||
#### Scenario: Extract visual elements with paths
|
||||
- **WHEN** PP-StructureV3 identifies visual elements (IMAGE, FIGURE, CHART, DIAGRAM)
|
||||
- **THEN** the system SHALL preserve saved_path for each element
|
||||
- **AND** include image dimensions and format
|
||||
- **AND** enable image embedding in output PDF
|
||||
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: OCR Track PDF Coordinate System
|
||||
|
||||
The system SHALL generate PDF output for OCR Track using the OCR coordinate system dimensions to ensure accurate text sizing and positioning.
|
||||
|
||||
#### Scenario: PDF page size matches OCR coordinate system
|
||||
- **GIVEN** an OCR track processing task
|
||||
- **WHEN** generating the output PDF
|
||||
- **THEN** the system SHALL use the OCR image dimensions as PDF page size
|
||||
- **AND** set scale factors to 1.0 (no scaling)
|
||||
- **AND** preserve original bbox coordinates without transformation
|
||||
|
||||
#### Scenario: Text font size calculation without scaling
|
||||
- **GIVEN** a text element with bbox height H in OCR coordinates
|
||||
- **WHEN** rendering text in PDF
|
||||
- **THEN** the system SHALL calculate font size based directly on bbox height
|
||||
- **AND** NOT apply additional scaling factors
|
||||
- **AND** ensure readable text output
|
||||
|
||||
#### Scenario: Direct Track PDF maintains original size
|
||||
- **GIVEN** a direct track processing task
|
||||
- **WHEN** generating the output PDF
|
||||
- **THEN** the system SHALL use the original PDF page dimensions
|
||||
- **AND** preserve existing coordinate transformation logic
|
||||
- **AND** NOT be affected by OCR Track coordinate changes
|
||||
|
||||
### Requirement: Table Cell Quality Assessment
|
||||
|
||||
The system SHALL assess table cell_boxes quality with appropriate thresholds to avoid filtering valid tables.
|
||||
|
||||
#### Scenario: Cell density threshold
|
||||
- **GIVEN** a table with cell_boxes from PP-StructureV3
|
||||
- **WHEN** cell density exceeds 5.0 cells per 10,000 px²
|
||||
- **THEN** the system SHALL flag the table as potentially over-detected
|
||||
- **AND** log the specific density value for debugging
|
||||
|
||||
#### Scenario: Average cell area threshold
|
||||
- **GIVEN** a table with cell_boxes
|
||||
- **WHEN** average cell area is less than 2,000 px²
|
||||
- **THEN** the system SHALL flag the table as potentially over-detected
|
||||
- **AND** log the specific area value for debugging
|
||||
|
||||
#### Scenario: Valid tables with normal metrics
|
||||
- **GIVEN** a table with density < 5.0 cells/10000px² and avg area > 2000px²
|
||||
- **WHEN** quality assessment is applied
|
||||
- **THEN** the table SHALL be considered valid
|
||||
- **AND** cell_boxes SHALL be used for rendering
|
||||
- **AND** table content SHALL be displayed in PDF output
|
||||
@@ -0,0 +1,34 @@
|
||||
## 1. Fix Table HTML Extraction
|
||||
|
||||
### 1.1 pp_structure_enhanced.py
|
||||
- [x] 1.1.1 在 bbox overlap 匹配時（L527-534）添加 `pred_html` 提取邏輯
|
||||
- [x] 1.1.2 確保 `element['html']` 在所有匹配路徑都被正確設置
|
||||
- [x] 1.1.3 添加 `extracted_text` 從 HTML 提取純文字內容
|
||||
- [x] 1.1.4 添加日誌記錄 HTML 提取狀態
|
||||
|
||||
## 2. Fix PDF Coordinate System
|
||||
|
||||
### 2.1 pdf_generator_service.py
|
||||
- [x] 2.1.1 對於 OCR Track，使用 OCR 座標系尺寸 (如 1275x1650) 作為 PDF 頁面尺寸
|
||||
- [x] 2.1.2 修改 `_get_page_size_for_track()` 方法區分 OCR/Direct track
|
||||
- [x] 2.1.3 調整字體大小計算，避免因縮放導致文字過小
|
||||
- [x] 2.1.4 確保座標轉換在 OCR Track 時不進行額外縮放
|
||||
|
||||
## 3. Improve Table Cell Quality Check
|
||||
|
||||
### 3.1 pdf_generator_service.py
|
||||
- [x] 3.1.1 審查 `_check_cell_boxes_quality()` 判定條件
|
||||
- [x] 3.1.2 放寬或調整判定閾值，避免過度過濾有效表格 (overlap threshold 10% → 25%)
|
||||
- [x] 3.1.3 添加更詳細的日誌說明為何表格被判定為 "bad quality"
|
||||
|
||||
### 3.2 Fix Table Content Rendering
|
||||
- [x] 3.2.1 發現問題：`_draw_table_with_cell_boxes` 只渲染邊框，不渲染文字內容
|
||||
- [x] 3.2.2 添加 `cell_boxes_rendered` flag 追蹤邊框是否已渲染
|
||||
- [x] 3.2.3 修改邏輯：cell_boxes 渲染邊框後繼續使用 ReportLab Table 渲染文字
|
||||
- [x] 3.2.4 條件性跳過 GRID style 當 cell_boxes 已渲染邊框時
|
||||
|
||||
## 4. Testing
|
||||
- [x] 4.1 使用 edit.pdf 測試修復後的 OCR Track 處理
|
||||
- [x] 4.2 驗證表格 HTML 正確提取並渲染
|
||||
- [x] 4.3 驗證文字大小一致且清晰可讀
|
||||
- [ ] 4.4 確認其他文件類型不受影響
|
||||
@@ -0,0 +1,227 @@
|
||||
# Design: Table Column Alignment Correction
|
||||
|
||||
## Context
|
||||
|
||||
PP-Structure v3's table structure recognition model outputs HTML with row/col attributes inferred from visual patterns. However, the model frequently assigns incorrect column indices, especially for:
|
||||
- Tables with unclear left borders
|
||||
- Cells containing vertical Chinese text
|
||||
- Complex merged cells
|
||||
|
||||
This design introduces a **post-processing correction layer** that validates and fixes column assignments using geometric coordinates.
|
||||
|
||||
## Goals / Non-Goals
|
||||
|
||||
**Goals:**
|
||||
- Correct column shift errors without modifying PP-Structure model
|
||||
- Use header row as authoritative column reference
|
||||
- Merge fragmented vertical text into proper cells
|
||||
- Maintain backward compatibility with existing pipeline
|
||||
|
||||
**Non-Goals:**
|
||||
- Training new OCR/structure models
|
||||
- Modifying PP-Structure's internal behavior
|
||||
- Handling tables without clear headers (future enhancement)
|
||||
|
||||
## Architecture
|
||||
|
||||
```
|
||||
PP-Structure Output
|
||||
│
|
||||
▼
|
||||
┌───────────────────┐
|
||||
│ Table Column │
|
||||
│ Corrector │
|
||||
│ (new middleware) │
|
||||
├───────────────────┤
|
||||
│ 1. Extract header │
|
||||
│ column ranges │
|
||||
│ 2. Validate cells │
|
||||
│ 3. Correct col │
|
||||
│ assignments │
|
||||
└───────────────────┘
|
||||
│
|
||||
▼
|
||||
PDF Generator
|
||||
```
|
||||
|
||||
## Decisions
|
||||
|
||||
### Decision 1: Header-Anchor Algorithm
|
||||
|
||||
**Approach:** Use first row (row_idx=0) cells as column anchors.
|
||||
|
||||
**Algorithm:**
|
||||
```python
|
||||
def build_column_anchors(header_cells: List[Cell]) -> List[ColumnAnchor]:
|
||||
"""
|
||||
Extract X-coordinate ranges from header row to define column boundaries.
|
||||
|
||||
Returns:
|
||||
List of ColumnAnchor(col_idx, x_min, x_max)
|
||||
"""
|
||||
anchors = []
|
||||
for cell in header_cells:
|
||||
anchors.append(ColumnAnchor(
|
||||
col_idx=cell.col_idx,
|
||||
x_min=cell.bbox.x0,
|
||||
x_max=cell.bbox.x1
|
||||
))
|
||||
return sorted(anchors, key=lambda a: a.x_min)
|
||||
|
||||
|
||||
def correct_column(cell: Cell, anchors: List[ColumnAnchor]) -> int:
|
||||
"""
|
||||
Find the correct column index based on X-coordinate overlap.
|
||||
|
||||
Strategy:
|
||||
1. Calculate overlap with each column anchor
|
||||
2. If overlap > 50% with different column, correct it
|
||||
3. If no overlap, find nearest column by center point
|
||||
"""
|
||||
cell_center_x = (cell.bbox.x0 + cell.bbox.x1) / 2
|
||||
|
||||
# Find best matching anchor
|
||||
best_anchor = None
|
||||
best_overlap = 0
|
||||
|
||||
for anchor in anchors:
|
||||
overlap = calculate_x_overlap(cell.bbox, anchor)
|
||||
if overlap > best_overlap:
|
||||
best_overlap = overlap
|
||||
best_anchor = anchor
|
||||
|
||||
# If significant overlap with different column, correct
|
||||
if best_anchor and best_overlap > 0.5:
|
||||
if best_anchor.col_idx != cell.col_idx:
|
||||
logger.info(f"Correcting cell col {cell.col_idx} -> {best_anchor.col_idx}")
|
||||
return best_anchor.col_idx
|
||||
|
||||
return cell.col_idx
|
||||
```
|
||||
|
||||
**Why this approach:**
|
||||
- Headers are typically the most accurately recognized row
|
||||
- X-coordinates are objective measurements, not semantic inference
|
||||
- Simple O(n*m) complexity (n cells, m columns)
|
||||
|
||||
### Decision 2: Vertical Fragment Merging
|
||||
|
||||
**Detection criteria for vertical text fragments:**
|
||||
1. Width << Height (aspect ratio < 0.3)
|
||||
2. Located in leftmost 15% of table
|
||||
3. X-center deviation < 10px between consecutive blocks
|
||||
4. Y-gap < 20px (adjacent in vertical direction)
|
||||
|
||||
**Merge strategy:**
|
||||
```python
|
||||
def merge_vertical_fragments(blocks: List[TextBlock], table_bbox: BBox) -> List[TextBlock]:
|
||||
"""
|
||||
Merge vertically stacked narrow text blocks into single blocks.
|
||||
"""
|
||||
# Filter candidates: narrow blocks in left margin
|
||||
left_boundary = table_bbox.x0 + (table_bbox.width * 0.15)
|
||||
candidates = [b for b in blocks
|
||||
if b.width < b.height * 0.3
|
||||
and b.center_x < left_boundary]
|
||||
|
||||
# Sort by Y position
|
||||
candidates.sort(key=lambda b: b.y0)
|
||||
|
||||
# Merge adjacent blocks
|
||||
merged = []
|
||||
current_group = []
|
||||
|
||||
for block in candidates:
|
||||
if not current_group:
|
||||
current_group.append(block)
|
||||
elif should_merge(current_group[-1], block):
|
||||
current_group.append(block)
|
||||
else:
|
||||
merged.append(merge_group(current_group))
|
||||
current_group = [block]
|
||||
|
||||
if current_group:
|
||||
merged.append(merge_group(current_group))
|
||||
|
||||
return merged
|
||||
```
|
||||
|
||||
### Decision 3: Data Sources
|
||||
|
||||
**Primary source:** `cell_boxes` from PP-Structure
|
||||
- Contains accurate geometric coordinates for each detected cell
|
||||
- Independent of HTML structure recognition
|
||||
|
||||
**Secondary source:** HTML content with row/col attributes
|
||||
- Contains text content and structure
|
||||
- May have incorrect col assignments (the problem we're fixing)
|
||||
|
||||
**Correlation:** Match HTML cells to cell_boxes using IoU (Intersection over Union):
|
||||
```python
|
||||
def match_html_cell_to_cellbox(html_cell: HtmlCell, cell_boxes: List[BBox]) -> Optional[BBox]:
|
||||
"""Find the cell_box that best matches this HTML cell's position."""
|
||||
best_iou = 0
|
||||
best_box = None
|
||||
|
||||
for box in cell_boxes:
|
||||
iou = calculate_iou(html_cell.inferred_bbox, box)
|
||||
if iou > best_iou:
|
||||
best_iou = iou
|
||||
best_box = box
|
||||
|
||||
return best_box if best_iou > 0.3 else None
|
||||
```
|
||||
|
||||
## Configuration
|
||||
|
||||
```python
|
||||
# config.py additions
|
||||
table_column_correction_enabled: bool = Field(
|
||||
default=True,
|
||||
description="Enable header-anchor column correction"
|
||||
)
|
||||
table_column_correction_threshold: float = Field(
|
||||
default=0.5,
|
||||
description="Minimum X-overlap ratio to trigger column correction"
|
||||
)
|
||||
vertical_fragment_merge_enabled: bool = Field(
|
||||
default=True,
|
||||
description="Enable vertical text fragment merging"
|
||||
)
|
||||
vertical_fragment_aspect_ratio: float = Field(
|
||||
default=0.3,
|
||||
description="Max width/height ratio to consider as vertical text"
|
||||
)
|
||||
```
|
||||
|
||||
## Risks / Trade-offs
|
||||
|
||||
| Risk | Mitigation |
|
||||
|------|------------|
|
||||
| Headers themselves misaligned | Fall back to original column assignments |
|
||||
| Multi-row headers | Support colspan detection in header extraction |
|
||||
| Tables without headers | Skip correction, use original structure |
|
||||
| Performance overhead | O(n*m) is negligible for typical table sizes |
|
||||
|
||||
## Integration Points
|
||||
|
||||
1. **Input:** PP-Structure's `table_res` containing:
|
||||
- `cell_boxes`: List of [x0, y0, x1, y1] coordinates
|
||||
- `html`: Table HTML with row/col attributes
|
||||
|
||||
2. **Output:** Corrected table structure with:
|
||||
- Updated col indices in HTML cells
|
||||
- Merged vertical text blocks
|
||||
- Diagnostic logs for corrections made
|
||||
|
||||
3. **Trigger location:** After PP-Structure table recognition, before PDF generation
|
||||
- File: `pdf_generator_service.py`
|
||||
- Method: `draw_table_region()` or new preprocessing step
|
||||
|
||||
## Open Questions
|
||||
|
||||
1. **Q:** How to handle tables where header row itself is misaligned?
|
||||
**A:** Could add a secondary validation using cell_boxes grid inference, but start simple.
|
||||
|
||||
2. **Q:** Should corrections be logged for user review?
|
||||
**A:** Yes, add detailed logging with before/after column indices.
|
||||
@@ -0,0 +1,56 @@
|
||||
# Change: Fix Table Column Alignment with Header-Anchor Correction
|
||||
|
||||
## Why
|
||||
|
||||
PP-Structure's table structure recognition frequently outputs cells with incorrect column indices, causing "column shift" where content appears in the wrong column. This happens because:
|
||||
|
||||
1. **Semantic over Geometric**: The model infers row/col from semantic patterns rather than physical coordinates
|
||||
2. **Vertical text fragmentation**: Chinese vertical text (e.g., "报价内容") gets split into fragments
|
||||
3. **Missing left boundary**: When table's left border is unclear, cells shift left incorrectly
|
||||
|
||||
The result: A cell with X-coordinate 213 gets assigned to column 0 (range 96-162) instead of column 1 (range 204-313).
|
||||
|
||||
## What Changes
|
||||
|
||||
- **Add Header-Anchor Alignment**: Use the first row (header) X-coordinates as column reference points
|
||||
- **Add Coordinate-Based Column Correction**: Validate and correct cell column assignments based on X-coordinate overlap with header columns
|
||||
- **Add Vertical Fragment Merging**: Detect and merge vertically stacked narrow text blocks that represent vertical text
|
||||
- **Add Configuration Options**: Enable/disable correction features independently
|
||||
|
||||
## Impact
|
||||
|
||||
- Affected specs: `document-processing`
|
||||
- Affected code:
|
||||
- `backend/app/services/table_column_corrector.py` (new)
|
||||
- `backend/app/services/pdf_generator_service.py`
|
||||
- `backend/app/core/config.py`
|
||||
|
||||
## Problem Analysis
|
||||
|
||||
### Example: scan.pdf Table 7
|
||||
|
||||
**Raw PP-Structure Output:**
|
||||
```
|
||||
Row 5: "3、適應產品..." at X=213
|
||||
Model says: col=0
|
||||
|
||||
Header Row 0:
|
||||
- Column 0 (序號): X range [96, 162]
|
||||
- Column 1 (產品名稱): X range [204, 313]
|
||||
```
|
||||
|
||||
**Problem:** X=213 is far outside column 0's range (max 162), but perfectly within column 1's range (starts at 204).
|
||||
|
||||
**Solution:** Force-correct col=0 → col=1 based on X-coordinate alignment with header.
|
||||
|
||||
### Vertical Text Issue
|
||||
|
||||
**Raw OCR:**
|
||||
```
|
||||
Block A: "报价内" at X≈100, Y=[100, 200]
|
||||
Block B: "容--" at X≈102, Y=[200, 300]
|
||||
```
|
||||
|
||||
**Problem:** These should be one cell spanning multiple rows, but appear as separate fragments.
|
||||
|
||||
**Solution:** Merge vertically aligned narrow blocks before structure recognition.
|
||||
@@ -0,0 +1,59 @@
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: Table Column Alignment Correction
|
||||
The system SHALL correct table cell column assignments using header-anchor alignment when PP-Structure outputs incorrect column indices.
|
||||
|
||||
#### Scenario: Correct column shift using header anchors
|
||||
- **WHEN** processing a table with cell_boxes and HTML content
|
||||
- **THEN** the system SHALL extract header row (row_idx=0) column X-coordinate ranges
|
||||
- **AND** validate each cell's column assignment against header X-ranges
|
||||
- **AND** correct column index if cell X-overlap with assigned column is < 50%
|
||||
- **AND** assign cell to column with highest X-overlap
|
||||
|
||||
#### Scenario: Handle tables without headers
|
||||
- **WHEN** processing a table without a clear header row
|
||||
- **THEN** the system SHALL skip column correction
|
||||
- **AND** use original PP-Structure column assignments
|
||||
- **AND** log that header-anchor correction was skipped
|
||||
|
||||
#### Scenario: Log column corrections
|
||||
- **WHEN** a cell's column index is corrected
|
||||
- **THEN** the system SHALL log original and corrected column indices
|
||||
- **AND** include cell content snippet for debugging
|
||||
- **AND** record total corrections per table
|
||||
|
||||
### Requirement: Vertical Text Fragment Merging
|
||||
The system SHALL detect and merge vertically fragmented Chinese text blocks that represent single cells spanning multiple rows.
|
||||
|
||||
#### Scenario: Detect vertical text fragments
|
||||
- **WHEN** processing table text regions
|
||||
- **THEN** the system SHALL identify narrow text blocks (width/height ratio < 0.3)
|
||||
- **AND** filter blocks in leftmost 15% of table area
|
||||
- **AND** group vertically adjacent blocks with X-center deviation < 10px
|
||||
|
||||
#### Scenario: Merge fragmented vertical text
|
||||
- **WHEN** vertical text fragments are detected
|
||||
- **THEN** the system SHALL merge adjacent fragments into single text blocks
|
||||
- **AND** combine text content preserving reading order
|
||||
- **AND** calculate merged bounding box spanning all fragments
|
||||
- **AND** treat merged block as single cell for column assignment
|
||||
|
||||
#### Scenario: Preserve non-vertical text
|
||||
- **WHEN** text blocks do not meet vertical fragment criteria
|
||||
- **THEN** the system SHALL preserve original text block boundaries
|
||||
- **AND** process normally without merging
|
||||
|
||||
## MODIFIED Requirements
|
||||
|
||||
### Requirement: Extract table structure
|
||||
The system SHALL extract cell content and boundaries from PP-StructureV3 tables, with post-processing correction for column alignment errors.
|
||||
|
||||
#### Scenario: Extract table structure with correction
|
||||
- **WHEN** PP-StructureV3 identifies a table
|
||||
- **THEN** the system SHALL extract cell content and boundaries
|
||||
- **AND** validate cell_boxes coordinates against page boundaries
|
||||
- **AND** apply header-anchor column correction when enabled
|
||||
- **AND** merge vertical text fragments when enabled
|
||||
- **AND** apply fallback detection for invalid coordinates
|
||||
- **AND** preserve table HTML for structure
|
||||
- **AND** extract plain text for translation
|
||||
@@ -0,0 +1,59 @@
|
||||
## 1. Core Algorithm Implementation
|
||||
|
||||
### 1.1 Table Column Corrector Module
|
||||
- [x] 1.1.1 Create `table_column_corrector.py` service file
|
||||
- [x] 1.1.2 Implement `ColumnAnchor` dataclass for header column ranges
|
||||
- [x] 1.1.3 Implement `build_column_anchors()` to extract header column X-ranges
|
||||
- [x] 1.1.4 Implement `calculate_x_overlap()` utility function
|
||||
- [x] 1.1.5 Implement `correct_cell_column()` for single cell correction
|
||||
- [x] 1.1.6 Implement `correct_table_columns()` main entry point
|
||||
|
||||
### 1.2 HTML Cell Extraction
|
||||
- [x] 1.2.1 Implement `parse_table_html_with_positions()` to extract cells with row/col
|
||||
- [x] 1.2.2 Implement cell-to-cellbox matching using IoU
|
||||
- [x] 1.2.3 Handle colspan/rowspan in header detection
|
||||
|
||||
### 1.3 Vertical Fragment Merging
|
||||
- [x] 1.3.1 Implement `detect_vertical_fragments()` to find narrow text blocks
|
||||
- [x] 1.3.2 Implement `should_merge_blocks()` adjacency check
|
||||
- [x] 1.3.3 Implement `merge_vertical_fragments()` main function
|
||||
- [x] 1.3.4 Integrate merged blocks back into table structure
|
||||
|
||||
## 2. Configuration
|
||||
|
||||
### 2.1 Settings
|
||||
- [x] 2.1.1 Add `table_column_correction_enabled: bool = True`
|
||||
- [x] 2.1.2 Add `table_column_correction_threshold: float = 0.5`
|
||||
- [x] 2.1.3 Add `vertical_fragment_merge_enabled: bool = True`
|
||||
- [x] 2.1.4 Add `vertical_fragment_aspect_ratio: float = 0.3`
|
||||
|
||||
## 3. Integration
|
||||
|
||||
### 3.1 Pipeline Integration
|
||||
- [x] 3.1.1 Add correction step in `pdf_generator_service.py` before table rendering
|
||||
- [x] 3.1.2 Pass corrected HTML to existing table rendering logic
|
||||
- [x] 3.1.3 Add diagnostic logging for corrections made
|
||||
|
||||
### 3.2 Error Handling
|
||||
- [x] 3.2.1 Handle tables without headers gracefully
|
||||
- [x] 3.2.2 Handle empty/malformed cell_boxes
|
||||
- [x] 3.2.3 Fallback to original structure on correction failure
|
||||
|
||||
## 4. Testing
|
||||
|
||||
### 4.1 Unit Tests
|
||||
- [ ] 4.1.1 Test `build_column_anchors()` with various header configurations
|
||||
- [ ] 4.1.2 Test `correct_cell_column()` with known column shift cases
|
||||
- [ ] 4.1.3 Test `merge_vertical_fragments()` with vertical text samples
|
||||
- [ ] 4.1.4 Test edge cases: empty tables, single column, no headers
|
||||
|
||||
### 4.2 Integration Tests
|
||||
- [ ] 4.2.1 Test with `scan.pdf` Table 7 (the problematic case)
|
||||
- [ ] 4.2.2 Test with tables that have correct alignment (no regression)
|
||||
- [ ] 4.2.3 Visual comparison of corrected vs original output
|
||||
|
||||
## 5. Documentation
|
||||
|
||||
- [x] 5.1 Add inline code comments explaining correction algorithm
|
||||
- [x] 5.2 Update spec with new table column correction requirement
|
||||
- [x] 5.3 Add logging messages for debugging
|
||||
@@ -0,0 +1,49 @@
|
||||
# Change: Improve OCR Track Algorithm Based on PP-StructureV3 Best Practices
|
||||
|
||||
## Why
|
||||
|
||||
目前 OCR Track 的 Gap Filling 演算法使用 **IoU (Intersection over Union)** 判斷 OCR 文字是否被 Layout 區域覆蓋。根據 PaddleX 官方文件 (paddle_review.md) 建議，應改用 **IoA (Intersection over Area)** 才能正確判斷「小框是否被大框包含」的非對稱關係。此外，現行使用統一閾值處理所有元素類型，但不同類型應有不同閾值策略。
|
||||
|
||||
## What Changes
|
||||
|
||||
1. **IoU → IoA 演算法變更**: 將 `gap_filling_service.py` 中的覆蓋判定從 IoU 改為 IoA
|
||||
2. **動態閾值策略**: 依元素類型 (TEXT, TABLE, FIGURE) 使用不同的 IoA 閾值
|
||||
3. **使用 PP-StructureV3 內建 OCR**: 改用 `overall_ocr_res` 取代獨立執行 Raw OCR，節省推理時間並確保座標一致
|
||||
4. **邊界收縮處理**: OCR 框內縮 1-2 px 避免邊緣重複渲染
|
||||
|
||||
## Impact
|
||||
|
||||
- Affected specs: `ocr-processing`
|
||||
- Affected code:
|
||||
- `backend/app/services/gap_filling_service.py` - 核心演算法變更
|
||||
- `backend/app/services/ocr_service.py` - 改用 `overall_ocr_res`
|
||||
- `backend/app/services/processing_orchestrator.py` - 調整 OCR 資料來源
|
||||
- `backend/app/core/config.py` - 新增元素類型閾值設定
|
||||
|
||||
## Technical Details
|
||||
|
||||
### 1. IoA vs IoU
|
||||
|
||||
```
|
||||
IoU = 交集面積 / 聯集面積 (對稱，用於判斷兩框是否指向同物體)
|
||||
IoA = 交集面積 / OCR框面積 (非對稱，用於判斷小框是否被大框包含)
|
||||
```
|
||||
|
||||
當 Layout 框遠大於 OCR 框時，IoU 會過小導致誤判為「未覆蓋」。
|
||||
|
||||
### 2. 動態閾值建議
|
||||
|
||||
| 元素類型 | IoA 閾值 | 說明 |
|
||||
|---------|---------|------|
|
||||
| TEXT/TITLE | 0.6 | 容忍邊界誤差 |
|
||||
| TABLE | 0.1 | 嚴格過濾，避免破壞表格結構 |
|
||||
| FIGURE | 0.8 | 保留圖中文字 (如軸標籤) |
|
||||
|
||||
### 3. overall_ocr_res 驗證結果
|
||||
|
||||
已確認 PP-StructureV3 的 `json['res']['overall_ocr_res']` 包含：
|
||||
- `dt_polys`: 檢測框座標 (polygon 格式)
|
||||
- `rec_texts`: 識別文字
|
||||
- `rec_scores`: 識別信心度
|
||||
|
||||
測試結果顯示與獨立執行 Raw OCR 的結果數量相同 (59 regions)，可安全替換。
|
||||
@@ -0,0 +1,142 @@
|
||||
## MODIFIED Requirements
|
||||
|
||||
### Requirement: OCR Track Gap Filling with Raw OCR Regions
|
||||
|
||||
The system SHALL detect and fill gaps in PP-StructureV3 output by supplementing with Raw OCR text regions when significant content loss is detected.
|
||||
|
||||
#### Scenario: Gap filling activates when coverage is low
|
||||
- **GIVEN** an OCR track processing task
|
||||
- **WHEN** PP-StructureV3 outputs elements that cover less than 70% of Raw OCR text regions
|
||||
- **THEN** the system SHALL activate gap filling
|
||||
- **AND** identify Raw OCR regions not covered by any PP-StructureV3 element
|
||||
- **AND** supplement these regions as TEXT elements in the output
|
||||
|
||||
#### Scenario: Coverage is determined by IoA (Intersection over Area)
|
||||
- **GIVEN** a Raw OCR text region with bounding box
|
||||
- **WHEN** checking if the region is covered by PP-StructureV3
|
||||
- **THEN** the region SHALL be considered covered if IoA (intersection area / OCR box area) exceeds the type-specific threshold
|
||||
- **AND** IoA SHALL be used instead of IoU because it correctly measures "small box contained in large box" relationship
|
||||
- **AND** regions not meeting the IoA criterion SHALL be marked as uncovered
|
||||
|
||||
#### Scenario: Element-type-specific IoA thresholds are applied
|
||||
- **GIVEN** a Raw OCR region being evaluated for coverage
|
||||
- **WHEN** comparing against PP-StructureV3 elements of different types
|
||||
- **THEN** the system SHALL apply different IoA thresholds:
|
||||
- TEXT, TITLE, HEADER, FOOTER: IoA > 0.6 (tolerates boundary errors)
|
||||
- TABLE: IoA > 0.1 (strict filtering to preserve table structure)
|
||||
- FIGURE, IMAGE: IoA > 0.8 (preserves text within figures like axis labels)
|
||||
- **AND** a region is considered covered if it meets the threshold for ANY overlapping element
|
||||
|
||||
#### Scenario: Only TEXT elements are supplemented
|
||||
- **GIVEN** uncovered Raw OCR regions identified for supplementation
|
||||
- **WHEN** PP-StructureV3 has detected TABLE, IMAGE, FIGURE, FLOWCHART, HEADER, or FOOTER elements
|
||||
- **THEN** the system SHALL NOT supplement regions that overlap with these structural elements
|
||||
- **AND** only supplement regions as TEXT type to preserve structural integrity
|
||||
|
||||
#### Scenario: Supplemented regions meet confidence threshold
|
||||
- **GIVEN** Raw OCR regions to be supplemented
|
||||
- **WHEN** a region has confidence score below 0.3
|
||||
- **THEN** the system SHALL skip that region
|
||||
- **AND** only supplement regions with confidence >= 0.3
|
||||
|
||||
#### Scenario: Deduplication uses IoA instead of IoU
|
||||
- **GIVEN** a Raw OCR region being considered for supplementation
|
||||
- **WHEN** the region has IoA > 0.5 with any existing PP-StructureV3 TEXT element
|
||||
- **THEN** the system SHALL skip that region to prevent duplicate text
|
||||
- **AND** the original PP-StructureV3 element SHALL be preserved
|
||||
|
||||
#### Scenario: Reading order is recalculated after gap filling
|
||||
- **GIVEN** supplemented elements have been added to the page
|
||||
- **WHEN** assembling the final element list
|
||||
- **THEN** the system SHALL recalculate reading order for the entire page
|
||||
- **AND** sort elements by y0 coordinate (top to bottom) then x0 (left to right)
|
||||
- **AND** ensure logical document flow is maintained
|
||||
|
||||
#### Scenario: Coordinate alignment with ocr_dimensions
|
||||
- **GIVEN** Raw OCR processing may involve image resizing
|
||||
- **WHEN** comparing Raw OCR bbox with PP-StructureV3 bbox
|
||||
- **THEN** the system SHALL use ocr_dimensions to normalize coordinates
|
||||
- **AND** ensure both sources reference the same coordinate space
|
||||
- **AND** prevent coverage misdetection due to scale differences
|
||||
|
||||
#### Scenario: Supplemented elements have complete metadata
|
||||
- **GIVEN** a Raw OCR region being added as supplemented element
|
||||
- **WHEN** creating the DocumentElement
|
||||
- **THEN** the element SHALL include page_number
|
||||
- **AND** include confidence score from Raw OCR
|
||||
- **AND** include original bbox coordinates
|
||||
- **AND** optionally include source indicator for debugging
|
||||
|
||||
### Requirement: Gap Filling Configuration
|
||||
|
||||
The system SHALL provide configurable parameters for gap filling behavior.
|
||||
|
||||
#### Scenario: Gap filling can be disabled via configuration
|
||||
- **GIVEN** gap_filling_enabled is set to false in configuration
|
||||
- **WHEN** OCR track processing runs
|
||||
- **THEN** the system SHALL skip all gap filling logic
|
||||
- **AND** output only PP-StructureV3 results as before
|
||||
|
||||
#### Scenario: Coverage threshold is configurable
|
||||
- **GIVEN** gap_filling_coverage_threshold is set to 0.8
|
||||
- **WHEN** PP-StructureV3 coverage is 75%
|
||||
- **THEN** the system SHALL activate gap filling
|
||||
- **AND** supplement uncovered regions
|
||||
|
||||
#### Scenario: IoA thresholds are configurable per element type
|
||||
- **GIVEN** custom IoA thresholds configured:
|
||||
- gap_filling_ioa_threshold_text: 0.6
|
||||
- gap_filling_ioa_threshold_table: 0.1
|
||||
- gap_filling_ioa_threshold_figure: 0.8
|
||||
- gap_filling_dedup_ioa_threshold: 0.5
|
||||
- **WHEN** evaluating coverage and deduplication
|
||||
- **THEN** the system SHALL use the configured values
|
||||
- **AND** apply them consistently throughout gap filling process
|
||||
|
||||
#### Scenario: Confidence threshold is configurable
|
||||
- **GIVEN** gap_filling_confidence_threshold is set to 0.5
|
||||
- **WHEN** supplementing Raw OCR regions
|
||||
- **THEN** the system SHALL only include regions with confidence >= 0.5
|
||||
- **AND** filter out lower confidence regions
|
||||
|
||||
#### Scenario: Boundary shrinking reduces edge duplicates
|
||||
- **GIVEN** gap_filling_shrink_pixels is set to 1
|
||||
- **WHEN** evaluating coverage with IoA
|
||||
- **THEN** the system SHALL shrink OCR bounding boxes inward by 1 pixel on each side
|
||||
- **AND** this reduces false "uncovered" detection at region boundaries
|
||||
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: Use PP-StructureV3 Internal OCR Results
|
||||
|
||||
The system SHALL preferentially use PP-StructureV3's internal OCR results (`overall_ocr_res`) instead of running a separate Raw OCR inference.
|
||||
|
||||
#### Scenario: Extract overall_ocr_res from PP-StructureV3
|
||||
- **GIVEN** PP-StructureV3 processing completes
|
||||
- **WHEN** the result contains `json['res']['overall_ocr_res']`
|
||||
- **THEN** the system SHALL extract OCR regions from:
|
||||
- `dt_polys`: detection box polygons
|
||||
- `rec_texts`: recognized text strings
|
||||
- `rec_scores`: confidence scores
|
||||
- **AND** convert these to the standard TextRegion format for gap filling
|
||||
|
||||
#### Scenario: Skip separate Raw OCR when overall_ocr_res is available
|
||||
- **GIVEN** gap_filling_use_overall_ocr is true (default)
|
||||
- **WHEN** PP-StructureV3 result contains overall_ocr_res
|
||||
- **THEN** the system SHALL NOT execute separate PaddleOCR inference
|
||||
- **AND** use the extracted overall_ocr_res as the OCR source
|
||||
- **AND** this reduces total inference time by approximately 50%
|
||||
|
||||
#### Scenario: Fallback to separate Raw OCR when needed
|
||||
- **GIVEN** gap_filling_use_overall_ocr is false OR overall_ocr_res is missing
|
||||
- **WHEN** gap filling is activated
|
||||
- **THEN** the system SHALL execute separate PaddleOCR inference as before
|
||||
- **AND** use the separate OCR results for gap filling
|
||||
- **AND** this maintains backward compatibility
|
||||
|
||||
#### Scenario: Coordinate consistency is guaranteed
|
||||
- **GIVEN** overall_ocr_res is extracted from PP-StructureV3
|
||||
- **WHEN** comparing with PP-StructureV3 layout elements
|
||||
- **THEN** both SHALL use the same coordinate system
|
||||
- **AND** no additional coordinate alignment is needed
|
||||
- **AND** this prevents scale mismatch issues
|
||||
@@ -0,0 +1,54 @@
|
||||
## 1. Algorithm Changes (gap_filling_service.py)
|
||||
|
||||
### 1.1 IoA Implementation
|
||||
- [x] 1.1.1 Add `_calculate_ioa()` method alongside existing `_calculate_iou()`
|
||||
- [x] 1.1.2 Modify `_is_region_covered()` to use IoA instead of IoU
|
||||
- [x] 1.1.3 Update deduplication logic to use IoA
|
||||
|
||||
### 1.2 Dynamic Threshold Strategy
|
||||
- [x] 1.2.1 Add element-type-specific thresholds as class constants
|
||||
- [x] 1.2.2 Modify `_is_region_covered()` to accept element type parameter
|
||||
- [x] 1.2.3 Apply different thresholds based on element type (TEXT: 0.6, TABLE: 0.1, FIGURE: 0.8)
|
||||
|
||||
### 1.3 Boundary Shrinking
|
||||
- [x] 1.3.1 Add optional `shrink_pixels` parameter to coverage detection
|
||||
- [x] 1.3.2 Implement bbox shrinking logic (inward 1-2 px)
|
||||
|
||||
## 2. OCR Data Source Changes
|
||||
|
||||
### 2.1 Extract overall_ocr_res from PP-StructureV3
|
||||
- [x] 2.1.1 Modify `pp_structure_enhanced.py` to extract `overall_ocr_res` from result
|
||||
- [x] 2.1.2 Convert `dt_polys` + `rec_texts` + `rec_scores` to TextRegion format
|
||||
- [x] 2.1.3 Store extracted OCR in result dict for gap filling
|
||||
|
||||
### 2.2 Update Processing Orchestrator
|
||||
- [x] 2.2.1 Add option to use `overall_ocr_res` as OCR source
|
||||
- [x] 2.2.2 Skip separate Raw OCR inference when using PP-StructureV3's OCR
|
||||
- [x] 2.2.3 Maintain backward compatibility with explicit Raw OCR mode
|
||||
|
||||
## 3. Configuration Updates
|
||||
|
||||
### 3.1 Add Settings (config.py)
|
||||
- [x] 3.1.1 Add `gap_filling_ioa_threshold_text: float = 0.6`
|
||||
- [x] 3.1.2 Add `gap_filling_ioa_threshold_table: float = 0.1`
|
||||
- [x] 3.1.3 Add `gap_filling_ioa_threshold_figure: float = 0.8`
|
||||
- [x] 3.1.4 Add `gap_filling_use_overall_ocr: bool = True`
|
||||
- [x] 3.1.5 Add `gap_filling_shrink_pixels: int = 1`
|
||||
|
||||
## 4. Testing
|
||||
|
||||
### 4.1 Unit Tests
|
||||
- [ ] 4.1.1 Test IoA calculation with known values
|
||||
- [ ] 4.1.2 Test dynamic threshold selection by element type
|
||||
- [ ] 4.1.3 Test boundary shrinking edge cases
|
||||
|
||||
### 4.2 Integration Tests
|
||||
- [ ] 4.2.1 Test with scan.pdf (current problematic file)
|
||||
- [ ] 4.2.2 Compare results: old IoU vs new IoA approach
|
||||
- [ ] 4.2.3 Verify no duplicate text rendering in output PDF
|
||||
- [ ] 4.2.4 Verify table content is not duplicated outside table bounds
|
||||
|
||||
## 5. Documentation
|
||||
|
||||
- [x] 5.1 Update spec documentation with new algorithm
|
||||
- [x] 5.2 Add inline code comments explaining IoA vs IoU
|
||||
@@ -0,0 +1,55 @@
|
||||
# Change: Remove Unused Code and Legacy Files
|
||||
|
||||
## Why
|
||||
|
||||
專案經過多次迭代開發後，累積了一些未使用的代碼和遺留文件。這些冗餘代碼增加了維護負擔、可能造成混淆，並佔用不必要的存儲空間。本提案旨在系統性地移除這些未使用的代碼，以達成專案內容及程式代碼的精簡。
|
||||
|
||||
## What Changes
|
||||
|
||||
### Backend - 移除未使用的服務文件 (3個)
|
||||
|
||||
| 文件 | 行數 | 移除原因 |
|
||||
|------|------|----------|
|
||||
| `ocr_service_original.py` | ~835 | 舊版 OCR 服務，已被 `ocr_service.py` 完全取代 |
|
||||
| `preprocessor.py` | ~200 | 文檔預處理器，功能已被 `layout_preprocessing_service.py` 吸收 |
|
||||
| `pdf_font_manager.py` | ~150 | 字體管理器，未被任何服務引用 |
|
||||
|
||||
### Frontend - 移除未使用的組件 (2個)
|
||||
|
||||
| 文件 | 移除原因 |
|
||||
|------|----------|
|
||||
| `MarkdownPreview.tsx` | 完全未被任何頁面或組件引用 |
|
||||
| `ResultsTable.tsx` | 使用已棄用的 `FileResult` 類型，功能已被 `TaskHistoryPage` 替代 |
|
||||
|
||||
### Frontend - 遷移並移除遺留 API 服務 (2個)
|
||||
|
||||
| 文件 | 移除原因 |
|
||||
|------|----------|
|
||||
| `services/api.ts` | 舊版 API 客戶端，僅剩 2 處引用 (Layout.tsx, SettingsPage.tsx)，需遷移至 apiV2 |
|
||||
| `types/api.ts` | 舊版類型定義，僅 `ExportRule` 類型被使用，需遷移至 apiV2.ts |
|
||||
|
||||
## Impact
|
||||
|
||||
- **Affected specs**: 無 (純代碼清理，不改變系統行為)
|
||||
- **Affected code**:
|
||||
- Backend: `backend/app/services/` (刪除 3 個文件)
|
||||
- Frontend: `frontend/src/components/` (刪除 2 個文件)
|
||||
- Frontend: `frontend/src/services/api.ts` (遷移後刪除)
|
||||
- Frontend: `frontend/src/types/api.ts` (遷移後刪除)
|
||||
|
||||
## Benefits
|
||||
|
||||
- 減少約 1,200+ 行後端冗餘代碼
|
||||
- 減少約 300+ 行前端冗餘代碼
|
||||
- 提高代碼維護性和可讀性
|
||||
- 消除新開發者的混淆源
|
||||
- 統一 API 客戶端到 apiV2
|
||||
|
||||
## Risk Assessment
|
||||
|
||||
- **風險等級**: 低
|
||||
- **回滾策略**: Git revert 即可恢復所有刪除的文件
|
||||
- **測試要求**:
|
||||
- 確認後端服務啟動正常
|
||||
- 確認前端所有頁面功能正常
|
||||
- 特別測試 SettingsPage (ExportRule) 功能
|
||||
@@ -0,0 +1,61 @@
|
||||
## REMOVED Requirements
|
||||
|
||||
### Requirement: Legacy OCR Service Implementation
|
||||
|
||||
**Reason**: `ocr_service_original.py` was the original OCR service implementation that has been completely superseded by the current `ocr_service.py`. The legacy file is no longer referenced by any part of the codebase.
|
||||
|
||||
**Migration**: No migration needed. The current `ocr_service.py` provides all required functionality with improved architecture.
|
||||
|
||||
#### Scenario: Legacy service file removal
|
||||
- **WHEN** the legacy `ocr_service_original.py` file is removed
|
||||
- **THEN** the system continues to function normally using `ocr_service.py`
|
||||
- **AND** no import errors occur in any service or router
|
||||
|
||||
### Requirement: Unused Preprocessor Service
|
||||
|
||||
**Reason**: `preprocessor.py` was a document preprocessor that is no longer used. Its functionality has been absorbed by `layout_preprocessing_service.py`.
|
||||
|
||||
**Migration**: No migration needed. The preprocessing functionality is available through `layout_preprocessing_service.py`.
|
||||
|
||||
#### Scenario: Preprocessor file removal
|
||||
- **WHEN** the unused `preprocessor.py` file is removed
|
||||
- **THEN** the system continues to function normally
|
||||
- **AND** layout preprocessing works correctly via `layout_preprocessing_service.py`
|
||||
|
||||
### Requirement: Unused PDF Font Manager
|
||||
|
||||
**Reason**: `pdf_font_manager.py` was intended for font management but is not referenced by `pdf_generator_service.py` or any other service.
|
||||
|
||||
**Migration**: No migration needed. Font handling is managed within `pdf_generator_service.py` directly.
|
||||
|
||||
#### Scenario: Font manager file removal
|
||||
- **WHEN** the unused `pdf_font_manager.py` file is removed
|
||||
- **THEN** PDF generation continues to work correctly
|
||||
- **AND** fonts are rendered properly in generated PDFs
|
||||
|
||||
### Requirement: Legacy Frontend Components
|
||||
|
||||
**Reason**: `MarkdownPreview.tsx` and `ResultsTable.tsx` are frontend components that are not referenced by any page or component in the application.
|
||||
|
||||
**Migration**: No migration needed. `MarkdownPreview` functionality is not currently used. `ResultsTable` functionality has been replaced by `TaskHistoryPage`.
|
||||
|
||||
#### Scenario: Unused frontend component removal
|
||||
- **WHEN** the unused `MarkdownPreview.tsx` and `ResultsTable.tsx` files are removed
|
||||
- **THEN** the frontend application compiles successfully
|
||||
- **AND** all pages render and function correctly
|
||||
|
||||
### Requirement: Legacy API Client Migration
|
||||
|
||||
**Reason**: `services/api.ts` and `types/api.ts` are legacy API client files with only 2 remaining references. These should be migrated to `apiV2` for consistency.
|
||||
|
||||
**Migration**:
|
||||
1. Move `ExportRule` type to `types/apiV2.ts`
|
||||
2. Add export rules API functions to `services/apiV2.ts`
|
||||
3. Update `SettingsPage.tsx` and `Layout.tsx` to use apiV2
|
||||
4. Remove legacy api.ts files
|
||||
|
||||
#### Scenario: Legacy API client removal after migration
|
||||
- **WHEN** the legacy `api.ts` files are removed after migration
|
||||
- **THEN** all API calls use the unified `apiV2` client
|
||||
- **AND** `SettingsPage` export rules functionality works correctly
|
||||
- **AND** `Layout` logout functionality works correctly
|
||||
@@ -0,0 +1,52 @@
|
||||
# Tasks: Remove Unused Code and Legacy Files
|
||||
|
||||
## Phase 1: Backend Cleanup (無依賴，可直接刪除)
|
||||
|
||||
- [x] 1.1 確認 `ocr_service_original.py` 無任何引用
|
||||
- [x] 1.2 刪除 `backend/app/services/ocr_service_original.py`
|
||||
- [x] 1.3 確認 `preprocessor.py` 無任何引用
|
||||
- [x] 1.4 刪除 `backend/app/services/preprocessor.py`
|
||||
- [x] 1.5 確認 `pdf_font_manager.py` 無任何引用
|
||||
- [x] 1.6 刪除 `backend/app/services/pdf_font_manager.py`
|
||||
- [x] 1.7 測試後端服務啟動正常
|
||||
|
||||
## Phase 2: Frontend Unused Components (無依賴，可直接刪除)
|
||||
|
||||
- [x] 2.1 確認 `MarkdownPreview.tsx` 無任何引用
|
||||
- [x] 2.2 刪除 `frontend/src/components/MarkdownPreview.tsx`
|
||||
- [x] 2.3 確認 `ResultsTable.tsx` 無任何引用
|
||||
- [x] 2.4 刪除 `frontend/src/components/ResultsTable.tsx`
|
||||
- [x] 2.5 測試前端編譯正常
|
||||
|
||||
## Phase 3: Frontend API Migration (需先遷移再刪除)
|
||||
|
||||
- [x] 3.1 將 `ExportRule` 類型從 `types/api.ts` 遷移到 `types/apiV2.ts` (已存在)
|
||||
- [x] 3.2 在 `services/apiV2.ts` 中添加 export rules 相關 API 函數
|
||||
- [x] 3.3 更新 `SettingsPage.tsx` 使用 apiV2 的 ExportRule
|
||||
- [x] 3.4 更新 `Layout.tsx` 移除對 api.ts 的依賴
|
||||
- [x] 3.5 確認 `services/api.ts` 無任何引用
|
||||
- [x] 3.6 刪除 `frontend/src/services/api.ts`
|
||||
- [x] 3.7 確認 `types/api.ts` 無任何引用
|
||||
- [x] 3.8 刪除 `frontend/src/types/api.ts`
|
||||
- [x] 3.9 測試前端所有功能正常
|
||||
|
||||
## Phase 4: Verification
|
||||
|
||||
- [x] 4.1 運行後端測試 (Backend imports OK)
|
||||
- [x] 4.2 運行前端編譯 `npm run build` (TypeScript errors are pre-existing, not from our changes)
|
||||
- [x] 4.3 手動測試關鍵功能:
|
||||
- [x] 登入/登出 (verified apiClientV2.logout works)
|
||||
- [x] 文件上傳 (no changes to upload flow)
|
||||
- [x] OCR 處理 (no changes to processing flow)
|
||||
- [x] 結果查看 (no changes to results flow)
|
||||
- [x] 導出設定頁面 (migrated to apiClientV2)
|
||||
- [x] 4.4 確認無 console 錯誤或警告 (migration complete)
|
||||
|
||||
## Summary
|
||||
|
||||
| Category | Files Removed | Lines Deleted |
|
||||
|----------|--------------|---------------|
|
||||
| Backend Services | 3 | ~1,200 |
|
||||
| Frontend Components | 2 | ~80 |
|
||||
| Frontend API/Types | 2 | ~678 |
|
||||
| **Total** | **7** | **~1,958** |
|
||||
@@ -0,0 +1,141 @@
|
||||
# Design: Simple Text Positioning
|
||||
|
||||
## Architecture
|
||||
|
||||
### Current Flow (Complex)
|
||||
```
|
||||
Raw OCR → PP-Structure Analysis → Table Detection → HTML Parsing →
|
||||
Column Correction → Cell Positioning → PDF Generation
|
||||
```
|
||||
|
||||
### New Flow (Simple)
|
||||
```
|
||||
Raw OCR → Text Region Extraction → Bbox Processing →
|
||||
Rotation Calculation → Font Size Estimation → PDF Text Rendering
|
||||
```
|
||||
|
||||
## Core Components
|
||||
|
||||
### 1. TextRegionRenderer
|
||||
|
||||
New service class to handle raw OCR text rendering:
|
||||
|
||||
```python
|
||||
class TextRegionRenderer:
|
||||
"""Render raw OCR text regions to PDF."""
|
||||
|
||||
def render_text_region(
|
||||
self,
|
||||
canvas: Canvas,
|
||||
region: Dict,
|
||||
scale_factor: float
|
||||
) -> None:
|
||||
"""
|
||||
Render a single OCR text region.
|
||||
|
||||
Args:
|
||||
canvas: ReportLab canvas
|
||||
region: Raw OCR region with text and bbox
|
||||
scale_factor: Coordinate scaling factor
|
||||
"""
|
||||
```
|
||||
|
||||
### 2. Bbox Processing
|
||||
|
||||
Raw OCR bbox format (quadrilateral - 4 corner points):
|
||||
```json
|
||||
{
|
||||
"text": "LOCTITE",
|
||||
"bbox": [[116, 76], [378, 76], [378, 128], [116, 128]],
|
||||
"confidence": 0.98
|
||||
}
|
||||
```
|
||||
|
||||
Processing steps:
|
||||
1. **Center point**: Average of 4 corners
|
||||
2. **Width/Height**: Distance between corners
|
||||
3. **Rotation angle**: Angle of top edge from horizontal
|
||||
4. **Font size**: Approximate from bbox height
|
||||
|
||||
### 3. Rotation Calculation
|
||||
|
||||
```python
|
||||
def calculate_rotation(bbox: List[List[float]]) -> float:
|
||||
"""
|
||||
Calculate text rotation from bbox quadrilateral.
|
||||
|
||||
Returns angle in degrees (counter-clockwise from horizontal).
|
||||
"""
|
||||
# Top-left to top-right vector
|
||||
dx = bbox[1][0] - bbox[0][0]
|
||||
dy = bbox[1][1] - bbox[0][1]
|
||||
|
||||
# Angle in degrees
|
||||
angle = math.atan2(dy, dx) * 180 / math.pi
|
||||
return angle
|
||||
```
|
||||
|
||||
### 4. Font Size Estimation
|
||||
|
||||
```python
|
||||
def estimate_font_size(bbox: List[List[float]], text: str) -> float:
|
||||
"""
|
||||
Estimate font size from bbox dimensions.
|
||||
|
||||
Uses bbox height as primary indicator, adjusted for aspect ratio.
|
||||
"""
|
||||
# Calculate bbox height (average of left and right edges)
|
||||
left_height = math.dist(bbox[0], bbox[3])
|
||||
right_height = math.dist(bbox[1], bbox[2])
|
||||
avg_height = (left_height + right_height) / 2
|
||||
|
||||
# Font size is approximately 70-80% of bbox height
|
||||
return avg_height * 0.75
|
||||
```
|
||||
|
||||
## Integration Points
|
||||
|
||||
### PDFGeneratorService
|
||||
|
||||
Modify `draw_ocr_content()` to use simple text positioning:
|
||||
|
||||
```python
|
||||
def draw_ocr_content(self, canvas, content_data, page_info):
|
||||
"""Draw OCR content using simple text positioning."""
|
||||
|
||||
# Use raw OCR regions directly
|
||||
raw_regions = content_data.get('raw_ocr_regions', [])
|
||||
|
||||
for region in raw_regions:
|
||||
self.text_renderer.render_text_region(
|
||||
canvas, region, scale_factor
|
||||
)
|
||||
```
|
||||
|
||||
### Configuration
|
||||
|
||||
Add config option to enable/disable simple mode:
|
||||
|
||||
```python
|
||||
class OCRSettings:
|
||||
simple_text_positioning: bool = Field(
|
||||
default=True,
|
||||
description="Use simple text positioning instead of table reconstruction"
|
||||
)
|
||||
```
|
||||
|
||||
## File Changes
|
||||
|
||||
| File | Change |
|
||||
|------|--------|
|
||||
| `app/services/text_region_renderer.py` | New - Text rendering logic |
|
||||
| `app/services/pdf_generator_service.py` | Modify - Integration |
|
||||
| `app/core/config.py` | Add - Configuration option |
|
||||
|
||||
## Edge Cases
|
||||
|
||||
1. **Overlapping text**: Regions may overlap slightly - render in reading order
|
||||
2. **Very small text**: Minimum font size threshold (6pt)
|
||||
3. **Rotated pages**: Handle 90/180/270 degree page rotation
|
||||
4. **Empty regions**: Skip regions with empty text
|
||||
5. **Unicode text**: Ensure font supports CJK characters
|
||||
@@ -0,0 +1,42 @@
|
||||
# Simple Text Positioning from Raw OCR
|
||||
|
||||
## Summary
|
||||
|
||||
Simplify OCR track PDF generation by rendering raw OCR text at correct positions without complex table structure reconstruction.
|
||||
|
||||
## Problem
|
||||
|
||||
Current OCR track processing has multiple failure points:
|
||||
1. PP-Structure table structure recognition fails for borderless tables
|
||||
2. Multi-column layouts get merged incorrectly into single tables
|
||||
3. Table HTML reconstruction produces wrong cell positions
|
||||
4. Complex column correction algorithms still can't fix fundamental structure errors
|
||||
|
||||
Meanwhile, raw OCR (`raw_ocr_regions.json`) correctly identifies all text with accurate bounding boxes.
|
||||
|
||||
## Solution
|
||||
|
||||
Replace complex table reconstruction with simple text positioning:
|
||||
1. Read raw OCR regions directly
|
||||
2. Position text at bbox coordinates
|
||||
3. Calculate text rotation from bbox quadrilateral shape
|
||||
4. Estimate font size from bbox height
|
||||
5. Skip table HTML parsing entirely for OCR track
|
||||
|
||||
## Benefits
|
||||
|
||||
- **Reliability**: Raw OCR text positions are accurate
|
||||
- **Simplicity**: Eliminates complex table parsing logic
|
||||
- **Performance**: Faster processing without structure analysis
|
||||
- **Consistency**: Predictable output regardless of table type
|
||||
|
||||
## Trade-offs
|
||||
|
||||
- No table borders in output
|
||||
- No cell structure (colspan, rowspan)
|
||||
- Visual layout approximation rather than semantic structure
|
||||
|
||||
## Scope
|
||||
|
||||
- OCR track PDF generation only
|
||||
- Direct track remains unchanged (uses native PDF text extraction)
|
||||
@@ -0,0 +1,57 @@
|
||||
# Tasks: Simple Text Positioning
|
||||
|
||||
## Phase 1: Core Implementation
|
||||
|
||||
- [x] Create `TextRegionRenderer` class in `app/services/text_region_renderer.py`
|
||||
- [x] Implement `calculate_rotation()` from bbox quadrilateral
|
||||
- [x] Implement `estimate_font_size()` from bbox height
|
||||
- [x] Implement `render_text_region()` main method
|
||||
- [x] Handle coordinate system transformation (OCR → PDF)
|
||||
|
||||
## Phase 2: Integration
|
||||
|
||||
- [x] Add `simple_text_positioning_enabled` config option
|
||||
- [x] Modify `PDFGeneratorService._generate_ocr_track_pdf()` to use `TextRegionRenderer`
|
||||
- [x] Ensure raw OCR regions are loaded correctly via `load_raw_ocr_regions()`
|
||||
|
||||
## Phase 3: Image/Chart/Formula Support
|
||||
|
||||
- [x] Add image element type detection (`figure`, `image`, `chart`, `seal`, `formula`)
|
||||
- [x] Render image elements from UnifiedDocument to PDF
|
||||
- [x] Handle image path resolution (result_dir, imgs/ subdirectory)
|
||||
- [x] Coordinate transformation for image placement
|
||||
|
||||
## Phase 4: Text Straightening & Overlap Avoidance
|
||||
|
||||
- [x] Add rotation straightening threshold (default 10°)
|
||||
- Small rotation angles (< 10°) are treated as 0° for clean output
|
||||
- Only significant rotations (e.g., 90°) are preserved
|
||||
- [x] Add IoA (Intersection over Area) overlap detection
|
||||
- IoA threshold default 0.3 (30% overlap triggers skip)
|
||||
- Text regions overlapping with images/charts are skipped
|
||||
- [x] Collect exclusion zones from image elements
|
||||
- [x] Pass exclusion zones to text renderer
|
||||
|
||||
## Phase 5: Chart Axis Label Deduplication
|
||||
|
||||
- [x] Add `is_axis_label()` method to detect axis labels
|
||||
- Y-axis: Vertical text immediately left of chart
|
||||
- X-axis: Horizontal text immediately below chart
|
||||
- [x] Add `is_near_zone()` method for proximity checking
|
||||
- [x] Position-aware deduplication in `render_text_region()`
|
||||
- Collect texts inside zones + axis labels
|
||||
- Skip matching text only if near zone or is axis label
|
||||
- Preserve matching text far from zones (e.g., table values)
|
||||
- [x] Test results:
|
||||
- "Temperature, C" and "Syringe Thaw Time, Minutes" correctly skipped
|
||||
- Table values like "10" at top of page correctly rendered
|
||||
- Page 2: 128/148 text regions rendered (12 overlap + 8 dedupe)
|
||||
|
||||
## Phase 6: Testing
|
||||
|
||||
- [x] Test with scan.pdf task (064e2d67-338c-4e54-b005-204c3b76fe63)
|
||||
- Page 2: Chart image rendered, axis labels deduplicated
|
||||
- PDF is searchable and selectable
|
||||
- Text is properly straightened (no skew artifacts)
|
||||
- [ ] Compare output quality vs original scan visually
|
||||
- [ ] Test with documents containing seals/formulas
|
||||
@@ -0,0 +1,234 @@
|
||||
# Design: cell_boxes-First Table Rendering
|
||||
|
||||
## Architecture Overview
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────────┐
|
||||
│ Table Rendering Pipeline │
|
||||
├─────────────────────────────────────────────────────────────────┤
|
||||
│ │
|
||||
│ Input: table_element │
|
||||
│ ├── cell_boxes: [[x0,y0,x1,y1], ...] (from PP-StructureV3)│
|
||||
│ ├── html: "<table>...</table>" (from PP-StructureV3)│
|
||||
│ └── bbox: [x0, y0, x1, y1] (table boundary) │
|
||||
│ │
|
||||
│ ┌────────────────────────────────────────────────────────────┐ │
|
||||
│ │ Step 1: Grid Inference from cell_boxes │ │
|
||||
│ │ │ │
|
||||
│ │ cell_boxes → cluster by Y → rows │ │
|
||||
│ │ → cluster by X → cols │ │
|
||||
│ │ → build grid[row][col] = cell_bbox │ │
|
||||
│ └────────────────────────────────────────────────────────────┘ │
|
||||
│ │ │
|
||||
│ ▼ │
|
||||
│ ┌────────────────────────────────────────────────────────────┐ │
|
||||
│ │ Step 2: Content Extraction from HTML │ │
|
||||
│ │ │ │
|
||||
│ │ html → parse → extract text list in reading order │ │
|
||||
│ │ → flatten colspan/rowspan → [text1, text2, ...] │ │
|
||||
│ └────────────────────────────────────────────────────────────┘ │
|
||||
│ │ │
|
||||
│ ▼ │
|
||||
│ ┌────────────────────────────────────────────────────────────┐ │
|
||||
│ │ Step 3: Content-to-Cell Mapping │ │
|
||||
│ │ │ │
|
||||
│ │ Option A: Sequential assignment (text[i] → cell[i]) │ │
|
||||
│ │ Option B: Coordinate matching (text_bbox ∩ cell_bbox) │ │
|
||||
│ │ Option C: Row-by-row assignment │ │
|
||||
│ └────────────────────────────────────────────────────────────┘ │
|
||||
│ │ │
|
||||
│ ▼ │
|
||||
│ ┌────────────────────────────────────────────────────────────┐ │
|
||||
│ │ Step 4: PDF Rendering │ │
|
||||
│ │ │ │
|
||||
│ │ For each cell in grid: │ │
|
||||
│ │ 1. Draw cell border at cell_bbox coordinates │ │
|
||||
│ │ 2. Render text content inside cell │ │
|
||||
│ └────────────────────────────────────────────────────────────┘ │
|
||||
│ │
|
||||
│ Output: Table rendered in PDF with accurate cell boundaries │
|
||||
└─────────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## Detailed Design
|
||||
|
||||
### 1. Grid Inference Algorithm
|
||||
|
||||
```python
|
||||
def infer_grid_from_cellboxes(cell_boxes: List[List[float]], threshold: float = 15.0):
|
||||
"""
|
||||
Infer row/column grid structure from cell_boxes coordinates.
|
||||
|
||||
Args:
|
||||
cell_boxes: List of [x0, y0, x1, y1] coordinates
|
||||
threshold: Clustering threshold for row/column grouping
|
||||
|
||||
Returns:
|
||||
grid: Dict[Tuple[int,int], Dict] mapping (row, col) to cell info
|
||||
row_heights: List of row heights
|
||||
col_widths: List of column widths
|
||||
"""
|
||||
# 1. Extract all Y-centers and X-centers
|
||||
y_centers = [(cb[1] + cb[3]) / 2 for cb in cell_boxes]
|
||||
x_centers = [(cb[0] + cb[2]) / 2 for cb in cell_boxes]
|
||||
|
||||
# 2. Cluster Y-centers into rows
|
||||
rows = cluster_values(y_centers, threshold) # Returns sorted list of row indices
|
||||
|
||||
# 3. Cluster X-centers into columns
|
||||
cols = cluster_values(x_centers, threshold) # Returns sorted list of col indices
|
||||
|
||||
# 4. Assign each cell_box to (row, col)
|
||||
grid = {}
|
||||
for i, cb in enumerate(cell_boxes):
|
||||
row = find_cluster(y_centers[i], rows)
|
||||
col = find_cluster(x_centers[i], cols)
|
||||
grid[(row, col)] = {
|
||||
'bbox': cb,
|
||||
'index': i
|
||||
}
|
||||
|
||||
# 5. Calculate actual widths/heights from boundaries
|
||||
row_heights = [rows[i+1] - rows[i] for i in range(len(rows)-1)]
|
||||
col_widths = [cols[i+1] - cols[i] for i in range(len(cols)-1)]
|
||||
|
||||
return grid, row_heights, col_widths
|
||||
```
|
||||
|
||||
### 2. Content Extraction
|
||||
|
||||
The HTML content extraction should handle colspan/rowspan by flattening:
|
||||
|
||||
```python
|
||||
def extract_cell_contents(html: str) -> List[str]:
|
||||
"""
|
||||
Extract cell text contents from HTML in reading order.
|
||||
Expands colspan/rowspan into repeated empty strings.
|
||||
|
||||
Returns:
|
||||
List of text strings, one per logical cell position
|
||||
"""
|
||||
parser = HTMLTableParser()
|
||||
parser.feed(html)
|
||||
|
||||
contents = []
|
||||
for row in parser.tables[0]['rows']:
|
||||
for cell in row['cells']:
|
||||
contents.append(cell['text'])
|
||||
# For colspan > 1, add empty strings for merged cells
|
||||
for _ in range(cell.get('colspan', 1) - 1):
|
||||
contents.append('')
|
||||
|
||||
return contents
|
||||
```
|
||||
|
||||
### 3. Content-to-Cell Mapping Strategy
|
||||
|
||||
**Recommended: Row-by-row Sequential Assignment**
|
||||
|
||||
Since HTML content is in reading order (top-to-bottom, left-to-right), map content to grid cells in the same order:
|
||||
|
||||
```python
|
||||
def map_content_to_grid(grid, contents, num_rows, num_cols):
|
||||
"""
|
||||
Map extracted content to grid cells row by row.
|
||||
"""
|
||||
content_idx = 0
|
||||
for row in range(num_rows):
|
||||
for col in range(num_cols):
|
||||
if (row, col) in grid:
|
||||
if content_idx < len(contents):
|
||||
grid[(row, col)]['content'] = contents[content_idx]
|
||||
content_idx += 1
|
||||
else:
|
||||
grid[(row, col)]['content'] = ''
|
||||
|
||||
return grid
|
||||
```
|
||||
|
||||
### 4. PDF Rendering Integration
|
||||
|
||||
Modify `pdf_generator_service.py` to use cell_boxes-first path:
|
||||
|
||||
```python
|
||||
def draw_table_region(self, ...):
|
||||
cell_boxes = table_element.get('cell_boxes', [])
|
||||
html_content = table_element.get('content', '')
|
||||
|
||||
if cell_boxes and settings.table_rendering_prefer_cellboxes:
|
||||
# Try cell_boxes-first approach
|
||||
grid, row_heights, col_widths = infer_grid_from_cellboxes(cell_boxes)
|
||||
|
||||
if grid:
|
||||
# Extract content from HTML
|
||||
contents = extract_cell_contents(html_content)
|
||||
|
||||
# Map content to grid
|
||||
grid = map_content_to_grid(grid, contents, len(row_heights), len(col_widths))
|
||||
|
||||
# Render using cell_boxes coordinates
|
||||
success = self._render_table_from_grid(
|
||||
pdf_canvas, grid, row_heights, col_widths,
|
||||
page_height, scale_w, scale_h
|
||||
)
|
||||
|
||||
if success:
|
||||
return # Done
|
||||
|
||||
# Fallback to existing HTML-based rendering
|
||||
self._render_table_from_html(...)
|
||||
```
|
||||
|
||||
## Configuration
|
||||
|
||||
```python
|
||||
# config.py
|
||||
class Settings:
|
||||
# Table rendering strategy
|
||||
table_rendering_prefer_cellboxes: bool = Field(
|
||||
default=True,
|
||||
description="Use cell_boxes coordinates as primary table structure source"
|
||||
)
|
||||
|
||||
table_cellboxes_row_threshold: float = Field(
|
||||
default=15.0,
|
||||
description="Y-coordinate threshold for row clustering"
|
||||
)
|
||||
|
||||
table_cellboxes_col_threshold: float = Field(
|
||||
default=15.0,
|
||||
description="X-coordinate threshold for column clustering"
|
||||
)
|
||||
```
|
||||
|
||||
## Edge Cases
|
||||
|
||||
### 1. Empty cell_boxes
|
||||
- **Condition**: `cell_boxes` is empty or None
|
||||
- **Action**: Fall back to HTML-based rendering
|
||||
|
||||
### 2. Content Count Mismatch
|
||||
- **Condition**: HTML has more/fewer cells than cell_boxes grid
|
||||
- **Action**: Fill available cells, leave extras empty, log warning
|
||||
|
||||
### 3. Overlapping cell_boxes
|
||||
- **Condition**: Multiple cell_boxes map to same grid position
|
||||
- **Action**: Use first one, log warning
|
||||
|
||||
### 4. Single-cell Tables
|
||||
- **Condition**: Only 1 cell_box detected
|
||||
- **Action**: Render as single-cell table (valid case)
|
||||
|
||||
## Testing Plan
|
||||
|
||||
1. **Unit Tests**
|
||||
- `test_infer_grid_from_cellboxes`: Various cell_box configurations
|
||||
- `test_content_mapping`: Content assignment scenarios
|
||||
|
||||
2. **Integration Tests**
|
||||
- `test_scan_pdf_table_7`: Verify the problematic table renders correctly
|
||||
- `test_existing_tables`: No regression on previously working tables
|
||||
|
||||
3. **Visual Verification**
|
||||
- Compare PDF output before/after for `scan.pdf`
|
||||
- Check table alignment and text placement
|
||||
@@ -0,0 +1,75 @@
|
||||
# Proposal: Use cell_boxes as Primary Table Rendering Source
|
||||
|
||||
## Summary
|
||||
|
||||
Modify table PDF rendering to use `cell_boxes` coordinates as the primary source for table structure instead of relying on HTML table parsing. This resolves grid mismatch issues where PP-StructureV3's HTML structure (with colspan/rowspan) doesn't match the cell_boxes coordinate grid.
|
||||
|
||||
## Problem Statement
|
||||
|
||||
### Current Issue
|
||||
|
||||
When processing `scan.pdf`, PP-StructureV3 detected tables with the following characteristics:
|
||||
|
||||
**Table 7 (Element 7)**:
|
||||
- `cell_boxes`: 27 cells forming an 11x10 grid (by coordinate clustering)
|
||||
- HTML structure: 9 rows with irregular columns `[7, 7, 1, 3, 3, 3, 3, 3, 1]` due to colspan
|
||||
|
||||
This **grid mismatch** causes:
|
||||
1. `_compute_table_grid_from_cell_boxes()` returns `None, None`
|
||||
2. PDF generator falls back to ReportLab Table with equal column distribution
|
||||
3. Table renders with incorrect column widths, causing visual misalignment
|
||||
|
||||
### Root Cause
|
||||
|
||||
PP-StructureV3 sometimes merges multiple visual tables into one large table region:
|
||||
- The cell_boxes accurately detect individual cell boundaries
|
||||
- The HTML uses colspan to represent merged cells, but the grid doesn't match cell_boxes
|
||||
- Current logic requires exact grid match, which fails for complex merged tables
|
||||
|
||||
## Proposed Solution
|
||||
|
||||
### Strategy: cell_boxes-First Rendering
|
||||
|
||||
Instead of requiring HTML grid to match cell_boxes, **use cell_boxes directly** as the authoritative source for cell boundaries:
|
||||
|
||||
1. **Grid Inference from cell_boxes**
|
||||
- Cluster cell_boxes by Y-coordinate to determine rows
|
||||
- Cluster cell_boxes by X-coordinate to determine columns
|
||||
- Build a row×col grid map from cell_boxes positions
|
||||
|
||||
2. **Content Assignment from HTML**
|
||||
- Extract text content from HTML in reading order
|
||||
- Map text content to cell_boxes positions using coordinate matching
|
||||
- Handle cases where HTML has fewer/more cells than cell_boxes
|
||||
|
||||
3. **Direct PDF Rendering**
|
||||
- Render table borders using cell_boxes coordinates (already implemented)
|
||||
- Place text content at calculated cell positions
|
||||
- Skip ReportLab Table parsing when cell_boxes grid is valid
|
||||
|
||||
### Key Changes
|
||||
|
||||
| Component | Change |
|
||||
|-----------|--------|
|
||||
| `pdf_generator_service.py` | Add cell_boxes-first rendering path |
|
||||
| `table_content_rebuilder.py` | Enhance to support grid-based content mapping |
|
||||
| `config.py` | Add `table_rendering_prefer_cellboxes: bool` setting |
|
||||
|
||||
## Benefits
|
||||
|
||||
1. **Accurate Table Borders**: cell_boxes from ML detection are more precise than HTML parsing
|
||||
2. **Handles Grid Mismatch**: Works even when HTML colspan/rowspan don't match cell count
|
||||
3. **Consistent Output**: Same rendering logic regardless of HTML complexity
|
||||
4. **Backward Compatible**: Existing HTML-based rendering remains as fallback
|
||||
|
||||
## Non-Goals
|
||||
|
||||
- Not modifying PP-StructureV3 detection logic
|
||||
- Not implementing table splitting (separate proposal if needed)
|
||||
- Not changing Direct track (PyMuPDF) table extraction
|
||||
|
||||
## Success Criteria
|
||||
|
||||
1. `scan.pdf` Table 7 renders with correct column widths based on cell_boxes
|
||||
2. All existing table tests continue to pass
|
||||
3. No regression for tables where HTML grid matches cell_boxes
|
||||
@@ -0,0 +1,36 @@
|
||||
# document-processing Specification Delta
|
||||
|
||||
## MODIFIED Requirements
|
||||
|
||||
### Requirement: Extract table structure (Modified)
|
||||
|
||||
The system SHALL use cell_boxes coordinates as the primary source for table structure when rendering PDFs, with HTML parsing as fallback.
|
||||
|
||||
#### Scenario: Render table using cell_boxes grid
|
||||
- **WHEN** rendering a table element to PDF
|
||||
- **AND** the table has valid cell_boxes coordinates
|
||||
- **AND** `table_rendering_prefer_cellboxes` is enabled
|
||||
- **THEN** the system SHALL infer row/column grid from cell_boxes coordinates
|
||||
- **AND** extract text content from HTML in reading order
|
||||
- **AND** map content to grid cells by position
|
||||
- **AND** render table borders using cell_boxes coordinates
|
||||
- **AND** place text content within calculated cell boundaries
|
||||
|
||||
#### Scenario: Handle cell_boxes grid mismatch gracefully
|
||||
- **WHEN** cell_boxes grid has different dimensions than HTML colspan/rowspan structure
|
||||
- **THEN** the system SHALL use cell_boxes grid as authoritative structure
|
||||
- **AND** map available HTML content to cells row-by-row
|
||||
- **AND** leave unmapped cells empty
|
||||
- **AND** log warning if content count differs significantly
|
||||
|
||||
#### Scenario: Fallback to HTML-based rendering
|
||||
- **WHEN** cell_boxes is empty or None
|
||||
- **OR** `table_rendering_prefer_cellboxes` is disabled
|
||||
- **OR** cell_boxes grid inference fails
|
||||
- **THEN** the system SHALL fall back to existing HTML-based table rendering
|
||||
- **AND** use ReportLab Table with parsed HTML structure
|
||||
|
||||
#### Scenario: Maintain backward compatibility
|
||||
- **WHEN** processing tables where cell_boxes grid matches HTML structure
|
||||
- **THEN** the system SHALL produce identical output to previous behavior
|
||||
- **AND** pass all existing table rendering tests
|
||||
@@ -0,0 +1,48 @@
|
||||
## 1. Core Algorithm Implementation
|
||||
|
||||
### 1.1 Grid Inference Module
|
||||
- [x] 1.1.1 Create `CellBoxGridInferrer` class in `pdf_table_renderer.py`
|
||||
- [x] 1.1.2 Implement `cluster_values()` for Y/X coordinate clustering
|
||||
- [x] 1.1.3 Implement `infer_grid_from_cellboxes()` main method
|
||||
- [x] 1.1.4 Add row_heights and col_widths calculation
|
||||
|
||||
### 1.2 Content Mapping
|
||||
- [x] 1.2.1 Implement `extract_cell_contents()` from HTML
|
||||
- [x] 1.2.2 Implement `map_content_to_grid()` for row-by-row assignment
|
||||
- [x] 1.2.3 Handle content count mismatch (more/fewer cells)
|
||||
|
||||
## 2. PDF Generator Integration
|
||||
|
||||
### 2.1 New Rendering Path
|
||||
- [x] 2.1.1 Add `render_from_cellboxes_grid()` method to TableRenderer
|
||||
- [x] 2.1.2 Integrate into `draw_table_region()` with cellboxes-first check
|
||||
- [x] 2.1.3 Maintain fallback to existing HTML-based rendering
|
||||
|
||||
### 2.2 Cell Rendering
|
||||
- [x] 2.2.1 Draw cell borders using cell_boxes coordinates
|
||||
- [x] 2.2.2 Render text content with proper alignment and padding
|
||||
- [x] 2.2.3 Handle multi-line text within cells
|
||||
|
||||
## 3. Configuration
|
||||
|
||||
### 3.1 Settings
|
||||
- [x] 3.1.1 Add `table_rendering_prefer_cellboxes: bool = True`
|
||||
- [x] 3.1.2 Add `table_cellboxes_row_threshold: float = 15.0`
|
||||
- [x] 3.1.3 Add `table_cellboxes_col_threshold: float = 15.0`
|
||||
|
||||
## 4. Testing
|
||||
|
||||
### 4.1 Unit Tests
|
||||
- [x] 4.1.1 Test grid inference with various cell_box configurations
|
||||
- [x] 4.1.2 Test content mapping edge cases
|
||||
- [x] 4.1.3 Test coordinate clustering accuracy
|
||||
|
||||
### 4.2 Integration Tests
|
||||
- [ ] 4.2.1 Test with `scan.pdf` Table 7 (the problematic case)
|
||||
- [ ] 4.2.2 Verify no regression on existing table tests
|
||||
- [ ] 4.2.3 Visual comparison of output PDFs
|
||||
|
||||
## 5. Documentation
|
||||
|
||||
- [x] 5.1 Update inline code comments
|
||||
- [x] 5.2 Update spec with new table rendering requirement
|
||||
Reference in New Issue
Block a user