From cfe65158a33eab790c3caaaf5c2de40c54a71579 Mon Sep 17 00:00:00 2001 From: egg Date: Thu, 11 Dec 2025 17:13:46 +0800 Subject: [PATCH] feat: enable document orientation detection for scanned PDFs MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 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 --- backend/app/core/config.py | 69 +- backend/app/routers/tasks.py | 76 +- backend/app/schemas/task.py | 175 ---- .../app/services/cell_validation_engine.py | 583 ------------- backend/app/services/gap_filling_service.py | 34 +- backend/app/services/ocr_service.py | 51 +- backend/app/services/pdf_generator.py | 507 ----------- backend/app/services/pdf_generator_service.py | 136 +-- backend/app/services/pp_structure_debug.py | 40 +- backend/app/services/pp_structure_enhanced.py | 107 ++- .../app/services/table_content_rebuilder.py | 806 ------------------ backend/app/services/text_region_renderer.py | 46 +- backend/app/utils/__init__.py | 5 + backend/app/utils/bbox_utils.py | 265 ++++++ frontend/src/components/OCRPresetSelector.tsx | 358 -------- frontend/src/components/PDFViewer.tsx | 4 +- .../src/components/TableDetectionSelector.tsx | 124 --- frontend/src/hooks/useTaskValidation.ts | 3 +- frontend/src/pages/AuditLogsPage.tsx | 10 +- frontend/src/pages/ExportPage.tsx | 3 +- frontend/src/pages/ProcessingPage.tsx | 41 +- frontend/src/pages/TaskDetailPage.tsx | 3 +- frontend/src/pages/TaskHistoryPage.tsx | 2 +- frontend/src/pages/UploadPage.tsx | 8 +- frontend/src/services/apiV2.ts | 3 +- frontend/src/store/taskStore.ts | 6 +- frontend/src/types/apiV2.ts | 68 -- .../2025-12-11-cleanup-dead-code/proposal.md | 175 ++++ .../specs/document-processing/spec.md | 42 + .../2025-12-11-cleanup-dead-code/tasks.md | 92 ++ .../design.md | 0 .../proposal.md | 0 .../specs/ocr-processing/spec.md | 0 .../tasks.md | 0 .../design.md | 0 .../proposal.md | 0 .../specs/document-processing/spec.md | 0 .../tasks.md | 0 .../proposal.md | 0 .../specs/ocr-processing/spec.md | 0 .../tasks.md | 0 .../proposal.md | 0 .../specs/document-processing/spec.md | 0 .../2025-12-11-remove-unused-code}/tasks.md | 0 .../design.md | 0 .../proposal.md | 0 .../tasks.md | 0 .../design.md | 0 .../proposal.md | 0 .../specs/document-processing/spec.md | 0 .../tasks.md | 0 .../proposal.md | 52 ++ .../specs/ocr-processing/spec.md | 80 ++ .../enable-doc-orientation-detection/tasks.md | 71 ++ .../simplify-frontend-ocr-config/proposal.md | 25 + .../specs/ocr-processing/spec.md | 127 +++ .../simplify-frontend-ocr-config/tasks.md | 51 ++ openspec/specs/ocr-processing/spec.md | 71 +- 58 files changed, 1271 insertions(+), 3048 deletions(-) delete mode 100644 backend/app/services/cell_validation_engine.py delete mode 100644 backend/app/services/pdf_generator.py delete mode 100644 backend/app/services/table_content_rebuilder.py create mode 100644 backend/app/utils/__init__.py create mode 100644 backend/app/utils/bbox_utils.py delete mode 100644 frontend/src/components/OCRPresetSelector.tsx delete mode 100644 frontend/src/components/TableDetectionSelector.tsx create mode 100644 openspec/changes/archive/2025-12-11-cleanup-dead-code/proposal.md create mode 100644 openspec/changes/archive/2025-12-11-cleanup-dead-code/specs/document-processing/spec.md create mode 100644 openspec/changes/archive/2025-12-11-cleanup-dead-code/tasks.md rename openspec/changes/{fix-ocr-track-table-rendering => archive/2025-12-11-fix-ocr-track-table-rendering}/design.md (100%) rename openspec/changes/{fix-ocr-track-table-rendering => archive/2025-12-11-fix-ocr-track-table-rendering}/proposal.md (100%) rename openspec/changes/{fix-ocr-track-table-rendering => archive/2025-12-11-fix-ocr-track-table-rendering}/specs/ocr-processing/spec.md (100%) rename openspec/changes/{fix-ocr-track-table-rendering => archive/2025-12-11-fix-ocr-track-table-rendering}/tasks.md (100%) rename openspec/changes/{fix-table-column-alignment => archive/2025-12-11-fix-table-column-alignment}/design.md (100%) rename openspec/changes/{fix-table-column-alignment => archive/2025-12-11-fix-table-column-alignment}/proposal.md (100%) rename openspec/changes/{fix-table-column-alignment => archive/2025-12-11-fix-table-column-alignment}/specs/document-processing/spec.md (100%) rename openspec/changes/{fix-table-column-alignment => archive/2025-12-11-fix-table-column-alignment}/tasks.md (100%) rename openspec/changes/{improve-ocr-track-algorithm => archive/2025-12-11-improve-ocr-track-algorithm}/proposal.md (100%) rename openspec/changes/{improve-ocr-track-algorithm => archive/2025-12-11-improve-ocr-track-algorithm}/specs/ocr-processing/spec.md (100%) rename openspec/changes/{improve-ocr-track-algorithm => archive/2025-12-11-improve-ocr-track-algorithm}/tasks.md (100%) rename openspec/changes/{remove-unused-code => archive/2025-12-11-remove-unused-code}/proposal.md (100%) rename openspec/changes/{remove-unused-code => archive/2025-12-11-remove-unused-code}/specs/document-processing/spec.md (100%) rename openspec/changes/{remove-unused-code => archive/2025-12-11-remove-unused-code}/tasks.md (100%) rename openspec/changes/{simple-text-positioning => archive/2025-12-11-simple-text-positioning}/design.md (100%) rename openspec/changes/{simple-text-positioning => archive/2025-12-11-simple-text-positioning}/proposal.md (100%) rename openspec/changes/{simple-text-positioning => archive/2025-12-11-simple-text-positioning}/tasks.md (100%) rename openspec/changes/{use-cellboxes-for-table-rendering => archive/2025-12-11-use-cellboxes-for-table-rendering}/design.md (100%) rename openspec/changes/{use-cellboxes-for-table-rendering => archive/2025-12-11-use-cellboxes-for-table-rendering}/proposal.md (100%) rename openspec/changes/{use-cellboxes-for-table-rendering => archive/2025-12-11-use-cellboxes-for-table-rendering}/specs/document-processing/spec.md (100%) rename openspec/changes/{use-cellboxes-for-table-rendering => archive/2025-12-11-use-cellboxes-for-table-rendering}/tasks.md (100%) create mode 100644 openspec/changes/enable-doc-orientation-detection/proposal.md create mode 100644 openspec/changes/enable-doc-orientation-detection/specs/ocr-processing/spec.md create mode 100644 openspec/changes/enable-doc-orientation-detection/tasks.md create mode 100644 openspec/changes/simplify-frontend-ocr-config/proposal.md create mode 100644 openspec/changes/simplify-frontend-ocr-config/specs/ocr-processing/spec.md create mode 100644 openspec/changes/simplify-frontend-ocr-config/tasks.md diff --git a/backend/app/core/config.py b/backend/app/core/config.py index 44e2959..d115761 100644 --- a/backend/app/core/config.py +++ b/backend/app/core/config.py @@ -90,11 +90,16 @@ class Settings(BaseSettings): max_concurrent_pages: int = Field(default=2) # Process 2 pages concurrently # PP-StructureV3 optimization + # Strategy: Use raw OCR positioning (simple-text-positioning) instead of table structure reconstruction + # - Layout Detection: ON (detect regions) + # - General OCR: ON (text recognition) + # - Table Recognition: OFF (no cell/structure parsing - use raw OCR bbox instead) + # - Seal/Formula/Chart: ON (specialized recognition) enable_chart_recognition: bool = Field(default=True) # Chart/diagram recognition enable_formula_recognition: bool = Field(default=True) # Math formula recognition - enable_table_recognition: bool = Field(default=True) # Table structure recognition + enable_table_recognition: bool = Field(default=False) # Table structure recognition - DISABLED (use raw OCR) enable_seal_recognition: bool = Field(default=True) # Seal/stamp recognition - enable_region_detection: bool = Field(default=True) # Region detection for better table structure + enable_region_detection: bool = Field(default=True) # Region detection for layout enable_text_recognition: bool = Field(default=True) # General text recognition # Table Parsing Mode - Controls how aggressively tables are parsed @@ -116,57 +121,6 @@ class Settings(BaseSettings): description="Layout threshold for ALL element detection. Higher values = fewer elements detected." ) - # Cell Validation (filter over-detected table cells) - # DISABLED: This is a patch behavior - focus on getting PP-Structure output right first - cell_validation_enabled: bool = Field( - default=False, - description="Enable cell validation to filter over-detected tables" - ) - cell_validation_max_density: float = Field( - default=3.0, - description="Max cells per 10,000px². Tables exceeding this are reclassified as TEXT." - ) - cell_validation_min_cell_area: float = Field( - default=3000.0, - description="Min average cell area in px². Tables below this are reclassified as TEXT." - ) - cell_validation_min_cell_height: float = Field( - default=10.0, - description="Min average cell height in px. Tables below this are reclassified as TEXT." - ) - - # Table Content Rebuilder (rebuild table HTML from raw OCR) - # DISABLED: This is a patch behavior - focus on getting PP-Structure output right first - table_content_rebuilder_enabled: bool = Field( - default=False, - description="Enable table content rebuilder to fix PP-Structure table HTML" - ) - - # Table Quality Check (determines rendering strategy based on cell_boxes overlap) - # When enabled, tables with overlapping cell_boxes are marked as 'bad' quality - # and rendered with border-only mode instead of full cell_boxes rendering. - # Disable this to always use cell_boxes rendering regardless of quality. - table_quality_check_enabled: bool = Field( - default=False, - description="Enable cell_boxes quality check. When disabled, all tables use cell_boxes rendering." - ) - - # Table Rendering: cell_boxes-first approach - # When enabled, uses cell_boxes coordinates as the primary source for table structure - # instead of relying on HTML colspan/rowspan, which often causes grid mismatch issues - # DISABLED: Algorithm needs improvement - clustering produces incorrect grid dimensions - table_rendering_prefer_cellboxes: bool = Field( - default=False, - description="Use cell_boxes coordinates as primary table structure source for PDF rendering" - ) - table_cellboxes_row_threshold: float = Field( - default=15.0, - description="Y-coordinate threshold for row clustering when inferring grid from cell_boxes" - ) - table_cellboxes_col_threshold: float = Field( - default=15.0, - description="X-coordinate threshold for column clustering when inferring grid from cell_boxes" - ) # Table Column Alignment Correction (Header-Anchor Algorithm) # Corrects PP-Structure's column assignment errors using header row X-coordinates as reference @@ -204,7 +158,10 @@ class Settings(BaseSettings): ) # PP-StructureV3 Preprocessing (Stage 1) - use_doc_orientation_classify: bool = Field(default=True) # Auto-detect and correct document rotation + # NOTE: doc_orientation_classify ENABLED - detects and corrects document orientation + # for scanned PDFs where content orientation differs from PDF page metadata. + # When rotation is detected (90°/270°), page dimensions are swapped accordingly. + use_doc_orientation_classify: bool = Field(default=True) # Enabled: auto-detect and correct page orientation use_doc_unwarping: bool = Field(default=False) # Disabled: can cause document distortion/skewing use_textline_orientation: bool = Field(default=True) # Detect textline orientation @@ -417,10 +374,6 @@ class Settings(BaseSettings): description="Use PP-StructureV3's internal OCR results instead of separate inference." ) - # Legacy IoU threshold (deprecated, kept for backward compatibility) - gap_filling_iou_threshold: float = Field(default=0.15) # Deprecated: use IoA thresholds - gap_filling_dedup_iou_threshold: float = Field(default=0.5) # Deprecated: use gap_filling_dedup_ioa_threshold - # ===== Debug Configuration ===== # Enable debug outputs for PP-StructureV3 analysis pp_structure_debug_enabled: bool = Field(default=True) # Save debug files for PP-StructureV3 diff --git a/backend/app/routers/tasks.py b/backend/app/routers/tasks.py index 062c3de..14b66fe 100644 --- a/backend/app/routers/tasks.py +++ b/backend/app/routers/tasks.py @@ -40,10 +40,6 @@ from app.schemas.task import ( PreprocessingPreviewRequest, PreprocessingPreviewResponse, ImageQualityMetrics, - TableDetectionConfig, - OCRPresetEnum, - OCRConfig, - OCR_PRESET_CONFIGS, ) from app.services.task_service import task_service from app.services.file_access_service import file_access_service @@ -79,10 +75,7 @@ def process_task_ocr( language: str = 'ch', layout_model: Optional[str] = "chinese", preprocessing_mode: Optional[str] = "auto", - preprocessing_config: Optional[dict] = None, - table_detection_config: Optional[dict] = None, - ocr_preset: Optional[str] = None, - ocr_config: Optional[dict] = None + preprocessing_config: Optional[dict] = None ): """ Background task to process OCR for a task with dual-track support. @@ -101,9 +94,6 @@ def process_task_ocr( layout_model: Layout detection model ('chinese', 'default', 'cdla') preprocessing_mode: Preprocessing mode ('auto', 'manual', 'disabled') preprocessing_config: Manual preprocessing config dict (contrast, sharpen, binarize) - table_detection_config: Table detection config dict (enable_wired_table, enable_wireless_table, enable_region_detection) - ocr_preset: OCR processing preset (text_heavy, datasheet, table_heavy, form, mixed, custom) - ocr_config: Custom OCR config dict (overrides preset values) """ from app.core.database import SessionLocal from app.models.task import Task @@ -116,7 +106,6 @@ def process_task_ocr( logger.info(f"Starting OCR processing for task {task_id}, file: {filename}") logger.info(f"Processing options: dual_track={use_dual_track}, force_track={force_track}, lang={language}") logger.info(f"Preprocessing options: mode={preprocessing_mode}, config={preprocessing_config}") - logger.info(f"Table detection options: {table_detection_config}") # Convert preprocessing parameters to proper types preprocess_mode_enum = None @@ -133,35 +122,6 @@ def process_task_ocr( binarize=preprocessing_config.get("binarize", False) ) - # Convert table detection config to object - table_det_config_obj = None - if table_detection_config: - table_det_config_obj = TableDetectionConfig( - enable_wired_table=table_detection_config.get("enable_wired_table", True), - enable_wireless_table=table_detection_config.get("enable_wireless_table", True), - enable_region_detection=table_detection_config.get("enable_region_detection", True) - ) - - # Convert OCR preset and config to proper objects - from app.schemas.task import OCRPresetEnum, OCRConfig, OCR_PRESET_CONFIGS, TableParsingModeEnum - ocr_config_obj = None - if ocr_preset: - preset_enum = OCRPresetEnum(ocr_preset) - # Get preset config as base - if preset_enum in OCR_PRESET_CONFIGS: - ocr_config_obj = OCR_PRESET_CONFIGS[preset_enum].model_copy() - else: - # CUSTOM preset - use provided config or defaults - ocr_config_obj = OCRConfig() - - # Override with custom config values if provided - if ocr_config: - for key, value in ocr_config.items(): - if hasattr(ocr_config_obj, key) and value is not None: - setattr(ocr_config_obj, key, value) - - logger.info(f"OCR config resolved: preset={ocr_preset}, config={ocr_config_obj.model_dump() if ocr_config_obj else None}") - # Get task directly by database ID (bypass user isolation for background task) task = db.query(Task).filter(Task.id == task_db_id).first() if not task: @@ -210,9 +170,7 @@ def process_task_ocr( force_track=force_track, layout_model=layout_model, preprocessing_mode=preprocess_mode_enum, - preprocessing_config=preprocess_config_obj, - table_detection_config=table_det_config_obj, - ocr_config=ocr_config_obj + preprocessing_config=preprocess_config_obj ) else: # Fall back to traditional processing (no force_track support) @@ -223,9 +181,7 @@ def process_task_ocr( output_dir=result_dir, layout_model=layout_model, preprocessing_mode=preprocess_mode_enum, - preprocessing_config=preprocess_config_obj, - table_detection_config=table_det_config_obj, - ocr_config=ocr_config_obj + preprocessing_config=preprocess_config_obj ) # Calculate processing time @@ -818,7 +774,7 @@ async def start_task( - **force_track**: Force specific processing track ('ocr' or 'direct') - **language**: OCR language code (default: 'ch') - **layout_model**: Layout detection model ('chinese', 'default', 'cdla') - - **table_detection**: Table detection config (enable_wired_table, enable_wireless_table, enable_region_detection) + - **preprocessing_mode**: Preprocessing mode ('auto', 'manual', 'disabled') """ try: # Parse processing options with defaults @@ -846,23 +802,6 @@ async def start_task( } logger.info(f"Preprocessing: mode={preprocessing_mode}, config={preprocessing_config}") - # Extract table detection options - table_detection_config = None - if options.table_detection: - table_detection_config = { - "enable_wired_table": options.table_detection.enable_wired_table, - "enable_wireless_table": options.table_detection.enable_wireless_table, - "enable_region_detection": options.table_detection.enable_region_detection - } - logger.info(f"Table detection: {table_detection_config}") - - # Extract OCR preset and config - ocr_preset = options.ocr_preset.value if options.ocr_preset else "datasheet" - ocr_config_dict = None - if options.ocr_config: - ocr_config_dict = options.ocr_config.model_dump() - logger.info(f"OCR preset: {ocr_preset}, config: {ocr_config_dict}") - # Get task details task = task_service.get_task_by_id( db=db, @@ -911,14 +850,11 @@ async def start_task( language=language, layout_model=layout_model, preprocessing_mode=preprocessing_mode, - preprocessing_config=preprocessing_config, - table_detection_config=table_detection_config, - ocr_preset=ocr_preset, - ocr_config=ocr_config_dict + preprocessing_config=preprocessing_config ) logger.info(f"Started OCR processing task {task_id} for user {current_user.email}") - logger.info(f"Options: dual_track={use_dual_track}, force_track={force_track}, lang={language}, layout_model={layout_model}, preprocessing={preprocessing_mode}, table_detection={table_detection_config}, ocr_preset={ocr_preset}") + logger.info(f"Options: dual_track={use_dual_track}, force_track={force_track}, lang={language}, layout_model={layout_model}, preprocessing={preprocessing_mode}") return task except HTTPException: diff --git a/backend/app/schemas/task.py b/backend/app/schemas/task.py index bd742fc..03ec9b4 100644 --- a/backend/app/schemas/task.py +++ b/backend/app/schemas/task.py @@ -65,139 +65,6 @@ class PreprocessingContrastEnum(str, Enum): DOCUMENT = "document" -class OCRPresetEnum(str, Enum): - """OCR processing preset for different document types. - - Presets provide optimized PP-Structure configurations for common document types: - - TEXT_HEAVY: Reports, articles, manuals (disable table recognition) - - DATASHEET: Technical datasheets, TDS (conservative table parsing) - - TABLE_HEAVY: Financial reports, spreadsheets (full table recognition) - - FORM: Applications, surveys (conservative table parsing) - - MIXED: General documents (classification only) - - CUSTOM: User-defined settings (use ocr_config) - """ - TEXT_HEAVY = "text_heavy" # Reports, articles, manuals - DATASHEET = "datasheet" # Technical datasheets, TDS - TABLE_HEAVY = "table_heavy" # Financial reports, spreadsheets - FORM = "form" # Applications, surveys - MIXED = "mixed" # General documents - CUSTOM = "custom" # User-defined settings - - -class TableParsingModeEnum(str, Enum): - """Table parsing mode controlling how aggressively tables are parsed. - - - FULL: Full table recognition with cell segmentation (aggressive) - - CONSERVATIVE: Disable wireless tables to prevent cell explosion - - CLASSIFICATION_ONLY: Only classify table regions, no cell segmentation - - DISABLED: Completely disable table recognition - """ - FULL = "full" - CONSERVATIVE = "conservative" - CLASSIFICATION_ONLY = "classification_only" - DISABLED = "disabled" - - -class OCRConfig(BaseModel): - """OCR processing configuration for PP-Structure. - - Allows fine-grained control over PP-Structure parameters. - Use with ocr_preset=CUSTOM or to override specific preset values. - """ - # Table Processing - table_parsing_mode: TableParsingModeEnum = Field( - default=TableParsingModeEnum.CONSERVATIVE, - description="Table parsing mode: full, conservative, classification_only, disabled" - ) - enable_wired_table: bool = Field( - default=True, - description="Enable wired (bordered) table detection" - ) - enable_wireless_table: bool = Field( - default=False, - description="Enable wireless (borderless) table detection. Can cause cell explosion." - ) - - # Layout Detection - layout_threshold: Optional[float] = Field( - default=None, - ge=0.0, - le=1.0, - description="Layout detection threshold. Higher = stricter. None uses default." - ) - layout_nms_threshold: Optional[float] = Field( - default=None, - ge=0.0, - le=1.0, - description="Layout NMS threshold. None uses default." - ) - - # Preprocessing - use_doc_orientation_classify: bool = Field( - default=True, - description="Auto-detect and correct document rotation" - ) - use_doc_unwarping: bool = Field( - default=False, - description="Correct document warping. Can cause distortion." - ) - use_textline_orientation: bool = Field( - default=True, - description="Detect textline orientation" - ) - - # Recognition Modules - enable_chart_recognition: bool = Field( - default=True, - description="Enable chart/diagram recognition" - ) - enable_formula_recognition: bool = Field( - default=True, - description="Enable math formula recognition" - ) - enable_seal_recognition: bool = Field( - default=False, - description="Enable seal/stamp recognition" - ) - enable_region_detection: bool = Field( - default=True, - description="Enable region detection for better structure" - ) - - -# Preset configurations mapping -OCR_PRESET_CONFIGS = { - OCRPresetEnum.TEXT_HEAVY: OCRConfig( - table_parsing_mode=TableParsingModeEnum.DISABLED, - enable_wired_table=False, - enable_wireless_table=False, - enable_chart_recognition=False, - enable_formula_recognition=False, - ), - OCRPresetEnum.DATASHEET: OCRConfig( - table_parsing_mode=TableParsingModeEnum.CONSERVATIVE, - enable_wired_table=True, - enable_wireless_table=False, - ), - OCRPresetEnum.TABLE_HEAVY: OCRConfig( - table_parsing_mode=TableParsingModeEnum.FULL, - enable_wired_table=True, - enable_wireless_table=True, - ), - OCRPresetEnum.FORM: OCRConfig( - table_parsing_mode=TableParsingModeEnum.CONSERVATIVE, - enable_wired_table=True, - enable_wireless_table=False, - ), - OCRPresetEnum.MIXED: OCRConfig( - table_parsing_mode=TableParsingModeEnum.CLASSIFICATION_ONLY, - enable_wired_table=True, - enable_wireless_table=False, - ), - # CUSTOM uses user-provided config directly -} - - class PreprocessingConfig(BaseModel): """Preprocessing configuration for layout detection enhancement. @@ -235,31 +102,6 @@ class PreprocessingConfig(BaseModel): ) -class TableDetectionConfig(BaseModel): - """Table detection configuration for PP-StructureV3. - - Controls which table detection modes to enable. PP-StructureV3 uses specialized - models for different table types: - - Wired (bordered): Tables with visible cell borders/grid lines - - Wireless (borderless): Tables without visible borders, relying on alignment - - Region detection: Detect table-like regions for better cell structure - - Multiple options can be enabled simultaneously for comprehensive detection. - """ - enable_wired_table: bool = Field( - default=True, - description="Enable wired (bordered) table detection. Best for tables with visible grid lines." - ) - enable_wireless_table: bool = Field( - default=True, - description="Enable wireless (borderless) table detection. Best for tables without visible borders." - ) - enable_region_detection: bool = Field( - default=True, - description="Enable region detection for better table structure inference." - ) - - class ImageQualityMetrics(BaseModel): """Image quality metrics from auto-analysis.""" contrast: float = Field(..., description="Contrast level (std dev of grayscale)") @@ -456,23 +298,6 @@ class ProcessingOptions(BaseModel): description="Manual preprocessing config (only used when preprocessing_mode='manual')" ) - # Table detection configuration (OCR track only) - table_detection: Optional[TableDetectionConfig] = Field( - None, - description="Table detection config. If None, all table detection modes are enabled." - ) - - # OCR Processing Preset (OCR track only) - # Use presets for optimized configurations or CUSTOM with ocr_config for fine-tuning - ocr_preset: Optional[OCRPresetEnum] = Field( - default=OCRPresetEnum.DATASHEET, - description="OCR processing preset: text_heavy, datasheet, table_heavy, form, mixed, custom" - ) - ocr_config: Optional[OCRConfig] = Field( - None, - description="Custom OCR config. Used when ocr_preset=custom or to override preset values." - ) - class AnalyzeRequest(BaseModel): """Document analysis request""" diff --git a/backend/app/services/cell_validation_engine.py b/backend/app/services/cell_validation_engine.py deleted file mode 100644 index a6cfb12..0000000 --- a/backend/app/services/cell_validation_engine.py +++ /dev/null @@ -1,583 +0,0 @@ -""" -Cell Validation Engine - -Validates PP-StructureV3 table detections using metric-based heuristics -to filter over-detected cells and reclassify invalid tables as TEXT elements. - -Metrics used: -- Cell density: cells per 10,000 px² (normal: 0.4-1.0, over-detected: 6+) -- Average cell area: px² per cell (normal: 10,000-25,000, over-detected: ~1,600) -- Cell height: table_height / cell_count (minimum: 10px for readable text) -""" - -import logging -from dataclasses import dataclass -from typing import List, Dict, Any, Optional, Tuple -from html.parser import HTMLParser -import re - -logger = logging.getLogger(__name__) - - -@dataclass -class CellValidationConfig: - """Configuration for cell validation thresholds.""" - max_cell_density: float = 3.0 # cells per 10,000 px² - min_avg_cell_area: float = 3000.0 # px² per cell - min_cell_height: float = 10.0 # px per cell row - enabled: bool = True - - -@dataclass -class TableValidationResult: - """Result of table validation.""" - is_valid: bool - table_element: Dict[str, Any] - reason: Optional[str] = None - metrics: Optional[Dict[str, float]] = None - - -class CellValidationEngine: - """ - Validates table elements from PP-StructureV3 output. - - Over-detected tables are identified by abnormal metrics and - reclassified as TEXT elements while preserving content. - """ - - def __init__(self, config: Optional[CellValidationConfig] = None): - self.config = config or CellValidationConfig() - - def calculate_table_metrics( - self, - bbox: List[float], - cell_boxes: List[List[float]] - ) -> Dict[str, float]: - """ - Calculate validation metrics for a table. - - Args: - bbox: Table bounding box [x0, y0, x1, y1] - cell_boxes: List of cell bounding boxes - - Returns: - Dictionary with calculated metrics - """ - if len(bbox) < 4: - return {"cell_count": 0, "cell_density": 0, "avg_cell_area": 0, "avg_cell_height": 0} - - cell_count = len(cell_boxes) - if cell_count == 0: - return {"cell_count": 0, "cell_density": 0, "avg_cell_area": 0, "avg_cell_height": 0} - - # Calculate table dimensions - table_width = bbox[2] - bbox[0] - table_height = bbox[3] - bbox[1] - table_area = table_width * table_height - - if table_area <= 0: - return {"cell_count": cell_count, "cell_density": 0, "avg_cell_area": 0, "avg_cell_height": 0} - - # Cell density: cells per 10,000 px² - cell_density = (cell_count / table_area) * 10000 - - # Average cell area - avg_cell_area = table_area / cell_count - - # Average cell height (table height / cell count) - avg_cell_height = table_height / cell_count - - return { - "cell_count": cell_count, - "table_width": table_width, - "table_height": table_height, - "table_area": table_area, - "cell_density": cell_density, - "avg_cell_area": avg_cell_area, - "avg_cell_height": avg_cell_height - } - - def validate_table( - self, - element: Dict[str, Any] - ) -> TableValidationResult: - """ - Validate a single table element. - - Args: - element: Table element from PP-StructureV3 output - - Returns: - TableValidationResult with validation status and metrics - """ - if not self.config.enabled: - return TableValidationResult(is_valid=True, table_element=element) - - # Extract bbox and cell_boxes - bbox = element.get("bbox", []) - cell_boxes = element.get("cell_boxes", []) - - # Tables without cells pass validation (structure-only tables) - if not cell_boxes: - return TableValidationResult( - is_valid=True, - table_element=element, - reason="No cells to validate" - ) - - # Calculate metrics - metrics = self.calculate_table_metrics(bbox, cell_boxes) - - # Check cell density - if metrics["cell_density"] > self.config.max_cell_density: - return TableValidationResult( - is_valid=False, - table_element=element, - reason=f"Cell density {metrics['cell_density']:.2f} exceeds threshold {self.config.max_cell_density}", - metrics=metrics - ) - - # Check average cell area - if metrics["avg_cell_area"] < self.config.min_avg_cell_area: - return TableValidationResult( - is_valid=False, - table_element=element, - reason=f"Avg cell area {metrics['avg_cell_area']:.0f}px² below threshold {self.config.min_avg_cell_area}px²", - metrics=metrics - ) - - # Check cell height - if metrics["avg_cell_height"] < self.config.min_cell_height: - return TableValidationResult( - is_valid=False, - table_element=element, - reason=f"Avg cell height {metrics['avg_cell_height']:.1f}px below threshold {self.config.min_cell_height}px", - metrics=metrics - ) - - # Content-based validation: check if content looks like prose vs tabular data - content_check = self._validate_table_content(element) - if not content_check["is_tabular"]: - return TableValidationResult( - is_valid=False, - table_element=element, - reason=content_check["reason"], - metrics=metrics - ) - - return TableValidationResult( - is_valid=True, - table_element=element, - metrics=metrics - ) - - def _validate_table_content(self, element: Dict[str, Any]) -> Dict[str, Any]: - """ - Validate table content to detect false positive tables. - - Checks: - 1. Sparsity: text coverage ratio (text area / table area) - 2. Header: does table have proper header structure - 3. Key-Value: for 2-col tables, is it a key-value list or random layout - 4. Prose: are cells containing long prose text - - Returns: - Dict with is_tabular (bool) and reason (str) - """ - html_content = element.get("content", "") - bbox = element.get("bbox", []) - cell_boxes = element.get("cell_boxes", []) - - if not html_content or ' 3: - # Large table without header is suspicious - logger.debug(f"Table has no header structure with {num_rows} rows") - - # === Check 3: Key-Value pattern for 2-column tables === - if num_cols == 2: - kv_result = self._check_key_value_pattern(row_data) - if kv_result["is_kv_list"] and kv_result["confidence"] > 0.7: - # High confidence key-value list - keep as table but log - logger.debug(f"Table identified as key-value list (conf={kv_result['confidence']:.2f})") - elif not kv_result["is_kv_list"] and kv_result["is_random_layout"]: - # Random 2-column layout, not a real table - return { - "is_tabular": False, - "reason": f"random_two_column_layout (not key-value)" - } - - # === Check 4: Prose content === - long_cells = [c for c in all_cells if c["length"] > 80] - prose_ratio = len(long_cells) / len(all_cells) if all_cells else 0 - if prose_ratio > 0.3: - return { - "is_tabular": False, - "reason": f"prose_content ({len(long_cells)}/{len(all_cells)} cells > 80 chars)" - } - - # === Check 5: Section header as table === - if num_rows <= 2 and num_cols <= 2: - first_row = row_data[0] if row_data else [] - if len(first_row) == 1: - text = first_row[0]["text"] - if text.isupper() and len(text) < 50: - return { - "is_tabular": False, - "reason": f"section_header_only ({text[:30]})" - } - - return {"is_tabular": True, "reason": "content_valid"} - - except Exception as e: - logger.warning(f"Content validation failed: {e}") - return {"is_tabular": True, "reason": f"validation_error: {e}"} - - def _check_sparsity( - self, - bbox: List[float], - cell_boxes: List[List[float]], - all_cells: List[Dict] - ) -> Dict[str, Any]: - """ - Check text coverage ratio (sparsity). - - Two-column layouts have large empty gaps in the middle. - Real tables have more uniform cell distribution. - """ - if len(bbox) < 4: - return {"is_valid": True, "reason": "no_bbox"} - - table_width = bbox[2] - bbox[0] - table_height = bbox[3] - bbox[1] - table_area = table_width * table_height - - if table_area <= 0: - return {"is_valid": True, "reason": "invalid_area"} - - # Calculate text area from cell_boxes - if cell_boxes: - text_area = 0 - for cb in cell_boxes: - if len(cb) >= 4: - w = abs(cb[2] - cb[0]) - h = abs(cb[3] - cb[1]) - text_area += w * h - coverage = text_area / table_area - else: - # Estimate from cell content length - total_chars = sum(c["length"] for c in all_cells) - # Rough estimate: 1 char ≈ 8x12 pixels = 96 px² - estimated_text_area = total_chars * 96 - coverage = min(estimated_text_area / table_area, 1.0) - - # Very sparse table (< 15% coverage) is suspicious - if coverage < 0.15: - return { - "is_valid": False, - "reason": f"sparse_content (coverage={coverage:.1%})" - } - - return {"is_valid": True, "coverage": coverage} - - def _check_header_structure( - self, - row_data: List[List[Dict]], - num_cols: int - ) -> Dict[str, Any]: - """ - Check if table has proper header structure. - - Real tables usually have: - - First row with elements - - Or first row with different content pattern (labels vs values) - """ - if not row_data: - return {"has_header": False} - - first_row = row_data[0] - - # Check for elements - th_count = sum(1 for c in first_row if c.get("is_header", False)) - if th_count > 0 and th_count >= len(first_row) * 0.5: - return {"has_header": True, "type": "th_elements"} - - # Check for header-like content (short, distinct from body) - if len(row_data) > 1: - first_row_avg_len = sum(c["length"] for c in first_row) / len(first_row) if first_row else 0 - body_rows = row_data[1:] - body_cells = [c for row in body_rows for c in row] - body_avg_len = sum(c["length"] for c in body_cells) / len(body_cells) if body_cells else 0 - - # Header row should be shorter (labels) than body (data) - if first_row_avg_len < body_avg_len * 0.7: - return {"has_header": True, "type": "short_labels"} - - return {"has_header": False} - - def _check_key_value_pattern( - self, - row_data: List[List[Dict]] - ) -> Dict[str, Any]: - """ - For 2-column tables, check if it's a key-value list. - - Key-value characteristics: - - Left column: short labels (< 30 chars) - - Right column: values (can be longer) - - Consistent pattern across rows - - Random layout characteristics: - - Both columns have similar length distribution - - No clear label-value relationship - """ - if not row_data: - return {"is_kv_list": False, "is_random_layout": False, "confidence": 0} - - left_lengths = [] - right_lengths = [] - kv_rows = 0 - total_rows = 0 - - for row in row_data: - if len(row) != 2: - continue - total_rows += 1 - left = row[0] - right = row[1] - left_lengths.append(left["length"]) - right_lengths.append(right["length"]) - - # Key-value pattern: left is short label, right is value - if left["length"] < 40 and left["length"] < right["length"] * 2: - kv_rows += 1 - - if total_rows == 0: - return {"is_kv_list": False, "is_random_layout": False, "confidence": 0} - - kv_ratio = kv_rows / total_rows - avg_left = sum(left_lengths) / len(left_lengths) if left_lengths else 0 - avg_right = sum(right_lengths) / len(right_lengths) if right_lengths else 0 - - # High KV ratio and left column is shorter = key-value list - if kv_ratio > 0.6 and avg_left < avg_right: - return { - "is_kv_list": True, - "is_random_layout": False, - "confidence": kv_ratio, - "avg_left": avg_left, - "avg_right": avg_right - } - - # Similar lengths on both sides = random layout - if avg_left > 0 and 0.5 < avg_right / avg_left < 2.0: - # Both columns have similar content length - return { - "is_kv_list": False, - "is_random_layout": True, - "confidence": 1 - kv_ratio, - "avg_left": avg_left, - "avg_right": avg_right - } - - return { - "is_kv_list": False, - "is_random_layout": False, - "confidence": 0, - "avg_left": avg_left, - "avg_right": avg_right - } - - def extract_text_from_table_html(self, html_content: str) -> str: - """ - Extract plain text from table HTML content. - - Args: - html_content: HTML string containing table structure - - Returns: - Plain text extracted from table cells - """ - if not html_content: - return "" - - try: - class TableTextExtractor(HTMLParser): - def __init__(self): - super().__init__() - self.text_parts = [] - self.in_cell = False - - def handle_starttag(self, tag, attrs): - if tag in ('td', 'th'): - self.in_cell = True - - def handle_endtag(self, tag): - if tag in ('td', 'th'): - self.in_cell = False - - def handle_data(self, data): - if self.in_cell: - stripped = data.strip() - if stripped: - self.text_parts.append(stripped) - - parser = TableTextExtractor() - parser.feed(html_content) - return ' '.join(parser.text_parts) - except Exception as e: - logger.warning(f"Failed to parse table HTML: {e}") - # Fallback: strip HTML tags with regex - text = re.sub(r'<[^>]+>', ' ', html_content) - text = re.sub(r'\s+', ' ', text).strip() - return text - - def reclassify_as_text(self, element: Dict[str, Any]) -> Dict[str, Any]: - """ - Convert an over-detected table element to a TEXT element. - - Args: - element: Table element to reclassify - - Returns: - New TEXT element with preserved content - """ - # Extract text content from HTML - html_content = element.get("content", "") - text_content = self.extract_text_from_table_html(html_content) - - # Create new TEXT element - text_element = { - "element_id": element.get("element_id", ""), - "type": "text", - "original_type": "table_reclassified", # Mark as reclassified - "content": text_content, - "page": element.get("page", 0), - "bbox": element.get("bbox", []), - "index": element.get("index", 0), - "confidence": element.get("confidence", 1.0), - "reclassified_from": "table", - "reclassification_reason": "over_detection" - } - - return text_element - - def validate_and_filter_elements( - self, - elements: List[Dict[str, Any]] - ) -> Tuple[List[Dict[str, Any]], Dict[str, Any]]: - """ - Validate all elements and filter/reclassify over-detected tables. - - Args: - elements: List of elements from PP-StructureV3 output - - Returns: - Tuple of (filtered_elements, statistics) - """ - filtered_elements = [] - stats = { - "total_tables": 0, - "valid_tables": 0, - "reclassified_tables": 0, - "reclassification_details": [] - } - - for element in elements: - if element.get("type") != "table": - # Non-table elements pass through unchanged - filtered_elements.append(element) - continue - - stats["total_tables"] += 1 - - # Validate table - result = self.validate_table(element) - - if result.is_valid: - stats["valid_tables"] += 1 - filtered_elements.append(element) - else: - # Reclassify as TEXT - stats["reclassified_tables"] += 1 - text_element = self.reclassify_as_text(element) - filtered_elements.append(text_element) - - stats["reclassification_details"].append({ - "element_id": element.get("element_id"), - "reason": result.reason, - "metrics": result.metrics - }) - - logger.info( - f"Reclassified table {element.get('element_id')} as TEXT: {result.reason}" - ) - - # Re-sort by reading order (y0 then x0) - filtered_elements = self._sort_by_reading_order(filtered_elements) - - return filtered_elements, stats - - def _sort_by_reading_order( - self, - elements: List[Dict[str, Any]] - ) -> List[Dict[str, Any]]: - """Sort elements by reading order (top-to-bottom, left-to-right).""" - def sort_key(elem): - bbox = elem.get("bbox", [0, 0, 0, 0]) - if isinstance(bbox, dict): - y0 = bbox.get("y0", 0) - x0 = bbox.get("x0", 0) - elif isinstance(bbox, list) and len(bbox) >= 2: - x0, y0 = bbox[0], bbox[1] - else: - y0, x0 = 0, 0 - return (y0, x0) - - return sorted(elements, key=sort_key) diff --git a/backend/app/services/gap_filling_service.py b/backend/app/services/gap_filling_service.py index b1ecb27..6429c4c 100644 --- a/backend/app/services/gap_filling_service.py +++ b/backend/app/services/gap_filling_service.py @@ -16,6 +16,7 @@ from app.models.unified_document import ( DocumentElement, BoundingBox, ElementType, Dimensions ) from app.core.config import settings +from app.utils.bbox_utils import normalize_bbox as _normalize_bbox logger = logging.getLogger(__name__) @@ -49,32 +50,9 @@ class TextRegion: @property def normalized_bbox(self) -> Tuple[float, float, float, float]: - """Get normalized bbox as (x0, y0, x1, y1).""" - if not self.bbox: - return (0, 0, 0, 0) - - # Check if bbox is nested list format [[x1,y1], [x2,y2], [x3,y3], [x4,y4]] - # This is common PaddleOCR polygon format - if len(self.bbox) >= 1 and isinstance(self.bbox[0], (list, tuple)): - # Nested format: extract all x and y coordinates - xs = [pt[0] for pt in self.bbox if len(pt) >= 2] - ys = [pt[1] for pt in self.bbox if len(pt) >= 2] - if xs and ys: - return (min(xs), min(ys), max(xs), max(ys)) - return (0, 0, 0, 0) - - # Flat format - if len(self.bbox) == 4: - # Simple [x0, y0, x1, y1] format - return (float(self.bbox[0]), float(self.bbox[1]), - float(self.bbox[2]), float(self.bbox[3])) - elif len(self.bbox) >= 8: - # Flat polygon format: [x1, y1, x2, y2, x3, y3, x4, y4] - xs = [self.bbox[i] for i in range(0, len(self.bbox), 2)] - ys = [self.bbox[i] for i in range(1, len(self.bbox), 2)] - return (min(xs), min(ys), max(xs), max(ys)) - - return (0, 0, 0, 0) + """Get normalized bbox as (x0, y0, x1, y1). Uses shared bbox utility.""" + result = _normalize_bbox(self.bbox) + return result if result else (0, 0, 0, 0) @property def center(self) -> Tuple[float, float]: @@ -171,10 +149,6 @@ class GapFillingService: settings, 'gap_filling_enabled', True ) - # Legacy compatibility - self.iou_threshold = getattr(settings, 'gap_filling_iou_threshold', 0.15) - self.dedup_iou_threshold = getattr(settings, 'gap_filling_dedup_iou_threshold', 0.5) - def should_activate( self, raw_ocr_regions: List[TextRegion], diff --git a/backend/app/services/ocr_service.py b/backend/app/services/ocr_service.py index 558ecdb..3d603c0 100644 --- a/backend/app/services/ocr_service.py +++ b/backend/app/services/ocr_service.py @@ -10,6 +10,7 @@ from typing import Any, Dict, List, Optional, Tuple, Union from datetime import datetime import uuid import gc # For garbage collection +import warnings # For suppressing PaddleX deprecation warnings from paddleocr import PaddleOCR, PPStructureV3 from PIL import Image @@ -34,7 +35,21 @@ from app.services.layout_preprocessing_service import ( get_layout_preprocessing_service, LayoutPreprocessingService, ) -from app.schemas.task import PreprocessingModeEnum, PreprocessingConfig, TableDetectionConfig +from app.schemas.task import PreprocessingModeEnum, PreprocessingConfig +from dataclasses import dataclass + + +@dataclass +class TableDetectionConfig: + """Internal table detection configuration for OCR service. + + Note: This was previously in app.schemas.task but is now internal to OCR service + as frontend no longer configures these options. + """ + enable_wired_table: bool = True + enable_wireless_table: bool = True + enable_region_detection: bool = True + # Import dual-track components try: @@ -798,7 +813,12 @@ class OCRService: if textline_ori_model: pp_kwargs['textline_orientation_model_name'] = textline_ori_model - self.structure_engine = PPStructureV3(**pp_kwargs) + # Suppress DeprecationWarning during PPStructureV3 initialization + # Workaround for PaddleX bug: it incorrectly treats Python's datetime.utcnow() + # deprecation warning as a model loading error in PP-Chart2Table + with warnings.catch_warnings(): + warnings.filterwarnings('ignore', category=DeprecationWarning) + self.structure_engine = PPStructureV3(**pp_kwargs) # Track model loading for cache management self._model_last_used['structure'] = datetime.now() @@ -881,7 +901,10 @@ class OCRService: if settings.textline_orientation_model_name: cpu_kwargs['textline_orientation_model_name'] = settings.textline_orientation_model_name - self.structure_engine = PPStructureV3(**cpu_kwargs) + # Suppress DeprecationWarning during PPStructureV3 initialization (CPU fallback) + with warnings.catch_warnings(): + warnings.filterwarnings('ignore', category=DeprecationWarning) + self.structure_engine = PPStructureV3(**cpu_kwargs) self._current_layout_model = layout_model # Track current model for recreation check # Track table detection config for recreation check if table_detection_config: @@ -1429,6 +1452,22 @@ class OCRService: raw_ocr_regions=text_regions # For table content rebuilding ) + # Get detected rotation from layout analysis (default: "0" = no rotation) + detected_rotation = "0" + if layout_data: + detected_rotation = layout_data.get('detected_rotation', '0') + + # Adjust page dimensions based on detected rotation + # When rotation is 90° or 270°, the page orientation changes (portrait <-> landscape) + # PP-StructureV3 returns coordinates based on the rotated image, so we need to swap dimensions + if detected_rotation in ['90', '270']: + original_width, original_height = ocr_width, ocr_height + ocr_width, ocr_height = original_height, original_width + logger.info( + f"Page dimensions adjusted for {detected_rotation}° rotation: " + f"{original_width}x{original_height} -> {ocr_width}x{ocr_height}" + ) + # Generate Markdown markdown_content = self.generate_markdown(text_regions, layout_data) @@ -1450,7 +1489,8 @@ class OCRService: 'ocr_dimensions': { 'width': ocr_width, 'height': ocr_height - } + }, + 'detected_rotation': detected_rotation # Document orientation: "0", "90", "180", "270" } # If layout data is enhanced, add enhanced results for converter @@ -1705,7 +1745,8 @@ class OCRService: 'total_elements': result['total_elements'], 'reading_order': result['reading_order'], 'element_types': result.get('element_types', {}), - 'enhanced': True + 'enhanced': True, + 'detected_rotation': result.get('detected_rotation', '0') # Document orientation } # Extract images metadata diff --git a/backend/app/services/pdf_generator.py b/backend/app/services/pdf_generator.py deleted file mode 100644 index 68e830c..0000000 --- a/backend/app/services/pdf_generator.py +++ /dev/null @@ -1,507 +0,0 @@ -""" -Tool_OCR - PDF Generator Service -Converts Markdown to layout-preserved PDFs using Pandoc + WeasyPrint -""" - -import logging -import subprocess -from pathlib import Path -from typing import Optional, Dict -from datetime import datetime - -from weasyprint import HTML, CSS -from markdown import markdown - -from app.core.config import settings - - -logger = logging.getLogger(__name__) - - -class PDFGenerationError(Exception): - """Exception raised when PDF generation fails""" - pass - - -class PDFGenerator: - """ - PDF generation service with layout preservation - - Supports two generation methods: - 1. Pandoc (preferred): Markdown → HTML → PDF via pandoc command - 2. WeasyPrint (fallback): Direct Python-based HTML → PDF conversion - """ - - # Default CSS template for layout preservation - DEFAULT_CSS = """ - @page { - size: A4; - margin: 2cm; - } - - body { - font-family: "Noto Sans CJK SC", "Noto Sans CJK TC", "Microsoft YaHei", "SimSun", sans-serif; - font-size: 11pt; - line-height: 1.6; - color: #333; - } - - h1 { - font-size: 24pt; - font-weight: bold; - margin-top: 0; - margin-bottom: 12pt; - color: #000; - page-break-after: avoid; - } - - h2 { - font-size: 18pt; - font-weight: bold; - margin-top: 18pt; - margin-bottom: 10pt; - color: #000; - page-break-after: avoid; - } - - h3 { - font-size: 14pt; - font-weight: bold; - margin-top: 14pt; - margin-bottom: 8pt; - color: #000; - page-break-after: avoid; - } - - p { - margin: 0 0 10pt 0; - text-align: justify; - } - - table { - width: 100%; - border-collapse: collapse; - margin: 12pt 0; - page-break-inside: avoid; - } - - table th { - background-color: #f0f0f0; - border: 1px solid #ccc; - padding: 8pt; - text-align: left; - font-weight: bold; - } - - table td { - border: 1px solid #ccc; - padding: 8pt; - text-align: left; - } - - code { - font-family: "Courier New", monospace; - font-size: 10pt; - background-color: #f5f5f5; - padding: 2pt 4pt; - border-radius: 3px; - } - - pre { - background-color: #f5f5f5; - border: 1px solid #ddd; - border-radius: 5px; - padding: 10pt; - overflow-x: auto; - page-break-inside: avoid; - } - - pre code { - background-color: transparent; - padding: 0; - } - - img { - max-width: 100%; - height: auto; - display: block; - margin: 12pt auto; - page-break-inside: avoid; - } - - blockquote { - border-left: 4px solid #ddd; - padding-left: 12pt; - margin: 12pt 0; - color: #666; - font-style: italic; - } - - ul, ol { - margin: 10pt 0; - padding-left: 20pt; - } - - li { - margin: 5pt 0; - } - - hr { - border: none; - border-top: 1px solid #ccc; - margin: 20pt 0; - } - - .page-break { - page-break-after: always; - } - """ - - # Academic paper template - ACADEMIC_CSS = """ - @page { - size: A4; - margin: 2.5cm; - } - - body { - font-family: "Times New Roman", "Noto Serif CJK SC", serif; - font-size: 12pt; - line-height: 1.8; - color: #000; - } - - h1 { - font-size: 20pt; - text-align: center; - margin-bottom: 24pt; - page-break-after: avoid; - } - - h2 { - font-size: 16pt; - margin-top: 20pt; - margin-bottom: 12pt; - page-break-after: avoid; - } - - h3 { - font-size: 14pt; - margin-top: 16pt; - margin-bottom: 10pt; - page-break-after: avoid; - } - - p { - text-indent: 2em; - text-align: justify; - margin: 0 0 12pt 0; - } - - table { - width: 100%; - border-collapse: collapse; - margin: 16pt auto; - page-break-inside: avoid; - } - - table caption { - font-weight: bold; - margin-bottom: 8pt; - } - """ - - # Business report template - BUSINESS_CSS = """ - @page { - size: A4; - margin: 2cm 2.5cm; - } - - body { - font-family: "Arial", "Noto Sans CJK SC", sans-serif; - font-size: 11pt; - line-height: 1.5; - color: #333; - } - - h1 { - font-size: 22pt; - color: #0066cc; - border-bottom: 3px solid #0066cc; - padding-bottom: 8pt; - margin-bottom: 20pt; - page-break-after: avoid; - } - - h2 { - font-size: 16pt; - color: #0066cc; - margin-top: 20pt; - margin-bottom: 12pt; - page-break-after: avoid; - } - - table { - width: 100%; - border-collapse: collapse; - margin: 16pt 0; - } - - table th { - background-color: #0066cc; - color: white; - padding: 10pt; - font-weight: bold; - } - - table td { - border: 1px solid #ddd; - padding: 10pt; - } - - table tr:nth-child(even) { - background-color: #f9f9f9; - } - """ - - def __init__(self): - """Initialize PDF generator""" - self.css_templates = { - "default": self.DEFAULT_CSS, - "academic": self.ACADEMIC_CSS, - "business": self.BUSINESS_CSS, - } - - def check_pandoc_available(self) -> bool: - """ - Check if Pandoc is installed and available - - Returns: - bool: True if pandoc is available, False otherwise - """ - try: - result = subprocess.run( - ["pandoc", "--version"], - capture_output=True, - text=True, - timeout=5 - ) - return result.returncode == 0 - except (subprocess.TimeoutExpired, FileNotFoundError): - logger.warning("Pandoc not found or timed out") - return False - - def generate_pdf_pandoc( - self, - markdown_path: Path, - output_path: Path, - css_template: str = "default", - metadata: Optional[Dict] = None - ) -> Path: - """ - Generate PDF using Pandoc (preferred method) - - Args: - markdown_path: Path to input Markdown file - output_path: Path to output PDF file - css_template: CSS template name or custom CSS string - metadata: Optional metadata dict (title, author, date) - - Returns: - Path: Path to generated PDF file - - Raises: - PDFGenerationError: If PDF generation fails - """ - try: - # Create temporary CSS file - css_content = self.css_templates.get(css_template, css_template) - css_file = output_path.parent / f"temp_{datetime.now().timestamp()}.css" - css_file.write_text(css_content, encoding="utf-8") - - # Build pandoc command - pandoc_cmd = [ - "pandoc", - str(markdown_path), - "-o", str(output_path), - "--pdf-engine=weasyprint", - "--css", str(css_file), - "--standalone", - "--from=markdown+tables+fenced_code_blocks+footnotes", - ] - - # Add metadata if provided - if metadata: - if metadata.get("title"): - pandoc_cmd.extend(["--metadata", f"title={metadata['title']}"]) - if metadata.get("author"): - pandoc_cmd.extend(["--metadata", f"author={metadata['author']}"]) - if metadata.get("date"): - pandoc_cmd.extend(["--metadata", f"date={metadata['date']}"]) - - # Execute pandoc - logger.info(f"Executing pandoc: {' '.join(pandoc_cmd)}") - result = subprocess.run( - pandoc_cmd, - capture_output=True, - text=True, - timeout=60 # 60 second timeout for large documents - ) - - # Clean up temporary CSS file - css_file.unlink(missing_ok=True) - - if result.returncode != 0: - error_msg = f"Pandoc failed: {result.stderr}" - logger.error(error_msg) - raise PDFGenerationError(error_msg) - - if not output_path.exists(): - raise PDFGenerationError(f"PDF file not created: {output_path}") - - logger.info(f"PDF generated successfully via Pandoc: {output_path}") - return output_path - - except subprocess.TimeoutExpired: - css_file.unlink(missing_ok=True) - raise PDFGenerationError("Pandoc execution timed out") - except Exception as e: - css_file.unlink(missing_ok=True) - raise PDFGenerationError(f"Pandoc PDF generation failed: {str(e)}") - - def generate_pdf_weasyprint( - self, - markdown_path: Path, - output_path: Path, - css_template: str = "default", - metadata: Optional[Dict] = None - ) -> Path: - """ - Generate PDF using WeasyPrint directly (fallback method) - - Args: - markdown_path: Path to input Markdown file - output_path: Path to output PDF file - css_template: CSS template name or custom CSS string - metadata: Optional metadata dict (title, author, date) - - Returns: - Path: Path to generated PDF file - - Raises: - PDFGenerationError: If PDF generation fails - """ - try: - # Read Markdown content - markdown_content = markdown_path.read_text(encoding="utf-8") - - # Convert Markdown to HTML - html_content = markdown( - markdown_content, - extensions=[ - 'tables', - 'fenced_code', - 'codehilite', - 'nl2br', - 'sane_lists', - ] - ) - - # Wrap HTML with proper structure - title = metadata.get("title", markdown_path.stem) if metadata else markdown_path.stem - full_html = f""" - - - - - {title} - - -{html_content} - - -""" - - # Get CSS content - css_content = self.css_templates.get(css_template, css_template) - - # Generate PDF - logger.info(f"Generating PDF via WeasyPrint: {output_path}") - html = HTML(string=full_html, base_url=str(markdown_path.parent)) - css = CSS(string=css_content) - html.write_pdf(str(output_path), stylesheets=[css]) - - if not output_path.exists(): - raise PDFGenerationError(f"PDF file not created: {output_path}") - - logger.info(f"PDF generated successfully via WeasyPrint: {output_path}") - return output_path - - except Exception as e: - raise PDFGenerationError(f"WeasyPrint PDF generation failed: {str(e)}") - - def generate_pdf( - self, - markdown_path: Path, - output_path: Path, - css_template: str = "default", - metadata: Optional[Dict] = None, - prefer_pandoc: bool = True - ) -> Path: - """ - Generate PDF from Markdown with automatic fallback - - Args: - markdown_path: Path to input Markdown file - output_path: Path to output PDF file - css_template: CSS template name ("default", "academic", "business") or custom CSS - metadata: Optional metadata dict (title, author, date) - prefer_pandoc: Use Pandoc if available, fallback to WeasyPrint - - Returns: - Path: Path to generated PDF file - - Raises: - PDFGenerationError: If both methods fail - """ - if not markdown_path.exists(): - raise PDFGenerationError(f"Markdown file not found: {markdown_path}") - - # Ensure output directory exists - output_path.parent.mkdir(parents=True, exist_ok=True) - - # Try Pandoc first if preferred and available - if prefer_pandoc and self.check_pandoc_available(): - try: - return self.generate_pdf_pandoc(markdown_path, output_path, css_template, metadata) - except PDFGenerationError as e: - logger.warning(f"Pandoc failed, falling back to WeasyPrint: {e}") - # Fall through to WeasyPrint - - # Use WeasyPrint (fallback or direct) - return self.generate_pdf_weasyprint(markdown_path, output_path, css_template, metadata) - - def get_available_templates(self) -> Dict[str, str]: - """ - Get list of available CSS templates - - Returns: - Dict mapping template names to descriptions - """ - return { - "default": "通用排版模板，適合大多數文檔", - "academic": "學術論文模板，適合研究報告", - "business": "商業報告模板，適合企業文檔", - } - - def save_custom_template(self, template_name: str, css_content: str) -> None: - """ - Save a custom CSS template - - Args: - template_name: Template name - css_content: CSS content - """ - self.css_templates[template_name] = css_content - logger.info(f"Custom CSS template saved: {template_name}") diff --git a/backend/app/services/pdf_generator_service.py b/backend/app/services/pdf_generator_service.py index 1fd7d23..f91e548 100644 --- a/backend/app/services/pdf_generator_service.py +++ b/backend/app/services/pdf_generator_service.py @@ -25,6 +25,7 @@ from PIL import Image from html.parser import HTMLParser from app.core.config import settings +from app.utils.bbox_utils import normalize_bbox # Import table column corrector for column alignment fix try: @@ -1258,8 +1259,44 @@ class PDFGeneratorService: else: logger.warning(f"Image file not found: {saved_path}") + # Also check for embedded images in table elements + # These are images detected inside table regions by PP-Structure + elif elem_type == 'table': + metadata = elem.metadata if hasattr(elem, 'metadata') else elem.get('metadata', {}) + embedded_images = metadata.get('embedded_images', []) if metadata else [] + for emb_img in embedded_images: + emb_bbox = emb_img.get('bbox', []) + if emb_bbox and len(emb_bbox) >= 4: + ex0, ey0, ex1, ey1 = emb_bbox[0], emb_bbox[1], emb_bbox[2], emb_bbox[3] + exclusion_zones.append((ex0, ey0, ex1, ey1)) + + # Also render the embedded image + saved_path = emb_img.get('saved_path', '') + if saved_path: + image_path = result_dir / saved_path + if not image_path.exists(): + image_path = result_dir / Path(saved_path).name + if image_path.exists(): + try: + pdf_x = ex0 + pdf_y = current_height - ey1 + img_width = ex1 - ex0 + img_height = ey1 - ey0 + pdf_canvas.drawImage( + str(image_path), + pdf_x, pdf_y, + width=img_width, + height=img_height, + preserveAspectRatio=True, + mask='auto' + ) + image_elements_rendered += 1 + logger.debug(f"Rendered embedded image: {saved_path} at ({pdf_x:.1f}, {pdf_y:.1f})") + except Exception as e: + logger.warning(f"Failed to render embedded image {saved_path}: {e}") + if image_elements_rendered > 0: - logger.info(f"Rendered {image_elements_rendered} image elements (figures/charts/seals/formulas)") + logger.info(f"Rendered {image_elements_rendered} image elements (figures/charts/seals/formulas/embedded)") if exclusion_zones: logger.info(f"Collected {len(exclusion_zones)} exclusion zones for text avoidance") @@ -1857,38 +1894,8 @@ class PDFGeneratorService: return None def _get_bbox_coords(self, bbox: Union[Dict, List[List[float]], List[float]]) -> Optional[Tuple[float, float, float, float]]: - """將任何 bbox 格式 (dict, 多邊形或 [x1,y1,x2,y2]) 轉換為 [x_min, y_min, x_max, y_max]""" - try: - if bbox is None: - return None - - # Dict format from UnifiedDocument: {"x0": ..., "y0": ..., "x1": ..., "y1": ...} - if isinstance(bbox, dict): - if 'x0' in bbox and 'y0' in bbox and 'x1' in bbox and 'y1' in bbox: - return float(bbox['x0']), float(bbox['y0']), float(bbox['x1']), float(bbox['y1']) - else: - logger.warning(f"Dict bbox 缺少必要欄位: {bbox}") - return None - - if not isinstance(bbox, (list, tuple)) or len(bbox) < 4: - return None - - if isinstance(bbox[0], (list, tuple)): - # 處理多邊形 [[x, y], ...] - x_coords = [p[0] for p in bbox if isinstance(p, (list, tuple)) and len(p) >= 2] - y_coords = [p[1] for p in bbox if isinstance(p, (list, tuple)) and len(p) >= 2] - if not x_coords or not y_coords: - return None - return min(x_coords), min(y_coords), max(x_coords), max(y_coords) - elif isinstance(bbox[0], (int, float)) and len(bbox) == 4: - # 處理 [x1, y1, x2, y2] - return float(bbox[0]), float(bbox[1]), float(bbox[2]), float(bbox[3]) - else: - logger.warning(f"未知的 bbox 格式: {bbox}") - return None - except Exception as e: - logger.error(f"解析 bbox {bbox} 時出錯: {e}") - return None + """將任何 bbox 格式 (dict, 多邊形或 [x1,y1,x2,y2]) 轉換為 [x_min, y_min, x_max, y_max]. Uses shared bbox utility.""" + return normalize_bbox(bbox) def _is_bbox_inside(self, inner_bbox_data: Dict, outer_bbox_data: Dict, tolerance: float = 5.0) -> bool: """ @@ -2463,29 +2470,7 @@ class PDFGeneratorService: else: logger.info("[TABLE] cell_boxes rendering failed, using ReportLab Table with borders") else: - # Grid mismatch: try cellboxes-first rendering if enabled - if settings.table_rendering_prefer_cellboxes: - logger.info(f"[TABLE] Grid mismatch, trying cellboxes-first rendering") - from app.services.pdf_table_renderer import TableRenderer, TableRenderConfig - renderer = TableRenderer(TableRenderConfig()) - success = renderer.render_from_cellboxes_grid( - pdf_canvas, - cell_boxes, - html_content, - tuple(raw_bbox), - page_height, - scale_w, - scale_h, - row_threshold=settings.table_cellboxes_row_threshold, - col_threshold=settings.table_cellboxes_col_threshold - ) - if success: - logger.info("[TABLE] cellboxes-first rendering succeeded, skipping HTML-based rendering") - return # Table fully rendered, exit early - else: - logger.info("[TABLE] cellboxes-first rendering failed, falling back to HTML-based") - else: - logger.info(f"[TABLE] Grid validation failed (mismatch), using ReportLab Table with borders") + logger.info(f"[TABLE] Grid validation failed (mismatch), using ReportLab Table with borders") else: logger.info("[TABLE] No valid bbox for grid validation, using ReportLab Table with borders") @@ -2942,47 +2927,16 @@ class PDFGeneratorService: """ Check the quality of cell_boxes to determine rendering strategy. + Always returns 'good' to use pure PP-Structure output (quality check removed). + Args: cell_boxes: List of cell bounding boxes element_id: Optional element ID for logging Returns: - 'good' if cell_boxes form a proper grid, 'bad' otherwise + 'good' - always use cell_boxes rendering """ - # If quality check is disabled, always return 'good' to use pure PP-Structure output - if not settings.table_quality_check_enabled: - logger.debug(f"[TABLE QUALITY] {element_id}: good - quality check disabled (pure PP-Structure mode)") - return 'good' - - if not cell_boxes or len(cell_boxes) < 2: - logger.debug(f"[TABLE QUALITY] {element_id}: bad - too few cells ({len(cell_boxes) if cell_boxes else 0})") - return 'bad' # No cell_boxes or too few - - # Count overlapping cell pairs - overlap_count = 0 - for i, box1 in enumerate(cell_boxes): - for j, box2 in enumerate(cell_boxes): - if i >= j: - continue - if not isinstance(box1, (list, tuple)) or len(box1) < 4: - continue - if not isinstance(box2, (list, tuple)) or len(box2) < 4: - continue - x_overlap = box1[0] < box2[2] and box1[2] > box2[0] - y_overlap = box1[1] < box2[3] and box1[3] > box2[1] - if x_overlap and y_overlap: - overlap_count += 1 - - total_pairs = len(cell_boxes) * (len(cell_boxes) - 1) // 2 - overlap_ratio = overlap_count / total_pairs if total_pairs > 0 else 0 - - # Relaxed threshold: 20% overlap instead of 10% to allow more tables through - # This is because PP-StructureV3's cell detection sometimes has slight overlaps - if overlap_ratio > 0.20: - logger.info(f"[TABLE QUALITY] {element_id}: bad - overlap ratio {overlap_ratio:.2%} > 20%") - return 'bad' - - logger.debug(f"[TABLE QUALITY] {element_id}: good - {len(cell_boxes)} cells, overlap {overlap_ratio:.2%}") + logger.debug(f"[TABLE QUALITY] {element_id}: good - pure PP-Structure mode") return 'good' def _draw_table_with_cell_boxes( diff --git a/backend/app/services/pp_structure_debug.py b/backend/app/services/pp_structure_debug.py index f15732f..b7c1b82 100644 --- a/backend/app/services/pp_structure_debug.py +++ b/backend/app/services/pp_structure_debug.py @@ -15,6 +15,8 @@ from datetime import datetime from PIL import Image, ImageDraw, ImageFont +from app.utils.bbox_utils import normalize_bbox + logger = logging.getLogger(__name__) # Color palette for different element types (RGB) @@ -238,42 +240,8 @@ class PPStructureDebug: draw.text((legend_x + 18, legend_y), "raw_ocr", fill=(0, 0, 0), font=font) def _normalize_bbox(self, bbox: Any) -> Optional[Tuple[float, float, float, float]]: - """Normalize bbox to (x0, y0, x1, y1) format.""" - if not bbox: - return None - - try: - # Handle nested list format [[x1,y1], [x2,y2], [x3,y3], [x4,y4]] - if isinstance(bbox, (list, tuple)) and len(bbox) >= 1: - if isinstance(bbox[0], (list, tuple)): - xs = [pt[0] for pt in bbox if len(pt) >= 2] - ys = [pt[1] for pt in bbox if len(pt) >= 2] - if xs and ys: - return (min(xs), min(ys), max(xs), max(ys)) - - # Handle flat list [x0, y0, x1, y1] - if isinstance(bbox, (list, tuple)) and len(bbox) == 4: - return (float(bbox[0]), float(bbox[1]), float(bbox[2]), float(bbox[3])) - - # Handle flat polygon [x1, y1, x2, y2, ...] - if isinstance(bbox, (list, tuple)) and len(bbox) >= 8: - xs = [bbox[i] for i in range(0, len(bbox), 2)] - ys = [bbox[i] for i in range(1, len(bbox), 2)] - return (min(xs), min(ys), max(xs), max(ys)) - - # Handle dict format - if isinstance(bbox, dict): - return ( - float(bbox.get('x0', bbox.get('x_min', 0))), - float(bbox.get('y0', bbox.get('y_min', 0))), - float(bbox.get('x1', bbox.get('x_max', 0))), - float(bbox.get('y1', bbox.get('y_max', 0))) - ) - - except (TypeError, ValueError, IndexError) as e: - logger.warning(f"Failed to normalize bbox {bbox}: {e}") - - return None + """Normalize bbox to (x0, y0, x1, y1) format. Uses shared bbox utility.""" + return normalize_bbox(bbox) def _generate_summary( self, diff --git a/backend/app/services/pp_structure_enhanced.py b/backend/app/services/pp_structure_enhanced.py index 9c0f4f5..9bef154 100644 --- a/backend/app/services/pp_structure_enhanced.py +++ b/backend/app/services/pp_structure_enhanced.py @@ -28,11 +28,9 @@ from PIL import Image import numpy as np import cv2 from app.models.unified_document import ElementType -from app.services.cell_validation_engine import CellValidationEngine, CellValidationConfig from app.core.config import settings from app.services.memory_manager import prediction_context from app.services.cv_table_detector import CVTableDetector -from app.services.table_content_rebuilder import TableContentRebuilder logger = logging.getLogger(__name__) @@ -159,6 +157,7 @@ class PPStructureEnhanced: all_images = [] all_tables = [] visualization_dir = None + detected_rotation = "0" # Default: no rotation # Process each page result for page_idx, page_result in enumerate(results): @@ -247,6 +246,56 @@ class PPStructureEnhanced: ocr_count = len(overall_ocr_res.get('rec_texts', [])) logger.info(f"Found overall_ocr_res with {ocr_count} text regions") + # Extract doc_preprocessor_res for orientation detection + # When use_doc_orientation_classify=True, this contains the detected rotation angle + # Note: doc_preprocessor_res may be at top-level result_json OR inside 'res' + doc_preprocessor_res = None + + # First, check result_dict (might be result_json['res']) + if 'doc_preprocessor_res' in result_dict: + doc_preprocessor_res = result_dict['doc_preprocessor_res'] + logger.info("Found doc_preprocessor_res in result_dict") + # Also check top-level result_json if it exists and differs from result_dict + elif hasattr(page_result, 'json') and isinstance(page_result.json, dict): + if 'doc_preprocessor_res' in page_result.json: + doc_preprocessor_res = page_result.json['doc_preprocessor_res'] + logger.info("Found doc_preprocessor_res at top-level result_json") + + # Debug: Log available keys to help diagnose structure issues + if doc_preprocessor_res is None: + logger.warning(f"doc_preprocessor_res NOT found. result_dict keys: {list(result_dict.keys()) if result_dict else 'None'}") + if hasattr(page_result, 'json') and isinstance(page_result.json, dict): + logger.warning(f"result_json keys: {list(page_result.json.keys())}") + + if doc_preprocessor_res: + # Debug: Log the complete structure of doc_preprocessor_res + logger.info(f"doc_preprocessor_res keys: {list(doc_preprocessor_res.keys()) if isinstance(doc_preprocessor_res, dict) else type(doc_preprocessor_res)}") + logger.info(f"doc_preprocessor_res content: {doc_preprocessor_res}") + + # Try multiple possible key names for rotation info + # PaddleOCR may use different structures depending on version + label_names = doc_preprocessor_res.get('label_names', []) + class_ids = doc_preprocessor_res.get('class_ids', []) + labels = doc_preprocessor_res.get('labels', []) + angle = doc_preprocessor_res.get('angle', None) + + # Determine rotation from available data + detected_rotation = "0" + if label_names: + detected_rotation = str(label_names[0]) + elif class_ids: + # class_ids: 0=0°, 1=90°, 2=180°, 3=270° + rotation_map = {0: "0", 1: "90", 2: "180", 3: "270"} + detected_rotation = rotation_map.get(class_ids[0], "0") + elif labels: + detected_rotation = str(labels[0]) + elif angle is not None: + detected_rotation = str(angle) + + logger.info(f"Document orientation detected: {detected_rotation}° (label_names={label_names}, class_ids={class_ids}, labels={labels}, angle={angle})") + else: + detected_rotation = "0" # Default: no rotation + # Process parsing_res_list if found if parsing_res_list: elements = self._process_parsing_res_list( @@ -295,7 +344,8 @@ class PPStructureEnhanced: 'tables': all_tables, 'images': all_images, 'element_types': self._count_element_types(all_elements), - 'has_parsing_res_list': parsing_res_list is not None + 'has_parsing_res_list': parsing_res_list is not None, + 'detected_rotation': detected_rotation # Document orientation: "0", "90", "180", "270" } # Add visualization directory if available @@ -653,42 +703,6 @@ class PPStructureEnhanced: element['embedded_images'] = embedded_images logger.info(f"[TABLE] Embedded {len(embedded_images)} images into table") - # 4. Table content rebuilding from raw OCR regions - # When cell_boxes have boundary issues, rebuild table content from raw OCR - # Only if table_content_rebuilder is enabled (disabled by default as it's a patch behavior) - logger.info(f"[TABLE] raw_ocr_regions available: {raw_ocr_regions is not None and len(raw_ocr_regions) if raw_ocr_regions else 0}") - logger.info(f"[TABLE] cell_boxes available: {len(element.get('cell_boxes', []))}") - if settings.table_content_rebuilder_enabled and raw_ocr_regions and element.get('cell_boxes'): - rebuilder = TableContentRebuilder() - should_rebuild, rebuild_reason = rebuilder.should_rebuild( - element['cell_boxes'], - bbox, - element.get('html', '') - ) - - if should_rebuild: - logger.info(f"[TABLE] Triggering table rebuild: {rebuild_reason}") - rebuilt_table, rebuild_stats = rebuilder.rebuild_table( - cell_boxes=element['cell_boxes'], - table_bbox=bbox, - raw_ocr_regions=raw_ocr_regions, - original_html=element.get('html', '') - ) - - if rebuilt_table: - # Update element with rebuilt content - element['html'] = rebuilt_table['html'] - element['rebuilt_table'] = rebuilt_table - element['rebuild_stats'] = rebuild_stats - element['extracted_text'] = self._extract_text_from_html(rebuilt_table['html']) - logger.info( - f"[TABLE] Rebuilt table: {rebuilt_table['rows']}x{rebuilt_table['cols']} " - f"with {len(rebuilt_table['cells'])} cells" - ) - else: - logger.warning(f"[TABLE] Rebuild failed: {rebuild_stats.get('reason', 'unknown')}") - element['rebuild_stats'] = rebuild_stats - # Special handling for images/figures/charts/stamps (visual elements that need cropping) elif mapped_type in [ElementType.IMAGE, ElementType.FIGURE, ElementType.CHART, ElementType.DIAGRAM, ElementType.STAMP, ElementType.LOGO]: # Save image if path provided @@ -718,21 +732,6 @@ class PPStructureEnhanced: elements.append(element) logger.debug(f"Processed element {idx}: type={mapped_type}, bbox={bbox}") - # Apply cell validation to filter over-detected tables - if settings.cell_validation_enabled: - cell_validator = CellValidationEngine(CellValidationConfig( - max_cell_density=settings.cell_validation_max_density, - min_avg_cell_area=settings.cell_validation_min_cell_area, - min_cell_height=settings.cell_validation_min_cell_height, - enabled=True - )) - elements, validation_stats = cell_validator.validate_and_filter_elements(elements) - if validation_stats['reclassified_tables'] > 0: - logger.info( - f"Cell validation: {validation_stats['reclassified_tables']}/{validation_stats['total_tables']} " - f"tables reclassified as TEXT due to over-detection" - ) - return elements def _embed_images_in_table( diff --git a/backend/app/services/table_content_rebuilder.py b/backend/app/services/table_content_rebuilder.py deleted file mode 100644 index dff6a0b..0000000 --- a/backend/app/services/table_content_rebuilder.py +++ /dev/null @@ -1,806 +0,0 @@ -""" -Table Content Rebuilder - -Rebuilds table content from raw OCR regions when PP-StructureV3's HTML output -is incorrect due to cell merge errors or boundary detection issues. - -This module addresses the key problem: PP-StructureV3's ML-based table recognition -often merges multiple cells incorrectly, especially for borderless tables. -The solution uses: -1. cell_boxes validation (filter out-of-bounds cells) -2. Raw OCR regions to rebuild accurate cell content -3. Grid-based row/col position calculation -""" - -import logging -from dataclasses import dataclass -from typing import List, Dict, Any, Optional, Tuple -from collections import defaultdict - -logger = logging.getLogger(__name__) - - -@dataclass -class CellBox: - """Represents a validated cell bounding box.""" - x0: float - y0: float - x1: float - y1: float - original_index: int - - @property - def center_y(self) -> float: - return (self.y0 + self.y1) / 2 - - @property - def center_x(self) -> float: - return (self.x0 + self.x1) / 2 - - @property - def area(self) -> float: - return max(0, (self.x1 - self.x0) * (self.y1 - self.y0)) - - -@dataclass -class OCRTextRegion: - """Represents a raw OCR text region.""" - text: str - x0: float - y0: float - x1: float - y1: float - confidence: float = 1.0 - - @property - def center_y(self) -> float: - return (self.y0 + self.y1) / 2 - - @property - def center_x(self) -> float: - return (self.x0 + self.x1) / 2 - - -@dataclass -class RebuiltCell: - """Represents a rebuilt table cell.""" - row: int - col: int - row_span: int - col_span: int - content: str - bbox: Optional[List[float]] = None - ocr_regions: List[OCRTextRegion] = None - - def __post_init__(self): - if self.ocr_regions is None: - self.ocr_regions = [] - - -class TableContentRebuilder: - """ - Rebuilds table content from raw OCR regions and validated cell_boxes. - - This class solves the problem where PP-StructureV3's HTML output incorrectly - merges multiple cells. Instead of relying on the ML-generated HTML, it: - 1. Validates cell_boxes against table bbox - 2. Groups cell_boxes into rows/columns by coordinate clustering - 3. Fills each cell with matching raw OCR text - 4. Generates correct table structure - """ - - def __init__( - self, - boundary_tolerance: float = 20.0, - row_clustering_threshold: float = 15.0, - col_clustering_threshold: float = 15.0, - iou_threshold_for_ocr_match: float = 0.3, - min_text_coverage: float = 0.5 - ): - """ - Initialize the rebuilder. - - Args: - boundary_tolerance: Tolerance for cell_boxes boundary check (pixels) - row_clustering_threshold: Max Y-distance for cells in same row (pixels) - col_clustering_threshold: Max X-distance for cells in same column (pixels) - iou_threshold_for_ocr_match: Min IoU to consider OCR region inside cell - min_text_coverage: Min overlap ratio for OCR text to be assigned to cell - """ - self.boundary_tolerance = boundary_tolerance - self.row_clustering_threshold = row_clustering_threshold - self.col_clustering_threshold = col_clustering_threshold - self.iou_threshold = iou_threshold_for_ocr_match - self.min_text_coverage = min_text_coverage - - def validate_cell_boxes( - self, - cell_boxes: List[List[float]], - table_bbox: List[float] - ) -> Tuple[List[CellBox], Dict[str, Any]]: - """ - Validate cell_boxes against table bbox, filtering invalid ones. - - Args: - cell_boxes: List of cell bounding boxes [[x0, y0, x1, y1], ...] - table_bbox: Table bounding box [x0, y0, x1, y1] - - Returns: - Tuple of (valid_cells, validation_stats) - """ - if not cell_boxes or len(table_bbox) < 4: - return [], {"total": 0, "valid": 0, "invalid": 0, "reason": "empty_input"} - - table_x0, table_y0, table_x1, table_y1 = table_bbox[:4] - table_height = table_y1 - table_y0 - table_width = table_x1 - table_x0 - - # Expanded table bounds with tolerance - expanded_y1 = table_y1 + self.boundary_tolerance - expanded_x1 = table_x1 + self.boundary_tolerance - expanded_y0 = table_y0 - self.boundary_tolerance - expanded_x0 = table_x0 - self.boundary_tolerance - - valid_cells = [] - invalid_reasons = defaultdict(int) - - for idx, box in enumerate(cell_boxes): - if not box or len(box) < 4: - invalid_reasons["invalid_format"] += 1 - continue - - x0, y0, x1, y1 = box[:4] - - # Check if cell is significantly outside table bounds - # Cell's bottom (y1) shouldn't exceed table's bottom + tolerance - if y1 > expanded_y1: - invalid_reasons["y1_exceeds_table"] += 1 - continue - - # Cell's top (y0) shouldn't be above table's top - tolerance - if y0 < expanded_y0: - invalid_reasons["y0_above_table"] += 1 - continue - - # Cell's right (x1) shouldn't exceed table's right + tolerance - if x1 > expanded_x1: - invalid_reasons["x1_exceeds_table"] += 1 - continue - - # Cell's left (x0) shouldn't be left of table - tolerance - if x0 < expanded_x0: - invalid_reasons["x0_left_of_table"] += 1 - continue - - # Check for inverted coordinates - if x0 >= x1 or y0 >= y1: - invalid_reasons["inverted_coords"] += 1 - continue - - # Check cell height is reasonable (at least 8px for readable text) - cell_height = y1 - y0 - if cell_height < 8: - invalid_reasons["too_small"] += 1 - continue - - valid_cells.append(CellBox( - x0=x0, y0=y0, x1=x1, y1=y1, - original_index=idx - )) - - stats = { - "total": len(cell_boxes), - "valid": len(valid_cells), - "invalid": len(cell_boxes) - len(valid_cells), - "invalid_reasons": dict(invalid_reasons), - "validity_ratio": len(valid_cells) / len(cell_boxes) if cell_boxes else 0 - } - - logger.info( - f"Cell box validation: {stats['valid']}/{stats['total']} valid " - f"(ratio={stats['validity_ratio']:.2%})" - ) - if invalid_reasons: - logger.debug(f"Invalid reasons: {dict(invalid_reasons)}") - - return valid_cells, stats - - def parse_raw_ocr_regions( - self, - raw_regions: List[Dict[str, Any]], - table_bbox: List[float] - ) -> List[OCRTextRegion]: - """ - Parse raw OCR regions and filter to those within/near table bbox. - - Args: - raw_regions: List of raw OCR region dicts with 'text', 'bbox', 'confidence' - table_bbox: Table bounding box [x0, y0, x1, y1] - - Returns: - List of OCRTextRegion objects within table area - """ - if not raw_regions or len(table_bbox) < 4: - return [] - - table_x0, table_y0, table_x1, table_y1 = table_bbox[:4] - # Expand table area slightly to catch edge text - margin = 10 - - result = [] - for region in raw_regions: - text = region.get('text', '').strip() - if not text: - continue - - bbox = region.get('bbox', []) - confidence = region.get('confidence', 1.0) - - # Parse bbox (handle both nested and flat formats) - if not bbox: - continue - - if isinstance(bbox[0], (list, tuple)): - # Nested format: [[x1,y1], [x2,y2], [x3,y3], [x4,y4]] - xs = [pt[0] for pt in bbox if len(pt) >= 2] - ys = [pt[1] for pt in bbox if len(pt) >= 2] - if xs and ys: - x0, y0, x1, y1 = min(xs), min(ys), max(xs), max(ys) - else: - continue - elif len(bbox) == 4: - x0, y0, x1, y1 = bbox - else: - continue - - # Check if region overlaps with table area - if (x1 < table_x0 - margin or x0 > table_x1 + margin or - y1 < table_y0 - margin or y0 > table_y1 + margin): - continue - - result.append(OCRTextRegion( - text=text, - x0=float(x0), y0=float(y0), - x1=float(x1), y1=float(y1), - confidence=confidence - )) - - logger.debug(f"Parsed {len(result)} OCR regions within table area") - return result - - def cluster_cells_into_grid( - self, - cells: List[CellBox] - ) -> Tuple[List[float], List[float], Dict[Tuple[int, int], CellBox]]: - """ - Cluster cells into rows and columns based on coordinates. - - Args: - cells: List of validated CellBox objects - - Returns: - Tuple of (row_boundaries, col_boundaries, cell_grid) - - row_boundaries: Y coordinates for row divisions - - col_boundaries: X coordinates for column divisions - - cell_grid: Dict mapping (row, col) to CellBox - """ - if not cells: - return [], [], {} - - # Collect all unique Y boundaries (top and bottom of cells) - y_coords = set() - x_coords = set() - for cell in cells: - y_coords.add(round(cell.y0, 1)) - y_coords.add(round(cell.y1, 1)) - x_coords.add(round(cell.x0, 1)) - x_coords.add(round(cell.x1, 1)) - - # Cluster nearby coordinates - row_boundaries = self._cluster_coordinates(sorted(y_coords), self.row_clustering_threshold) - col_boundaries = self._cluster_coordinates(sorted(x_coords), self.col_clustering_threshold) - - logger.debug(f"Found {len(row_boundaries)} row boundaries, {len(col_boundaries)} col boundaries") - - # Map cells to grid positions - cell_grid = {} - for cell in cells: - # Find row (based on cell's top Y coordinate) - row = self._find_position(cell.y0, row_boundaries) - # Find column (based on cell's left X coordinate) - col = self._find_position(cell.x0, col_boundaries) - - if row is not None and col is not None: - # Check for span (if cell extends across multiple rows/cols) - row_end = self._find_position(cell.y1, row_boundaries) - col_end = self._find_position(cell.x1, col_boundaries) - - # Store with potential span info - if (row, col) not in cell_grid: - cell_grid[(row, col)] = cell - - return row_boundaries, col_boundaries, cell_grid - - def _cluster_coordinates( - self, - coords: List[float], - threshold: float - ) -> List[float]: - """Cluster nearby coordinates into distinct values.""" - if not coords: - return [] - - clustered = [coords[0]] - for coord in coords[1:]: - if coord - clustered[-1] > threshold: - clustered.append(coord) - - return clustered - - def _find_position( - self, - value: float, - boundaries: List[float] - ) -> Optional[int]: - """Find which position (index) a value falls into.""" - for i, boundary in enumerate(boundaries): - if value <= boundary + self.row_clustering_threshold: - return i - return len(boundaries) - 1 if boundaries else None - - def assign_ocr_to_cells( - self, - cells: List[CellBox], - ocr_regions: List[OCRTextRegion], - row_boundaries: List[float], - col_boundaries: List[float] - ) -> Dict[Tuple[int, int], List[OCRTextRegion]]: - """ - Assign OCR text regions to cells based on spatial overlap. - - Args: - cells: List of validated CellBox objects - ocr_regions: List of OCRTextRegion objects - row_boundaries: Y coordinates for row divisions - col_boundaries: X coordinates for column divisions - - Returns: - Dict mapping (row, col) to list of OCR regions in that cell - """ - cell_ocr_map: Dict[Tuple[int, int], List[OCRTextRegion]] = defaultdict(list) - - for ocr in ocr_regions: - best_cell = None - best_overlap = 0 - - for cell in cells: - overlap = self._calculate_overlap_ratio( - (ocr.x0, ocr.y0, ocr.x1, ocr.y1), - (cell.x0, cell.y0, cell.x1, cell.y1) - ) - - if overlap > best_overlap and overlap >= self.min_text_coverage: - best_overlap = overlap - best_cell = cell - - if best_cell: - row = self._find_position(best_cell.y0, row_boundaries) - col = self._find_position(best_cell.x0, col_boundaries) - if row is not None and col is not None: - cell_ocr_map[(row, col)].append(ocr) - - return cell_ocr_map - - def _calculate_overlap_ratio( - self, - box1: Tuple[float, float, float, float], - box2: Tuple[float, float, float, float] - ) -> float: - """Calculate overlap ratio of box1 with box2.""" - x0_1, y0_1, x1_1, y1_1 = box1 - x0_2, y0_2, x1_2, y1_2 = box2 - - # Calculate intersection - inter_x0 = max(x0_1, x0_2) - inter_y0 = max(y0_1, y0_2) - inter_x1 = min(x1_1, x1_2) - inter_y1 = min(y1_1, y1_2) - - if inter_x0 >= inter_x1 or inter_y0 >= inter_y1: - return 0.0 - - inter_area = (inter_x1 - inter_x0) * (inter_y1 - inter_y0) - box1_area = (x1_1 - x0_1) * (y1_1 - y0_1) - - return inter_area / box1_area if box1_area > 0 else 0.0 - - def rebuild_table( - self, - cell_boxes: List[List[float]], - table_bbox: List[float], - raw_ocr_regions: List[Dict[str, Any]], - original_html: str = "" - ) -> Tuple[Dict[str, Any], Dict[str, Any]]: - """ - Rebuild table content from cell_boxes and raw OCR regions. - - This is the main entry point. It: - 1. Validates cell_boxes - 2. If validity ratio is low, uses pure OCR-based rebuild - 3. Otherwise, uses cell_boxes + OCR hybrid rebuild - - Args: - cell_boxes: List of cell bounding boxes from PP-StructureV3 - table_bbox: Table bounding box [x0, y0, x1, y1] - raw_ocr_regions: List of raw OCR region dicts - original_html: Original HTML from PP-StructureV3 (for fallback) - - Returns: - Tuple of (rebuilt_table_dict, rebuild_stats) - """ - stats = { - "action": "none", - "reason": "", - "original_cell_count": len(cell_boxes) if cell_boxes else 0, - "valid_cell_count": 0, - "ocr_regions_in_table": 0, - "rebuilt_rows": 0, - "rebuilt_cols": 0 - } - - # Step 1: Validate cell_boxes - valid_cells, validation_stats = self.validate_cell_boxes(cell_boxes, table_bbox) - stats["valid_cell_count"] = validation_stats["valid"] - stats["validation"] = validation_stats - - # Step 2: Parse raw OCR regions in table area - ocr_regions = self.parse_raw_ocr_regions(raw_ocr_regions, table_bbox) - stats["ocr_regions_in_table"] = len(ocr_regions) - - if not ocr_regions: - stats["action"] = "skip" - stats["reason"] = "no_ocr_regions_in_table" - return None, stats - - # Step 3: Choose rebuild strategy based on cell_boxes validity - # If validity ratio is too low (< 50%), use pure OCR-based rebuild - if validation_stats["validity_ratio"] < 0.5 or len(valid_cells) < 2: - logger.info( - f"Using pure OCR-based rebuild (validity={validation_stats['validity_ratio']:.2%})" - ) - return self._rebuild_from_ocr_only(ocr_regions, table_bbox, stats) - - # Otherwise, use hybrid cell_boxes + OCR rebuild - return self._rebuild_with_cell_boxes(valid_cells, ocr_regions, stats, table_bbox) - - def _rebuild_from_ocr_only( - self, - ocr_regions: List[OCRTextRegion], - table_bbox: List[float], - stats: Dict[str, Any] - ) -> Tuple[Dict[str, Any], Dict[str, Any]]: - """ - Rebuild table using only OCR regions (when cell_boxes are unreliable). - - Strategy: - 1. Detect column boundary from OCR x-coordinates - 2. Cluster OCR regions by Y coordinate into rows - 3. Split each row into left/right columns - """ - if not ocr_regions: - stats["action"] = "skip" - stats["reason"] = "no_ocr_regions" - return None, stats - - # Get table bounds - table_x0, table_y0, table_x1, table_y1 = table_bbox[:4] - table_width = table_x1 - table_x0 - - # Step 1: Detect column split point by analyzing x-coordinates - # Look for the gap between left column (x0 < 250) and right column (x0 >= 250) - col_split_x = self._detect_column_split(ocr_regions, table_bbox) - logger.debug(f"Detected column split at x={col_split_x}") - - # Step 2: Cluster OCR regions by Y coordinate into rows - # Use smaller threshold (12px) to properly separate rows - row_threshold = 12.0 - sorted_ocr = sorted(ocr_regions, key=lambda r: r.center_y) - - rows = [] - current_row = [sorted_ocr[0]] - - for ocr in sorted_ocr[1:]: - if ocr.center_y - current_row[-1].center_y <= row_threshold: - current_row.append(ocr) - else: - rows.append(current_row) - current_row = [ocr] - rows.append(current_row) - - logger.debug(f"Detected {len(rows)} rows") - - # Step 3: Analyze column structure - left_regions = [r for r in ocr_regions if r.x0 < col_split_x] - right_regions = [r for r in ocr_regions if r.x0 >= col_split_x] - num_cols = 2 if len(left_regions) >= 2 and len(right_regions) >= 2 else 1 - - # Step 4: Build cells for each row - rebuilt_cells = [] - for row_idx, row_ocrs in enumerate(rows): - row_ocrs_sorted = sorted(row_ocrs, key=lambda r: r.center_x) - - if num_cols == 2: - # Split into left and right columns using x0 - left_ocrs = [r for r in row_ocrs_sorted if r.x0 < col_split_x] - right_ocrs = [r for r in row_ocrs_sorted if r.x0 >= col_split_x] - - # Left column cell - if left_ocrs: - left_content = " ".join(r.text for r in left_ocrs) - left_bbox = [ - min(r.x0 for r in left_ocrs), - min(r.y0 for r in left_ocrs), - max(r.x1 for r in left_ocrs), - max(r.y1 for r in left_ocrs) - ] - rebuilt_cells.append({ - "row": row_idx, - "col": 0, - "row_span": 1, - "col_span": 1, - "content": left_content, - "bbox": left_bbox - }) - - # Right column cell - if right_ocrs: - right_content = " ".join(r.text for r in right_ocrs) - right_bbox = [ - min(r.x0 for r in right_ocrs), - min(r.y0 for r in right_ocrs), - max(r.x1 for r in right_ocrs), - max(r.y1 for r in right_ocrs) - ] - rebuilt_cells.append({ - "row": row_idx, - "col": 1, - "row_span": 1, - "col_span": 1, - "content": right_content, - "bbox": right_bbox - }) - else: - # Single column - merge all OCR in row - row_content = " ".join(r.text for r in row_ocrs_sorted) - row_bbox = [ - min(r.x0 for r in row_ocrs_sorted), - min(r.y0 for r in row_ocrs_sorted), - max(r.x1 for r in row_ocrs_sorted), - max(r.y1 for r in row_ocrs_sorted) - ] - rebuilt_cells.append({ - "row": row_idx, - "col": 0, - "row_span": 1, - "col_span": 1, - "content": row_content, - "bbox": row_bbox - }) - - num_rows = len(rows) - stats["rebuilt_rows"] = num_rows - stats["rebuilt_cols"] = num_cols - - # Build result - rebuilt_table = { - "rows": num_rows, - "cols": num_cols, - "cells": rebuilt_cells, - "html": self._generate_html(rebuilt_cells, num_rows, num_cols), - "rebuild_source": "pure_ocr" - } - - stats["action"] = "rebuilt" - stats["reason"] = "pure_ocr_success" - stats["rebuilt_cell_count"] = len(rebuilt_cells) - - logger.info( - f"Table rebuilt (pure OCR): {num_rows}x{num_cols} with {len(rebuilt_cells)} cells" - ) - - return rebuilt_table, stats - - def _detect_column_split( - self, - ocr_regions: List[OCRTextRegion], - table_bbox: List[float] - ) -> float: - """ - Detect the column split point by analyzing x-coordinates. - - For tables with left/right structure (e.g., property-value tables), - there's usually a gap between left column text and right column text. - """ - if not ocr_regions: - return (table_bbox[0] + table_bbox[2]) / 2 - - # Collect all x0 values (left edge of each text region) - x0_values = sorted(set(round(r.x0) for r in ocr_regions)) - - if len(x0_values) < 2: - return (table_bbox[0] + table_bbox[2]) / 2 - - # Find the largest gap between consecutive x0 values - # This usually indicates the column boundary - max_gap = 0 - split_point = (table_bbox[0] + table_bbox[2]) / 2 - - for i in range(len(x0_values) - 1): - gap = x0_values[i + 1] - x0_values[i] - if gap > max_gap and gap > 50: # Require minimum 50px gap - max_gap = gap - split_point = (x0_values[i] + x0_values[i + 1]) / 2 - - # If no clear gap found, use table center - if max_gap < 50: - split_point = (table_bbox[0] + table_bbox[2]) / 2 - - return split_point - - def _rebuild_with_cell_boxes( - self, - valid_cells: List[CellBox], - ocr_regions: List[OCRTextRegion], - stats: Dict[str, Any], - table_bbox: Optional[List[float]] = None - ) -> Tuple[Dict[str, Any], Dict[str, Any]]: - """Rebuild table using cell_boxes structure + OCR content.""" - # Step 3: Cluster cells into grid - row_boundaries, col_boundaries, cell_grid = self.cluster_cells_into_grid(valid_cells) - - num_rows = len(row_boundaries) - 1 if len(row_boundaries) > 1 else 1 - num_cols = len(col_boundaries) - 1 if len(col_boundaries) > 1 else 1 - - # Quality check: if hybrid produces too many columns or sparse grid, fall back to pure OCR - # A well-formed table typically has 2-5 columns. Too many columns indicates poor clustering. - total_expected_cells = num_rows * num_cols - if num_cols > 5 or total_expected_cells > 100: - logger.info( - f"Hybrid mode produced {num_rows}x{num_cols} grid (too sparse), " - f"falling back to pure OCR mode" - ) - if table_bbox: - return self._rebuild_from_ocr_only(ocr_regions, table_bbox, stats) - - stats["rebuilt_rows"] = num_rows - stats["rebuilt_cols"] = num_cols - - # Step 4: Assign OCR text to cells - cell_ocr_map = self.assign_ocr_to_cells( - valid_cells, ocr_regions, row_boundaries, col_boundaries - ) - - # Step 5: Build rebuilt cells - rebuilt_cells = [] - for (row, col), ocr_list in cell_ocr_map.items(): - # Sort OCR regions by position (top to bottom, left to right) - sorted_ocr = sorted(ocr_list, key=lambda r: (r.center_y, r.center_x)) - content = " ".join(r.text for r in sorted_ocr) - - # Find the cell bbox for this position - cell_bbox = None - for cell in valid_cells: - cell_row = self._find_position(cell.y0, row_boundaries) - cell_col = self._find_position(cell.x0, col_boundaries) - if cell_row == row and cell_col == col: - cell_bbox = [cell.x0, cell.y0, cell.x1, cell.y1] - break - - rebuilt_cells.append({ - "row": row, - "col": col, - "row_span": 1, - "col_span": 1, - "content": content, - "bbox": cell_bbox - }) - - # Quality check: if too few cells have content compared to grid size, fall back to pure OCR - content_ratio = len(rebuilt_cells) / total_expected_cells if total_expected_cells > 0 else 0 - if content_ratio < 0.3 and table_bbox: - logger.info( - f"Hybrid mode has low content ratio ({content_ratio:.2%}), " - f"falling back to pure OCR mode" - ) - return self._rebuild_from_ocr_only(ocr_regions, table_bbox, stats) - - # Build result - rebuilt_table = { - "rows": num_rows, - "cols": num_cols, - "cells": rebuilt_cells, - "html": self._generate_html(rebuilt_cells, num_rows, num_cols), - "rebuild_source": "cell_boxes_hybrid" - } - - stats["action"] = "rebuilt" - stats["reason"] = "hybrid_success" - stats["rebuilt_cell_count"] = len(rebuilt_cells) - - logger.info( - f"Table rebuilt (hybrid): {num_rows}x{num_cols} with {len(rebuilt_cells)} cells " - f"(from {len(ocr_regions)} OCR regions)" - ) - - return rebuilt_table, stats - - def _generate_html( - self, - cells: List[Dict[str, Any]], - num_rows: int, - num_cols: int - ) -> str: - """Generate HTML table from rebuilt cells.""" - # Create grid - grid = [[None for _ in range(num_cols)] for _ in range(num_rows)] - - for cell in cells: - row, col = cell["row"], cell["col"] - if 0 <= row < num_rows and 0 <= col < num_cols: - grid[row][col] = cell["content"] - - # Build HTML - html_parts = [""] - for row_idx in range(num_rows): - html_parts.append("") - for col_idx in range(num_cols): - content = grid[row_idx][col_idx] or "" - tag = "th" if row_idx == 0 else "td" - html_parts.append(f"<{tag}>{content}") - html_parts.append("") - html_parts.append("
") - - return "".join(html_parts) - - def should_rebuild( - self, - cell_boxes: List[List[float]], - table_bbox: List[float], - original_html: str = "" - ) -> Tuple[bool, str]: - """ - Determine if table should be rebuilt based on cell_boxes validity. - - Args: - cell_boxes: List of cell bounding boxes - table_bbox: Table bounding box - original_html: Original HTML from PP-StructureV3 - - Returns: - Tuple of (should_rebuild, reason) - """ - if not cell_boxes: - return False, "no_cell_boxes" - - _, validation_stats = self.validate_cell_boxes(cell_boxes, table_bbox) - - # Always rebuild if ANY cells are invalid - PP-Structure HTML often merges cells incorrectly - # even when most cell_boxes are valid - if validation_stats["invalid"] > 0: - return True, f"invalid_cells_{validation_stats['invalid']}/{validation_stats['total']}" - - # Rebuild if there are boundary violations - invalid_reasons = validation_stats.get("invalid_reasons", {}) - boundary_violations = ( - invalid_reasons.get("y1_exceeds_table", 0) + - invalid_reasons.get("y0_above_table", 0) + - invalid_reasons.get("x1_exceeds_table", 0) + - invalid_reasons.get("x0_left_of_table", 0) - ) - - if boundary_violations > 0: - return True, f"boundary_violations_{boundary_violations}" - - # Also rebuild to ensure OCR-based content is used instead of PP-Structure HTML - # PP-Structure's HTML often has incorrect cell merging - return True, "ocr_content_preferred" diff --git a/backend/app/services/text_region_renderer.py b/backend/app/services/text_region_renderer.py index 9807e14..ef59109 100644 --- a/backend/app/services/text_region_renderer.py +++ b/backend/app/services/text_region_renderer.py @@ -15,6 +15,8 @@ from typing import Dict, List, Optional, Set, Tuple from reportlab.pdfgen import canvas from reportlab.lib.colors import black +from app.utils.bbox_utils import normalize_bbox + logger = logging.getLogger(__name__) @@ -162,6 +164,7 @@ class TextRegionRenderer: def get_bbox_as_rect(self, bbox: List[List[float]]) -> Tuple[float, float, float, float]: """ Convert quadrilateral bbox to axis-aligned rectangle (x0, y0, x1, y1). + Uses shared bbox utility. Args: bbox: List of 4 [x, y] coordinate pairs @@ -169,12 +172,8 @@ class TextRegionRenderer: Returns: Tuple of (x0, y0, x1, y1) - min/max coordinates """ - if len(bbox) < 4: - return (0.0, 0.0, 0.0, 0.0) - - x_coords = [p[0] for p in bbox] - y_coords = [p[1] for p in bbox] - return (min(x_coords), min(y_coords), max(x_coords), max(y_coords)) + result = normalize_bbox(bbox) + return result if result else (0.0, 0.0, 0.0, 0.0) def get_bbox_left_baseline( self, @@ -646,19 +645,26 @@ def load_raw_ocr_regions(result_dir: str, task_id: str, page_num: int) -> List[D from pathlib import Path import json - # Construct filename pattern - filename = f"{task_id}_edit_page_{page_num}_raw_ocr_regions.json" - file_path = Path(result_dir) / filename + result_path = Path(result_dir) - if not file_path.exists(): - logger.warning(f"Raw OCR regions file not found: {file_path}") - return [] + # Use glob pattern to find raw OCR regions file + # Filename format: {task_id}_{original_filename}_page_{page_num}_raw_ocr_regions.json + # The original_filename varies based on uploaded file (e.g., scan, document, etc.) + glob_pattern = f"{task_id}_*_page_{page_num}_raw_ocr_regions.json" + matching_files = list(result_path.glob(glob_pattern)) - try: - with open(file_path, 'r', encoding='utf-8') as f: - regions = json.load(f) - logger.info(f"Loaded {len(regions)} raw OCR regions from {filename}") - return regions - except Exception as e: - logger.error(f"Failed to load raw OCR regions: {e}") - return [] + if matching_files: + # Use the first matching file (there should only be one per page) + file_path = matching_files[0] + try: + with open(file_path, 'r', encoding='utf-8') as f: + regions = json.load(f) + logger.info(f"Loaded {len(regions)} raw OCR regions from {file_path.name}") + return regions + except Exception as e: + logger.error(f"Failed to load raw OCR regions from {file_path}: {e}") + return [] + + logger.warning(f"Raw OCR regions file not found for task {task_id} page {page_num}. " + f"Glob pattern: {glob_pattern}") + return [] diff --git a/backend/app/utils/__init__.py b/backend/app/utils/__init__.py new file mode 100644 index 0000000..f4295de --- /dev/null +++ b/backend/app/utils/__init__.py @@ -0,0 +1,5 @@ +"""Utility modules for the OCR application.""" + +from .bbox_utils import normalize_bbox, get_bbox_center, calculate_ioa + +__all__ = ['normalize_bbox', 'get_bbox_center', 'calculate_ioa'] diff --git a/backend/app/utils/bbox_utils.py b/backend/app/utils/bbox_utils.py new file mode 100644 index 0000000..68d4083 --- /dev/null +++ b/backend/app/utils/bbox_utils.py @@ -0,0 +1,265 @@ +""" +Unified bounding box utilities for consistent bbox handling across services. + +Supports multiple bbox formats: +- Nested polygon: [[x1,y1], [x2,y2], [x3,y3], [x4,y4]] +- Flat rectangle: [x0, y0, x1, y1] +- Flat polygon: [x1, y1, x2, y2, x3, y3, x4, y4] +- Dict format: {"x0": ..., "y0": ..., "x1": ..., "y1": ...} +""" + +import logging +from typing import Any, Dict, List, Optional, Tuple, Union + +logger = logging.getLogger(__name__) + +BboxCoords = Tuple[float, float, float, float] # (x0, y0, x1, y1) + + +def normalize_bbox( + bbox: Union[Dict, List, Tuple, None] +) -> Optional[BboxCoords]: + """ + Normalize any bbox format to (x0, y0, x1, y1) tuple. + + Handles: + - Nested polygon: [[x1,y1], [x2,y2], [x3,y3], [x4,y4]] + - Flat rectangle: [x0, y0, x1, y1] + - Flat polygon: [x1, y1, x2, y2, x3, y3, x4, y4] + - Dict format: {"x0": ..., "y0": ..., "x1": ..., "y1": ...} + + Args: + bbox: Bounding box in any supported format + + Returns: + Normalized (x0, y0, x1, y1) tuple or None if invalid + """ + if bbox is None: + return None + + try: + # Dict format: {"x0": ..., "y0": ..., "x1": ..., "y1": ...} + if isinstance(bbox, dict): + if 'x0' in bbox and 'y0' in bbox and 'x1' in bbox and 'y1' in bbox: + return ( + float(bbox['x0']), + float(bbox['y0']), + float(bbox['x1']), + float(bbox['y1']) + ) + # Alternative dict keys + if 'x_min' in bbox or 'y_min' in bbox: + return ( + float(bbox.get('x_min', bbox.get('x0', 0))), + float(bbox.get('y_min', bbox.get('y0', 0))), + float(bbox.get('x_max', bbox.get('x1', 0))), + float(bbox.get('y_max', bbox.get('y1', 0))) + ) + logger.warning(f"Dict bbox missing required fields: {bbox}") + return None + + # List/tuple formats + if isinstance(bbox, (list, tuple)): + if len(bbox) == 0: + return None + + # Nested polygon format: [[x1,y1], [x2,y2], ...] + if isinstance(bbox[0], (list, tuple)): + xs = [pt[0] for pt in bbox if len(pt) >= 2] + ys = [pt[1] for pt in bbox if len(pt) >= 2] + if xs and ys: + return ( + float(min(xs)), + float(min(ys)), + float(max(xs)), + float(max(ys)) + ) + return None + + # Flat rectangle: [x0, y0, x1, y1] + if len(bbox) == 4: + return ( + float(bbox[0]), + float(bbox[1]), + float(bbox[2]), + float(bbox[3]) + ) + + # Flat polygon: [x1, y1, x2, y2, x3, y3, x4, y4, ...] + if len(bbox) >= 8 and len(bbox) % 2 == 0: + xs = [bbox[i] for i in range(0, len(bbox), 2)] + ys = [bbox[i] for i in range(1, len(bbox), 2)] + return ( + float(min(xs)), + float(min(ys)), + float(max(xs)), + float(max(ys)) + ) + + logger.warning(f"Unknown bbox format: {type(bbox).__name__}, value: {bbox}") + return None + + except (TypeError, ValueError, IndexError) as e: + logger.warning(f"Failed to normalize bbox {bbox}: {e}") + return None + + +def get_bbox_center(bbox: Union[Dict, List, Tuple, BboxCoords, None]) -> Optional[Tuple[float, float]]: + """ + Get the center point of a bounding box. + + Args: + bbox: Bounding box in any supported format or already normalized + + Returns: + (center_x, center_y) tuple or None if invalid + """ + # If already normalized tuple + if isinstance(bbox, tuple) and len(bbox) == 4: + x0, y0, x1, y1 = bbox + return ((x0 + x1) / 2, (y0 + y1) / 2) + + # Otherwise normalize first + coords = normalize_bbox(bbox) + if coords is None: + return None + + x0, y0, x1, y1 = coords + return ((x0 + x1) / 2, (y0 + y1) / 2) + + +def get_bbox_area(bbox: Union[Dict, List, Tuple, BboxCoords, None]) -> float: + """ + Calculate the area of a bounding box. + + Args: + bbox: Bounding box in any supported format + + Returns: + Area in square pixels, 0 if invalid + """ + coords = normalize_bbox(bbox) if not (isinstance(bbox, tuple) and len(bbox) == 4) else bbox + if coords is None: + return 0.0 + + x0, y0, x1, y1 = coords + return max(0, x1 - x0) * max(0, y1 - y0) + + +def calculate_ioa( + inner_bbox: Union[Dict, List, Tuple, BboxCoords, None], + outer_bbox: Union[Dict, List, Tuple, BboxCoords, None] +) -> float: + """ + Calculate Intersection over Area (IoA) of inner bbox with respect to outer bbox. + + IoA = intersection_area / inner_area + + Args: + inner_bbox: The bbox to check (numerator area) + outer_bbox: The reference bbox + + Returns: + IoA ratio (0.0 to 1.0), 0.0 if either bbox is invalid + """ + inner_coords = normalize_bbox(inner_bbox) if not (isinstance(inner_bbox, tuple) and len(inner_bbox) == 4) else inner_bbox + outer_coords = normalize_bbox(outer_bbox) if not (isinstance(outer_bbox, tuple) and len(outer_bbox) == 4) else outer_bbox + + if inner_coords is None or outer_coords is None: + return 0.0 + + inner_x0, inner_y0, inner_x1, inner_y1 = inner_coords + outer_x0, outer_y0, outer_x1, outer_y1 = outer_coords + + # Calculate intersection + inter_x0 = max(inner_x0, outer_x0) + inter_y0 = max(inner_y0, outer_y0) + inter_x1 = min(inner_x1, outer_x1) + inter_y1 = min(inner_y1, outer_y1) + + if inter_x1 <= inter_x0 or inter_y1 <= inter_y0: + return 0.0 + + intersection_area = (inter_x1 - inter_x0) * (inter_y1 - inter_y0) + inner_area = (inner_x1 - inner_x0) * (inner_y1 - inner_y0) + + if inner_area <= 0: + return 0.0 + + return intersection_area / inner_area + + +def calculate_iou( + bbox1: Union[Dict, List, Tuple, BboxCoords, None], + bbox2: Union[Dict, List, Tuple, BboxCoords, None] +) -> float: + """ + Calculate Intersection over Union (IoU) of two bounding boxes. + + Args: + bbox1: First bounding box + bbox2: Second bounding box + + Returns: + IoU ratio (0.0 to 1.0), 0.0 if either bbox is invalid + """ + coords1 = normalize_bbox(bbox1) if not (isinstance(bbox1, tuple) and len(bbox1) == 4) else bbox1 + coords2 = normalize_bbox(bbox2) if not (isinstance(bbox2, tuple) and len(bbox2) == 4) else bbox2 + + if coords1 is None or coords2 is None: + return 0.0 + + x0_1, y0_1, x1_1, y1_1 = coords1 + x0_2, y0_2, x1_2, y1_2 = coords2 + + # Calculate intersection + inter_x0 = max(x0_1, x0_2) + inter_y0 = max(y0_1, y0_2) + inter_x1 = min(x1_1, x1_2) + inter_y1 = min(y1_1, y1_2) + + if inter_x1 <= inter_x0 or inter_y1 <= inter_y0: + return 0.0 + + intersection_area = (inter_x1 - inter_x0) * (inter_y1 - inter_y0) + area1 = (x1_1 - x0_1) * (y1_1 - y0_1) + area2 = (x1_2 - x0_2) * (y1_2 - y0_2) + union_area = area1 + area2 - intersection_area + + if union_area <= 0: + return 0.0 + + return intersection_area / union_area + + +def is_bbox_inside( + inner_bbox: Union[Dict, List, Tuple, BboxCoords, None], + outer_bbox: Union[Dict, List, Tuple, BboxCoords, None], + tolerance: float = 0.0 +) -> bool: + """ + Check if inner_bbox is completely inside outer_bbox (with optional tolerance). + + Args: + inner_bbox: The bbox to check + outer_bbox: The containing bbox + tolerance: Allowed overflow in pixels + + Returns: + True if inner is inside outer (within tolerance) + """ + inner_coords = normalize_bbox(inner_bbox) if not (isinstance(inner_bbox, tuple) and len(inner_bbox) == 4) else inner_bbox + outer_coords = normalize_bbox(outer_bbox) if not (isinstance(outer_bbox, tuple) and len(outer_bbox) == 4) else outer_bbox + + if inner_coords is None or outer_coords is None: + return False + + inner_x0, inner_y0, inner_x1, inner_y1 = inner_coords + outer_x0, outer_y0, outer_x1, outer_y1 = outer_coords + + return ( + inner_x0 >= outer_x0 - tolerance and + inner_y0 >= outer_y0 - tolerance and + inner_x1 <= outer_x1 + tolerance and + inner_y1 <= outer_y1 + tolerance + ) diff --git a/frontend/src/components/OCRPresetSelector.tsx b/frontend/src/components/OCRPresetSelector.tsx deleted file mode 100644 index 61b071d..0000000 --- a/frontend/src/components/OCRPresetSelector.tsx +++ /dev/null @@ -1,358 +0,0 @@ -import { useState } from 'react' -import { cn } from '@/lib/utils' -import { Check, ChevronDown, ChevronUp, FileText, Table, Settings, FileEdit, Layers, Cog } from 'lucide-react' -import { useTranslation } from 'react-i18next' -import type { OCRPreset, OCRConfig, TableParsingMode, OCRPresetInfo } from '@/types/apiV2' - -interface OCRPresetSelectorProps { - value: OCRPreset - onChange: (preset: OCRPreset) => void - customConfig?: OCRConfig - onCustomConfigChange?: (config: OCRConfig) => void - disabled?: boolean - className?: string -} - -// Preset icons mapping -const PRESET_ICONS: Record = { - text_heavy: , - datasheet: , - table_heavy: , - form: , - mixed: , - custom: , -} - -// Preset configurations (matching backend OCR_PRESET_CONFIGS) -const PRESET_CONFIGS: Record = { - text_heavy: { - table_parsing_mode: 'disabled', - enable_wired_table: false, - enable_wireless_table: false, - enable_chart_recognition: false, - enable_formula_recognition: false, - }, - datasheet: { - table_parsing_mode: 'conservative', - enable_wired_table: true, - enable_wireless_table: false, - }, - table_heavy: { - table_parsing_mode: 'full', - enable_wired_table: true, - enable_wireless_table: true, - }, - form: { - table_parsing_mode: 'conservative', - enable_wired_table: true, - enable_wireless_table: false, - }, - mixed: { - table_parsing_mode: 'classification_only', - enable_wired_table: true, - enable_wireless_table: false, - }, - custom: {}, -} - -// Preset info for display -const PRESET_INFO: Record = { - text_heavy: { - displayName: '純文字文件', - description: '報告、文章、手冊等以文字為主的文件。禁用表格識別以提高處理速度。', - }, - datasheet: { - displayName: '技術規格書', - description: '產品規格書、技術數據表 (TDS)。使用保守模式避免過度分割。', - }, - table_heavy: { - displayName: '表格密集文件', - description: '財務報表、試算表。啟用完整表格識別以捕捉所有表格。', - }, - form: { - displayName: '表單', - description: '申請表、問卷調查。識別表單欄位但避免過度分割。', - }, - mixed: { - displayName: '混合內容', - description: '一般文件。只做表格區域分類，不做細胞分割。', - }, - custom: { - displayName: '自訂設定', - description: '進階使用者可自行調整所有 PP-Structure 參數。', - }, -} - -export default function OCRPresetSelector({ - value, - onChange, - customConfig, - onCustomConfigChange, - disabled = false, - className, -}: OCRPresetSelectorProps) { - const { t } = useTranslation() - const [showAdvanced, setShowAdvanced] = useState(false) - const presets: OCRPreset[] = ['datasheet', 'text_heavy', 'table_heavy', 'form', 'mixed', 'custom'] - - const getPresetInfo = (preset: OCRPreset) => PRESET_INFO[preset] - - // Get effective config (preset config merged with custom overrides) - const getEffectiveConfig = (): OCRConfig => { - if (value === 'custom') { - return customConfig || {} - } - return { ...PRESET_CONFIGS[value], ...customConfig } - } - - const handleCustomConfigChange = (key: keyof OCRConfig, val: any) => { - if (onCustomConfigChange) { - onCustomConfigChange({ - ...customConfig, - [key]: val, - }) - } - } - - return ( -
- {/* Header */} -
-
- -

OCR 處理預設

-
- -
- - {/* Preset Grid */} -
- {presets.map((preset) => { - const info = getPresetInfo(preset) - const isSelected = value === preset - - return ( - - ) - })} -
- - {/* Selected Preset Description */} -
-

- {PRESET_INFO[value].displayName}： - {PRESET_INFO[value].description} -

-
- - {/* Advanced Settings Panel */} - {showAdvanced && ( -
-

- - 進階參數設定 -

- - {/* Table Parsing Mode */} -
- - -

- {value !== 'custom' && '選擇「自訂設定」預設以調整此參數'} -

-
- - {/* Table Detection Options */} -
- - -
- - {/* Recognition Modules */} -
- -
- - - - -
-
- - {/* Preprocessing Options */} -
- -
- - -
-
- - {value !== 'custom' && ( -

- 提示：選擇「自訂設定」預設以啟用手動調整參數 -

- )} -
- )} - - {/* Info Note */} -
-

- 預設配置會根據文件類型優化 PP-Structure 的表格識別和版面分析參數。 - 選擇錯誤的預設可能導致表格過度分割或識別失敗。 -

-
-
- ) -} diff --git a/frontend/src/components/PDFViewer.tsx b/frontend/src/components/PDFViewer.tsx index cc65274..538e215 100644 --- a/frontend/src/components/PDFViewer.tsx +++ b/frontend/src/components/PDFViewer.tsx @@ -1,6 +1,8 @@ import { useState, useCallback, useMemo, useRef, useEffect } from 'react' import { Document, Page, pdfjs } from 'react-pdf' -import type { PDFDocumentProxy } from 'pdfjs-dist' + +// Type alias for PDFDocumentProxy to avoid direct pdfjs-dist import issues +type PDFDocumentProxy = ReturnType extends Promise ? T : never import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card' import { Button } from '@/components/ui/button' import { ChevronLeft, ChevronRight, ZoomIn, ZoomOut, Loader2 } from 'lucide-react' diff --git a/frontend/src/components/TableDetectionSelector.tsx b/frontend/src/components/TableDetectionSelector.tsx deleted file mode 100644 index 752767b..0000000 --- a/frontend/src/components/TableDetectionSelector.tsx +++ /dev/null @@ -1,124 +0,0 @@ -import { cn } from '@/lib/utils' -import { Checkbox } from '@/components/ui/checkbox' -import { Table, Grid3X3, Rows3 } from 'lucide-react' -import { useTranslation } from 'react-i18next' -import type { TableDetectionConfig } from '@/types/apiV2' - -interface TableDetectionSelectorProps { - value: TableDetectionConfig - onChange: (config: TableDetectionConfig) => void - disabled?: boolean - className?: string -} - -interface DetectionOption { - key: keyof TableDetectionConfig - icon: React.ReactNode - labelKey: string - descKey: string -} - -const DETECTION_OPTIONS: DetectionOption[] = [ - { - key: 'enable_wired_table', - icon: , - labelKey: 'processing.tableDetection.wired', - descKey: 'processing.tableDetection.wiredDesc', - }, - { - key: 'enable_wireless_table', - icon: , - labelKey: 'processing.tableDetection.wireless', - descKey: 'processing.tableDetection.wirelessDesc', - }, - { - key: 'enable_region_detection', - icon:
, - labelKey: 'processing.tableDetection.region', - descKey: 'processing.tableDetection.regionDesc', - }, -] - -export default function TableDetectionSelector({ - value, - onChange, - disabled = false, - className, -}: TableDetectionSelectorProps) { - const { t } = useTranslation() - - const handleOptionChange = (key: keyof TableDetectionConfig, checked: boolean) => { - onChange({ - ...value, - [key]: checked, - }) - } - - return ( -
- {/* Header */} -
-
-

{t('processing.tableDetection.title')}

- - - {/* Detection Options */} -
- {DETECTION_OPTIONS.map((option) => { - const isChecked = value[option.key] - - return ( - - ) - })} -
- - {/* Info Note */} -
-

- {t('processing.tableDetection.note')} -

-
- - ) -} diff --git a/frontend/src/hooks/useTaskValidation.ts b/frontend/src/hooks/useTaskValidation.ts index de5fc3f..851b608 100644 --- a/frontend/src/hooks/useTaskValidation.ts +++ b/frontend/src/hooks/useTaskValidation.ts @@ -1,5 +1,6 @@ import { useEffect, useState } from 'react' import { useQuery } from '@tanstack/react-query' +import { AxiosError } from 'axios' import { useUploadStore } from '@/store/uploadStore' import { useTaskStore } from '@/store/taskStore' import { apiClientV2 } from '@/services/apiV2' @@ -58,7 +59,7 @@ export function useTaskValidation(options?: { // Handle 404 error - mark as not found and clean up cache useEffect(() => { - if (error && (error as any)?.response?.status === 404) { + if (error && error instanceof AxiosError && error.response?.status === 404) { setIsNotFound(true) if (taskId) { removeFromCache(taskId) diff --git a/frontend/src/pages/AuditLogsPage.tsx b/frontend/src/pages/AuditLogsPage.tsx index dcf6e62..586704e 100644 --- a/frontend/src/pages/AuditLogsPage.tsx +++ b/frontend/src/pages/AuditLogsPage.tsx @@ -29,7 +29,7 @@ import { TableRow, } from '@/components/ui/table' import { Badge } from '@/components/ui/badge' -import { Select } from '@/components/ui/select' +import { NativeSelect } from '@/components/ui/select' export default function AuditLogsPage() { const navigate = useNavigate() @@ -145,9 +145,9 @@ export default function AuditLogsPage() {
- { + onChange={(e: React.ChangeEvent) => { setSuccessFilter(e.target.value) handleFilterChange() }} diff --git a/frontend/src/pages/ExportPage.tsx b/frontend/src/pages/ExportPage.tsx index 6f470e7..a7f2ca4 100644 --- a/frontend/src/pages/ExportPage.tsx +++ b/frontend/src/pages/ExportPage.tsx @@ -1,4 +1,4 @@ -import { useState, useEffect } from 'react' +import { useState } from 'react' import { useNavigate } from 'react-router-dom' import { useTranslation } from 'react-i18next' import { useQuery } from '@tanstack/react-query' @@ -13,7 +13,6 @@ import { FileJson, FileType, AlertCircle, - Settings, CheckCircle2, ArrowLeft, Loader2 diff --git a/frontend/src/pages/ProcessingPage.tsx b/frontend/src/pages/ProcessingPage.tsx index d1261e6..0cadcf7 100644 --- a/frontend/src/pages/ProcessingPage.tsx +++ b/frontend/src/pages/ProcessingPage.tsx @@ -12,13 +12,11 @@ import { Play, CheckCircle, FileText, AlertCircle, Clock, Activity, Loader2 } fr import LayoutModelSelector from '@/components/LayoutModelSelector' import PreprocessingSettings from '@/components/PreprocessingSettings' import PreprocessingPreview from '@/components/PreprocessingPreview' -import TableDetectionSelector from '@/components/TableDetectionSelector' import ProcessingTrackSelector from '@/components/ProcessingTrackSelector' -import OCRPresetSelector from '@/components/OCRPresetSelector' import TaskNotFound from '@/components/TaskNotFound' import { useTaskValidation } from '@/hooks/useTaskValidation' import { useTaskStore, useProcessingState } from '@/store/taskStore' -import type { LayoutModel, ProcessingOptions, PreprocessingMode, PreprocessingConfig, TableDetectionConfig, ProcessingTrack, OCRPreset, OCRConfig } from '@/types/apiV2' +import type { LayoutModel, ProcessingOptions, PreprocessingMode, PreprocessingConfig, ProcessingTrack } from '@/types/apiV2' export default function ProcessingPage() { const { t } = useTranslation() @@ -27,7 +25,9 @@ export default function ProcessingPage() { // Use TaskStore for processing state management const { startProcessing, stopProcessing, updateTaskStatus } = useTaskStore() - const processingState = useProcessingState() + // processingState is available for future use (e.g., displaying global processing status) + const _processingState = useProcessingState() + void _processingState // Suppress unused variable warning // Use shared hook for task validation const { taskId, taskDetail, isLoading: isValidating, isNotFound, clearAndReset } = useTaskValidation({ @@ -56,20 +56,9 @@ export default function ProcessingPage() { }) const [showPreview, setShowPreview] = useState(false) - // Table detection state - const [tableDetectionConfig, setTableDetectionConfig] = useState({ - enable_wired_table: true, - enable_wireless_table: true, - enable_region_detection: true, - }) - // Processing track override state (null = use system recommendation) const [forceTrack, setForceTrack] = useState(null) - // OCR Preset state (default to 'datasheet' for best balance) - const [ocrPreset, setOcrPreset] = useState('datasheet') - const [ocrConfig, setOcrConfig] = useState({}) - // Analyze document to determine if OCR is needed (only for pending tasks) const { data: documentAnalysis, isLoading: isAnalyzing } = useQuery({ queryKey: ['documentAnalysis', taskId], @@ -91,6 +80,8 @@ export default function ProcessingPage() { )) // Start OCR processing + // NOTE: Simple OCR mode - using backend defaults for table/chart/formula recognition + // Only layout_model and preprocessing options are configurable from frontend const processOCRMutation = useMutation({ mutationFn: () => { const options: ProcessingOptions = { @@ -100,9 +91,7 @@ export default function ProcessingPage() { layout_model: layoutModel, preprocessing_mode: preprocessingMode, preprocessing_config: preprocessingMode === 'manual' ? preprocessingConfig : undefined, - table_detection: tableDetectionConfig, - ocr_preset: ocrPreset, - ocr_config: ocrPreset === 'custom' ? ocrConfig : undefined, + // NOTE: table_detection, ocr_preset, ocr_config removed - using backend defaults } // Update TaskStore processing state @@ -448,15 +437,6 @@ export default function ProcessingPage() { {/* OCR Track Options - Only show when document needs OCR */} {needsOcrTrack && !isAnalyzing && ( <> - {/* OCR Processing Preset - Primary selection */} - - {/* Layout Model Selection */} - {/* Table Detection Settings */} - - {/* Preprocessing Settings */} { - setStatusFilter(e.target.value as any) + setStatusFilter(e.target.value as TaskStatus | 'all') handleFilterChange() }} options={[ diff --git a/frontend/src/pages/UploadPage.tsx b/frontend/src/pages/UploadPage.tsx index 99fe318..5bb10de 100644 --- a/frontend/src/pages/UploadPage.tsx +++ b/frontend/src/pages/UploadPage.tsx @@ -15,7 +15,7 @@ export default function UploadPage() { const navigate = useNavigate() const { toast } = useToast() const [selectedFiles, setSelectedFiles] = useState([]) - const { setBatchId, setFiles, setUploadProgress } = useUploadStore() + const { setBatchId, setUploadProgress } = useUploadStore() const uploadMutation = useMutation({ mutationFn: async (files: File[]) => { @@ -28,10 +28,10 @@ export default function UploadPage() { return tasks }, onSuccess: (tasks) => { - // For now, just use the first task_id as batch_id - // TODO: Update store to handle multiple tasks + // Use the first task_id as the current batch identifier + // Note: Type assertion needed - store expects number but API returns string UUID if (tasks.length > 0) { - setBatchId(tasks[0].task_id as any) // temporary workaround + setBatchId(tasks[0].task_id as unknown as number) } toast({ title: t('upload.uploadSuccess'), diff --git a/frontend/src/services/apiV2.ts b/frontend/src/services/apiV2.ts index 5717101..4a19a61 100644 --- a/frontend/src/services/apiV2.ts +++ b/frontend/src/services/apiV2.ts @@ -25,7 +25,6 @@ import type { SystemStats, UserWithStats, TopUser, - AuditLog, AuditLogListResponse, UserActivitySummary, ProcessingOptions, @@ -55,7 +54,7 @@ class ApiClientV2 { private token: string | null = null private userInfo: UserInfo | null = null private tokenExpiresAt: number | null = null - private refreshTimer: NodeJS.Timeout | null = null + private refreshTimer: ReturnType | null = null private isRefreshing: boolean = false private refreshFailed: boolean = false diff --git a/frontend/src/store/taskStore.ts b/frontend/src/store/taskStore.ts index b8accae..324b40c 100644 --- a/frontend/src/store/taskStore.ts +++ b/frontend/src/store/taskStore.ts @@ -140,12 +140,16 @@ export const useTaskStore = create()( updateTaskCache: (task) => { set((state) => { const taskId = 'task_id' in task ? task.task_id : task.taskId + // Extract processing track from either Task (snake_case) or CachedTask (camelCase) + const track = 'processing_track' in task + ? task.processing_track + : ('processingTrack' in task ? task.processingTrack : undefined) const cached: CachedTask = { taskId, filename: task.filename || null, status: task.status, updatedAt: new Date().toISOString(), - processingTrack: 'processing_track' in task ? task.processing_track : task.processingTrack, + processingTrack: track, } // Remove existing entry if present diff --git a/frontend/src/types/apiV2.ts b/frontend/src/types/apiV2.ts index 4c42822..6397258 100644 --- a/frontend/src/types/apiV2.ts +++ b/frontend/src/types/apiV2.ts @@ -111,71 +111,6 @@ export interface PreprocessingConfig { remove_scan_artifacts: boolean // Remove horizontal scan line artifacts } -/** - * Table detection configuration for PP-StructureV3. - * Controls which table detection modes to enable. - * - enable_wired_table: Tables with visible cell borders/grid lines - * - enable_wireless_table: Tables without visible borders - * - enable_region_detection: Detect table-like regions for better cell structure - */ -export interface TableDetectionConfig { - enable_wired_table: boolean - enable_wireless_table: boolean - enable_region_detection: boolean -} - -/** - * OCR processing preset for different document types. - * Presets provide optimized PP-Structure configurations for common document types. - */ -export type OCRPreset = 'text_heavy' | 'datasheet' | 'table_heavy' | 'form' | 'mixed' | 'custom' - -/** - * Table parsing mode controlling how aggressively tables are parsed. - * - full: Full table recognition with cell segmentation (aggressive) - * - conservative: Disable wireless tables to prevent cell explosion - * - classification_only: Only classify table regions, no cell segmentation - * - disabled: Completely disable table recognition - */ -export type TableParsingMode = 'full' | 'conservative' | 'classification_only' | 'disabled' - -/** - * OCR processing configuration for PP-Structure. - * Allows fine-grained control over PP-Structure parameters. - */ -export interface OCRConfig { - // Table Processing - table_parsing_mode?: TableParsingMode - enable_wired_table?: boolean - enable_wireless_table?: boolean - - // Layout Detection - layout_threshold?: number | null // 0.0-1.0 - layout_nms_threshold?: number | null // 0.0-1.0 - - // Preprocessing - use_doc_orientation_classify?: boolean - use_doc_unwarping?: boolean - use_textline_orientation?: boolean - - // Recognition Modules - enable_chart_recognition?: boolean - enable_formula_recognition?: boolean - enable_seal_recognition?: boolean - enable_region_detection?: boolean -} - -/** - * Preset configuration metadata for display purposes. - */ -export interface OCRPresetInfo { - name: OCRPreset - displayName: string - description: string - icon: string - config: OCRConfig -} - /** * Image quality metrics from auto-analysis. */ @@ -213,9 +148,6 @@ export interface ProcessingOptions { layout_model?: LayoutModel // Layout detection model selection (OCR track only) preprocessing_mode?: PreprocessingMode // Preprocessing mode (OCR track only) preprocessing_config?: PreprocessingConfig // Manual preprocessing config - table_detection?: TableDetectionConfig // Table detection options (OCR track only) - ocr_preset?: OCRPreset // OCR processing preset (OCR track only) - ocr_config?: OCRConfig // Custom OCR config (overrides preset values) } export interface TaskCreate { diff --git a/openspec/changes/archive/2025-12-11-cleanup-dead-code/proposal.md b/openspec/changes/archive/2025-12-11-cleanup-dead-code/proposal.md new file mode 100644 index 0000000..411b28b --- /dev/null +++ b/openspec/changes/archive/2025-12-11-cleanup-dead-code/proposal.md @@ -0,0 +1,175 @@ +# Change: Cleanup Dead Code and Improve Code Quality + +## Why + +深度代碼盤點發現專案中存在以下問題： +1. 已廢棄但未刪除的服務文件（507行） +2. 過時的配置項（已標記 deprecated 但未移除） +3. 重複的 bbox 處理邏輯散落在 4 個文件中 +4. 未使用的 imports 和類型斷言問題 +5. 多個 TODO 標記需要處理或移除 +6. **Paddle/PP-Structure 相關的禁用功能和補丁代碼** + +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。 + +## What Changes + +### Phase 1: 刪除廢棄文件 (高優先級) + +| 文件 | 行數 | 原因 | +|------|------|------| +| `backend/app/services/pdf_generator.py` | 507 | 已被 `pdf_generator_service.py` 完全替代，無任何引用 | + +### Phase 2: 移除過時配置 (高優先級) + +| 文件 | 配置項 | 原因 | +|------|--------|------| +| `backend/app/core/config.py` | `gap_filling_iou_threshold` | 已過時，應使用 IoA 閾值 | +| `backend/app/core/config.py` | `gap_filling_dedup_iou_threshold` | 已過時，應使用 `gap_filling_dedup_ioa_threshold` | + +### Phase 3: 提取共用 bbox 工具函數 (中優先級) + +創建 `backend/app/utils/bbox_utils.py`，統一以下位置的重複邏輯： + +| 文件 | 函數 | 行號 | +|------|------|------| +| `gap_filling_service.py` | `normalized_bbox` property | L51 | +| `pdf_generator_service.py` | `_get_bbox_coords` | L1859 | +| `pp_structure_debug.py` | `_normalize_bbox` | L240 | +| `text_region_renderer.py` | `get_bbox_as_rect` | L162 | + +### Phase 4: 前端代碼清理 (低優先級) + +| 文件 | 問題 | 行號 | +|------|------|------| +| `ExportPage.tsx` | 未使用的 `CardDescription` import | L5 | +| `UploadPage.tsx` | `as any` 類型斷言 + TODO | L32-34 | +| `TaskHistoryPage.tsx` | `as any` 類型斷言 | L337 | +| `useTaskValidation.ts` | `as any` 類型斷言 | L61 | + +### Phase 5: 清理禁用的表格補丁功能 (中優先級) + +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： + +| 服務文件 | 配置項 | 狀態 | 說明 | 建議 | +|----------|--------|------|------|------| +| `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 | +| `table_content_rebuilder.py` | `table_content_rebuilder_enabled` | False | 從 Raw OCR 重建表格 HTML | **可刪除** - 補丁行為 | +| - | `table_quality_check_enabled` | False | 單元格框質量檢查 | **移除配置** - 未完全實現 | +| - | `table_rendering_prefer_cellboxes` | False | 算法需改進 | **移除配置** - 算法有誤 | + +### Phase 6: 評估 PP-Structure 模型使用 (需討論) + +#### 當前使用的模型 (11個) + +**必需模型 (3個) - 核心 OCR 功能** +| 模型 | 用途 | 狀態 | +|------|------|------| +| `PP-DocLayout_plus-L` | 佈局檢測 | **必需** | +| `PP-OCRv5_server_det` | 文本檢測 | **必需** | +| `PP-OCRv5_server_rec` | 文本識別 | **必需** | + +**表格相關模型 (5個) - 可選但啟用** +| 模型 | 用途 | 狀態 | 記憶體 | +|------|------|------|--------| +| `SLANeXt_wired` | 有邊框表格結構識別 | 啟用 | ~350MB | +| `SLANeXt_wireless` | 無邊框表格結構識別 | **保守模式下禁用** | ~350MB | +| `PP-LCNet_x1_0_table_cls` | 表格分類 | 啟用 | ~50MB | +| `RT-DETR-L_wired_table_cell_det` | 有邊框單元格檢測 | 啟用 | 共享 | +| `RT-DETR-L_wireless_table_cell_det` | 無邊框單元格檢測 | **保守模式下禁用** | 共享 | + +**增強功能模型 (2個) - 可選** +| 模型 | 用途 | 狀態 | 是否需要 | +|------|------|------|----------| +| `PP-FormulaNet_plus-L` | 公式轉 LaTeX | 啟用 | 視需求，可禁用節省 ~300MB | +| `PP-Chart2Table` | 圖表轉表格 | 啟用 | 視需求，可禁用節省 ~200MB | + +**預處理模型 (3個)** +| 模型 | 用途 | 狀態 | 建議 | +|------|------|------|------| +| `PP-LCNet_x1_0_doc_ori` | 文檔方向檢測 | 啟用 | 保留 | +| `PP-LCNet_x1_0_textline_ori` | 文本行方向檢測 | 啟用 | 保留 | +| `UVDoc` | 文檔變形修正 | **禁用** | **可移除配置** - 會導致文檔失真 | + +#### 禁用的 Gap Filling 功能 + +| 配置項 | 狀態 | 相關代碼 | 建議 | +|--------|------|----------|------| +| `gap_filling_enabled` | False | `gap_filling_service.py` | 保留代碼，作為可選增強 | +| `gap_filling_iou_threshold` | 過時 | config.py | **刪除** - 已被 IoA 閾值取代 | +| `gap_filling_dedup_iou_threshold` | 過時 | config.py | **刪除** - 已被 IoA 閾值取代 | + +## Impact + +- **Affected specs**: 無（純代碼清理，不改變系統行為） +- **Affected code**: + - Backend: 刪除 1-3 個文件，修改 config.py，創建 bbox_utils.py + - Frontend: 修改 4 個文件（類型改進） +- **記憶體影響**: 如移除無邊框表格模型，可節省 ~700MB GPU 記憶體 + +## Benefits + +- 減少約 **600-1,500 行**冗餘代碼（視 Phase 5-6 範圍） +- 統一 bbox 處理邏輯，減少重複代碼 **80-100 行** +- 提升 TypeScript 類型安全性 +- 移除過時配置和補丁代碼，減少維護負擔 +- 精簡 PP-Structure 模型配置，提升可讀性 + +## Risk Assessment + +- **風險等級**: 低-中 +- **Phase 1-2**: 無風險（刪除未使用的代碼） +- **Phase 3**: 低風險（重構，需要測試） +- **Phase 4**: 低風險（類型改進） +- **Phase 5**: 低風險（刪除禁用的補丁代碼） +- **Phase 6**: 中風險（需評估模型是否還需要） +- **回滾策略**: Git revert + +## Paddle/PP-Structure 使用情況摘要 + +### 直接使用 Paddle 的文件 (僅 3 個) + +| 文件 | 行數 | 功能 | +|------|------|------| +| `ocr_service.py` | ~2,590 | OCR 引擎管理、GPU 配置、模型卸載 | +| `pp_structure_enhanced.py` | ~1,324 | PP-StructureV3 結果解析、元素提取 | +| `memory_manager.py` | ~2,269 | GPU 記憶體監控、多後端支持 | + +### 表格解析模式 (table_parsing_mode) + +| 模式 | 說明 | 適用場景 | +|------|------|----------| +| `full` | 激進，完整表格檢測 | 表格密集的文檔 | +| `conservative` | **當前使用**，禁用無邊框表格 | 混合文檔 | +| `classification_only` | 僅識別表格區域，無結構解析 | 數據表/電子表格 | +| `disabled` | 完全禁用表格識別 | 純文本文檔 | + +### 補丁 vs 核心功能分類 + +``` +┌─────────────────────────────────────────────────────────────┐ +│ 核心功能 (必須保留) │ +├─────────────────────────────────────────────────────────────┤ +│ • PaddleOCR 文本識別 │ +│ • PP-DocLayout 佈局檢測 │ +│ • SLANeXt 表格結構識別 │ +│ • 記憶體管理和自動卸載 │ +└─────────────────────────────────────────────────────────────┘ + +┌─────────────────────────────────────────────────────────────┐ +│ 補丁功能 (建議移除) │ +├─────────────────────────────────────────────────────────────┤ +│ • cell_validation_engine.py - 過度檢測過濾 │ +│ • table_content_rebuilder.py - 表格內容重建 │ +│ • table_quality_check - 未完全實現 │ +│ • table_rendering_prefer_cellboxes - 算法有誤 │ +└─────────────────────────────────────────────────────────────┘ + +┌─────────────────────────────────────────────────────────────┐ +│ 可選增強 (保留代碼，按需啟用) │ +├─────────────────────────────────────────────────────────────┤ +│ • gap_filling_service.py - OCR 補充遺漏區域 │ +│ • PP-FormulaNet - 公式識別 │ +│ • PP-Chart2Table - 圖表識別 │ +└─────────────────────────────────────────────────────────────┘ +``` diff --git a/openspec/changes/archive/2025-12-11-cleanup-dead-code/specs/document-processing/spec.md b/openspec/changes/archive/2025-12-11-cleanup-dead-code/specs/document-processing/spec.md new file mode 100644 index 0000000..2d467ce --- /dev/null +++ b/openspec/changes/archive/2025-12-11-cleanup-dead-code/specs/document-processing/spec.md @@ -0,0 +1,42 @@ +## REMOVED Requirements + +### Requirement: Legacy PDF Generator Service + +**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. + +**Migration**: No migration needed. The new `pdf_generator_service.py` provides all functionality with improved features. + +#### Scenario: Legacy PDF generator file removal +- **WHEN** the legacy `pdf_generator.py` file is removed +- **THEN** the system continues to function normally using `pdf_generator_service.py` +- **AND** PDF generation works correctly with layout preservation +- **AND** no import errors occur in any service or router + +### Requirement: Deprecated IoU Configuration Parameters + +**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. + +**Migration**: Use `gap_filling_dedup_ioa_threshold` instead. + +#### Scenario: Deprecated config removal +- **WHEN** the deprecated IoU configuration parameters are removed from config.py +- **THEN** gap filling service uses IoA-based thresholds +- **AND** the system starts without configuration errors + +## ADDED Requirements + +### Requirement: Unified Bbox Utility Module + +The system SHALL provide a centralized bbox utility module (`backend/app/utils/bbox_utils.py`) for consistent bounding box normalization across all services. + +#### Scenario: Bbox normalization from polygon format +- **WHEN** a bbox in polygon format `[[x1,y1], [x2,y2], [x3,y3], [x4,y4]]` is provided +- **THEN** the utility returns normalized tuple `(x0, y0, x1, y1)` representing min/max coordinates + +#### Scenario: Bbox normalization from flat array +- **WHEN** a bbox in flat array format `[x0, y0, x1, y1]` is provided +- **THEN** the utility returns normalized tuple `(x0, y0, x1, y1)` + +#### Scenario: Bbox normalization from 8-point polygon +- **WHEN** a bbox in 8-point format `[x1, y1, x2, y2, x3, y3, x4, y4]` is provided +- **THEN** the utility calculates and returns normalized tuple `(min_x, min_y, max_x, max_y)` diff --git a/openspec/changes/archive/2025-12-11-cleanup-dead-code/tasks.md b/openspec/changes/archive/2025-12-11-cleanup-dead-code/tasks.md new file mode 100644 index 0000000..0c1a307 --- /dev/null +++ b/openspec/changes/archive/2025-12-11-cleanup-dead-code/tasks.md @@ -0,0 +1,92 @@ +# Tasks: Cleanup Dead Code and Improve Code Quality + +## Phase 1: 刪除廢棄文件 (高優先級, ~30分鐘) + +- [x] 1.1 確認 `pdf_generator.py` 無任何引用 +- [x] 1.2 刪除 `backend/app/services/pdf_generator.py` +- [x] 1.3 驗證後端啟動正常 + +## Phase 2: 移除過時配置 (高優先級, ~15分鐘) + +- [x] 2.1 移除 `config.py` 中的 `gap_filling_iou_threshold` +- [x] 2.2 移除 `config.py` 中的 `gap_filling_dedup_iou_threshold` +- [x] 2.3 搜索並更新任何使用這些配置的代碼 +- [x] 2.4 驗證後端啟動正常 + +## Phase 3: 提取共用 bbox 工具函數 (中優先級, ~2小時) + +- [x] 3.1 創建 `backend/app/utils/__init__.py`（如不存在） +- [x] 3.2 創建 `backend/app/utils/bbox_utils.py`，實現統一的 bbox 處理函數 +- [x] 3.3 重構 `gap_filling_service.py` 使用共用函數 +- [x] 3.4 重構 `pdf_generator_service.py` 使用共用函數 +- [x] 3.5 重構 `pp_structure_debug.py` 使用共用函數 +- [x] 3.6 重構 `text_region_renderer.py` 使用共用函數 +- [x] 3.7 測試所有相關功能正常 + +## Phase 4: 前端代碼清理 (低優先級, ~1小時) + +- [x] 4.1 移除 `ExportPage.tsx` 中未使用的 `CardDescription` import (SKIPPED - actually used) +- [x] 4.2 重構 `UploadPage.tsx` 的 `as any` 類型斷言 (improved to `as unknown as number`) +- [x] 4.3 處理或移除 `UploadPage.tsx` 中的 TODO 註釋 (comment improved) +- [x] 4.4 重構 `TaskHistoryPage.tsx` 的 `as any` 類型斷言 (changed to `as TaskStatus | 'all'`) +- [x] 4.5 重構 `useTaskValidation.ts` 的 `as any` 類型斷言 (using `instanceof AxiosError`) +- [x] 4.6 驗證前端編譯正常 (pre-existing errors not from our changes) + +## Phase 5: 清理禁用的表格補丁功能 (中優先級, ~1小時) + +- [x] 5.1 移除 `cell_validation_engine.py` 整個文件（已禁用的補丁功能） +- [x] 5.2 移除 `table_content_rebuilder.py` 整個文件（已禁用的補丁功能） +- [x] 5.3 移除 `config.py` 中的 `cell_validation_enabled` 配置 +- [x] 5.4 移除 `config.py` 中的 `table_content_rebuilder_enabled` 配置 +- [x] 5.5 移除 `config.py` 中的 `table_quality_check_enabled` 配置 +- [x] 5.6 移除 `config.py` 中的 `table_rendering_prefer_cellboxes` 配置 +- [x] 5.7 搜索並清理所有引用這些配置的代碼 +- [x] 5.8 驗證後端啟動正常 + +## Phase 6: 評估 PP-Structure 模型使用 (需討論, ~2小時) + +### 6.1 必需模型 (不可移除) +- [x] 6.1.1 確認 `PP-DocLayout_plus-L` 佈局檢測使用中 +- [x] 6.1.2 確認 `PP-OCRv5_server_det` 文本檢測使用中 +- [x] 6.1.3 確認 `PP-OCRv5_server_rec` 文本識別使用中 + +### 6.2 表格相關模型 (評估是否需要) +- [x] 6.2.1 評估 `SLANeXt_wired` 有邊框表格結構識別 (保留 - 核心功能) +- [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) +- [x] 6.2.3 評估 `PP-LCNet_x1_0_table_cls` 表格分類器 (保留 - 核心功能) +- [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) +- [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) + +### 6.3 增強功能模型 (可選禁用) +- [x] 6.3.1 評估 `PP-FormulaNet_plus-L` 公式識別（~300MB）(保留 - 可選功能) +- [x] 6.3.2 評估 `PP-Chart2Table` 圖表識別（~200MB）(保留 - 可選功能) + +### 6.4 預處理模型 +- [x] 6.4.1 確認 `PP-LCNet_x1_0_doc_ori` 文檔方向檢測使用中 +- [x] 6.4.2 確認 `PP-LCNet_x1_0_textline_ori` 文本行方向檢測使用中 +- [x] 6.4.3 移除 `UVDoc` 文檔變形修正配置 (保留 - 已禁用但可選) + +### 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** | - | - | diff --git a/openspec/changes/fix-ocr-track-table-rendering/design.md b/openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/design.md similarity index 100% rename from openspec/changes/fix-ocr-track-table-rendering/design.md rename to openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/design.md diff --git a/openspec/changes/fix-ocr-track-table-rendering/proposal.md b/openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/proposal.md similarity index 100% rename from openspec/changes/fix-ocr-track-table-rendering/proposal.md rename to openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/proposal.md diff --git a/openspec/changes/fix-ocr-track-table-rendering/specs/ocr-processing/spec.md b/openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/specs/ocr-processing/spec.md similarity index 100% rename from openspec/changes/fix-ocr-track-table-rendering/specs/ocr-processing/spec.md rename to openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/specs/ocr-processing/spec.md diff --git a/openspec/changes/fix-ocr-track-table-rendering/tasks.md b/openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/tasks.md similarity index 100% rename from openspec/changes/fix-ocr-track-table-rendering/tasks.md rename to openspec/changes/archive/2025-12-11-fix-ocr-track-table-rendering/tasks.md diff --git a/openspec/changes/fix-table-column-alignment/design.md b/openspec/changes/archive/2025-12-11-fix-table-column-alignment/design.md similarity index 100% rename from openspec/changes/fix-table-column-alignment/design.md rename to openspec/changes/archive/2025-12-11-fix-table-column-alignment/design.md diff --git a/openspec/changes/fix-table-column-alignment/proposal.md b/openspec/changes/archive/2025-12-11-fix-table-column-alignment/proposal.md similarity index 100% rename from openspec/changes/fix-table-column-alignment/proposal.md rename to openspec/changes/archive/2025-12-11-fix-table-column-alignment/proposal.md diff --git a/openspec/changes/fix-table-column-alignment/specs/document-processing/spec.md b/openspec/changes/archive/2025-12-11-fix-table-column-alignment/specs/document-processing/spec.md similarity index 100% rename from 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similarity index 100% rename from openspec/changes/improve-ocr-track-algorithm/specs/ocr-processing/spec.md rename to openspec/changes/archive/2025-12-11-improve-ocr-track-algorithm/specs/ocr-processing/spec.md diff --git a/openspec/changes/improve-ocr-track-algorithm/tasks.md b/openspec/changes/archive/2025-12-11-improve-ocr-track-algorithm/tasks.md similarity index 100% rename from openspec/changes/improve-ocr-track-algorithm/tasks.md rename to openspec/changes/archive/2025-12-11-improve-ocr-track-algorithm/tasks.md diff --git a/openspec/changes/remove-unused-code/proposal.md b/openspec/changes/archive/2025-12-11-remove-unused-code/proposal.md similarity index 100% rename from openspec/changes/remove-unused-code/proposal.md rename to openspec/changes/archive/2025-12-11-remove-unused-code/proposal.md diff --git a/openspec/changes/remove-unused-code/specs/document-processing/spec.md b/openspec/changes/archive/2025-12-11-remove-unused-code/specs/document-processing/spec.md similarity 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rename to openspec/changes/archive/2025-12-11-simple-text-positioning/proposal.md diff --git a/openspec/changes/simple-text-positioning/tasks.md b/openspec/changes/archive/2025-12-11-simple-text-positioning/tasks.md similarity index 100% rename from openspec/changes/simple-text-positioning/tasks.md rename to openspec/changes/archive/2025-12-11-simple-text-positioning/tasks.md diff --git a/openspec/changes/use-cellboxes-for-table-rendering/design.md b/openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/design.md similarity index 100% rename from openspec/changes/use-cellboxes-for-table-rendering/design.md rename to openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/design.md diff --git a/openspec/changes/use-cellboxes-for-table-rendering/proposal.md b/openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/proposal.md similarity index 100% rename from openspec/changes/use-cellboxes-for-table-rendering/proposal.md rename to openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/proposal.md diff --git a/openspec/changes/use-cellboxes-for-table-rendering/specs/document-processing/spec.md b/openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/specs/document-processing/spec.md similarity index 100% rename from openspec/changes/use-cellboxes-for-table-rendering/specs/document-processing/spec.md rename to openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/specs/document-processing/spec.md diff --git a/openspec/changes/use-cellboxes-for-table-rendering/tasks.md b/openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/tasks.md similarity index 100% rename from openspec/changes/use-cellboxes-for-table-rendering/tasks.md rename to openspec/changes/archive/2025-12-11-use-cellboxes-for-table-rendering/tasks.md diff --git a/openspec/changes/enable-doc-orientation-detection/proposal.md b/openspec/changes/enable-doc-orientation-detection/proposal.md new file mode 100644 index 0000000..59a98d8 --- /dev/null +++ b/openspec/changes/enable-doc-orientation-detection/proposal.md @@ -0,0 +1,52 @@ +# Enable Document Orientation Detection + +## Summary +Enable PP-StructureV3's document orientation classification feature to correctly handle PDF scans where the content orientation differs from the PDF page metadata. + +## Problem Statement +Currently, when a portrait-oriented PDF contains landscape-scanned content (or vice versa), the OCR system produces incorrect results because: + +1. **pdf2image** extracts images based on PDF metadata (e.g., `Page size: 1242 x 1755`, `Page rot: 0`) +2. **PP-StructureV3** has `use_doc_orientation_classify=False` (disabled) +3. The OCR attempts to read sideways text, resulting in poor recognition +4. The output PDF has wrong page dimensions + +### Example Scenario +- Input: Portrait PDF (1242 x 1755) containing landscape-scanned delivery form +- Current output: Portrait PDF with unreadable/incorrect text +- Expected output: Landscape PDF (1755 x 1242) with correctly oriented text + +## Proposed Solution +Enable document orientation detection in PP-StructureV3 and adjust page dimensions based on the detected rotation: + +1. **Enable orientation detection**: Set `use_doc_orientation_classify=True` in config +2. **Capture rotation info**: Extract the detected rotation angle (0°/90°/180°/270°) from PP-StructureV3 results +3. **Adjust dimensions**: When 90° or 270° rotation is detected, swap width and height for the output PDF +4. **Use OCR coordinates directly**: PP-StructureV3 returns coordinates based on the rotated image, so no coordinate transformation is needed + +## PP-StructureV3 Orientation Detection Details +According to PaddleOCR documentation: +- **Stage 1 preprocessing**: `use_doc_orientation_classify` detects and rotates the entire page +- **Output format**: `doc_preprocessor_res` contains: + - `class_ids`: [0-3] corresponding to [0°, 90°, 180°, 270°] + - `label_names`: ["0", "90", "180", "270"] + - `scores`: confidence scores +- **Model accuracy**: PP-LCNet_x1_0_doc_ori achieves 99.06% top-1 accuracy + +## Scope +- Backend only (no frontend changes required) +- Affects OCR track processing +- Does not affect Direct or Hybrid track + +## Risks and Mitigations +| Risk | Mitigation | +|------|------------| +| Model might incorrectly classify mixed-orientation pages | 99.06% accuracy is acceptable; `use_textline_orientation` (already enabled) handles per-line correction | +| Coordinate mismatch in edge cases | Thorough testing with portrait, landscape, and mixed documents | +| Performance overhead | Orientation classification adds ~100ms per page (negligible vs total OCR time) | + +## Success Criteria +1. Portrait PDF with landscape content produces landscape output PDF +2. Landscape PDF with portrait content produces portrait output PDF +3. Normal orientation documents continue to work correctly +4. Text recognition accuracy improves for rotated documents diff --git a/openspec/changes/enable-doc-orientation-detection/specs/ocr-processing/spec.md b/openspec/changes/enable-doc-orientation-detection/specs/ocr-processing/spec.md new file mode 100644 index 0000000..7f3dbf0 --- /dev/null +++ b/openspec/changes/enable-doc-orientation-detection/specs/ocr-processing/spec.md @@ -0,0 +1,80 @@ +# ocr-processing Specification Delta + +## ADDED Requirements + +### Requirement: Document Orientation Detection + +The system SHALL detect and correct document orientation for scanned PDFs where the content orientation differs from PDF page metadata. + +#### Scenario: Portrait PDF with landscape content is corrected +- **GIVEN** a PDF with portrait page dimensions (width < height) +- **AND** the scanned content is rotated 90° (landscape scan in portrait page) +- **WHEN** PP-StructureV3 processes the image with `use_doc_orientation_classify=True` +- **THEN** the system SHALL detect rotation angle as "90" or "270" +- **AND** the output PDF page dimensions SHALL be swapped (width ↔ height) +- **AND** all text elements SHALL be correctly positioned in the rotated coordinate space + +#### Scenario: Landscape PDF with portrait content is corrected +- **GIVEN** a PDF with landscape page dimensions (width > height) +- **AND** the scanned content is rotated 90° (portrait scan in landscape page) +- **WHEN** PP-StructureV3 processes the image +- **THEN** the system SHALL detect rotation angle as "90" or "270" +- **AND** the output PDF page dimensions SHALL be swapped +- **AND** all text elements SHALL be correctly positioned + +#### Scenario: Upside-down content is corrected +- **GIVEN** a scanned document that is upside down (180° rotation) +- **WHEN** PP-StructureV3 processes the image +- **THEN** the system SHALL detect rotation angle as "180" +- **AND** page dimensions SHALL NOT be swapped (orientation is same, just flipped) +- **AND** text elements SHALL be correctly positioned after internal rotation + +#### Scenario: Correctly oriented documents remain unchanged +- **GIVEN** a PDF where page metadata matches actual content orientation +- **WHEN** PP-StructureV3 processes the image +- **THEN** the system SHALL detect rotation angle as "0" +- **AND** page dimensions SHALL remain unchanged +- **AND** processing SHALL proceed normally without dimension adjustment + +#### Scenario: Rotation angle is captured from PP-StructureV3 results +- **GIVEN** PP-StructureV3 is configured with `use_doc_orientation_classify=True` +- **WHEN** processing completes +- **THEN** the system SHALL extract rotation angle from `doc_preprocessor_res.label_names` +- **AND** include `detected_rotation` in the OCR result metadata +- **AND** log the detected rotation for debugging + +#### Scenario: Dimension adjustment happens before PDF generation +- **GIVEN** OCR processing detects rotation angle of "90" or "270" +- **WHEN** creating the UnifiedDocument for PDF generation +- **THEN** the Page dimensions SHALL use adjusted (swapped) width and height +- **AND** OCR coordinates SHALL be used directly (already in rotated space) +- **AND** no additional coordinate transformation is needed + +### Requirement: Orientation Detection Configuration + +The system SHALL provide configuration for enabling/disabling document orientation detection. + +#### Scenario: Orientation detection is enabled by default +- **GIVEN** default configuration settings +- **WHEN** OCR track processing runs +- **THEN** `use_doc_orientation_classify` SHALL be `True` +- **AND** PP-StructureV3 SHALL perform document orientation classification + +#### Scenario: Orientation detection can be disabled +- **GIVEN** `use_doc_orientation_classify` is set to `False` in configuration +- **WHEN** OCR track processing runs +- **THEN** the system SHALL NOT perform orientation detection +- **AND** page dimensions SHALL be based on original image dimensions +- **AND** this maintains backward compatibility for controlled environments + +## MODIFIED Requirements + +### Requirement: Layout Model Selection (Modified) + +The system SHALL apply document orientation detection before layout detection regardless of the selected layout model. + +#### Scenario: Orientation detection works with all layout models +- **GIVEN** a user selects any layout model (chinese, default, cdla) +- **WHEN** OCR processing runs with `use_doc_orientation_classify=True` +- **THEN** orientation detection SHALL be applied regardless of layout model choice +- **AND** orientation detection happens in Stage 1 (preprocessing) before layout detection (Stage 3) diff --git a/openspec/changes/enable-doc-orientation-detection/tasks.md b/openspec/changes/enable-doc-orientation-detection/tasks.md new file mode 100644 index 0000000..f355817 --- /dev/null +++ b/openspec/changes/enable-doc-orientation-detection/tasks.md @@ -0,0 +1,71 @@ +# Tasks + +## Phase 1: Enable Orientation Detection + +- [x] **Task 1.1**: Enable `use_doc_orientation_classify` in config + - File: `backend/app/core/config.py` + - Change: Set `use_doc_orientation_classify: bool = Field(default=True)` + - Update comment to reflect new behavior + +- [x] **Task 1.2**: Capture rotation info from PP-StructureV3 results + - File: `backend/app/services/pp_structure_enhanced.py` + - Extract `doc_preprocessor_res` from PP-StructureV3 output + - Parse `label_names` to get detected rotation angle + - Pass rotation angle to caller + +## Phase 2: Dimension Adjustment + +- [x] **Task 2.1**: Add rotation angle to OCR result + - File: `backend/app/services/ocr_service.py` + - Receive rotation angle from `analyze_layout()` + - Include `detected_rotation` in result dict + +- [x] **Task 2.2**: Adjust page dimensions based on rotation + - File: `backend/app/services/ocr_service.py` + - In `process_image()`, after getting `ocr_width, ocr_height` from PIL + - If `detected_rotation` is "90" or "270", swap dimensions + - Log dimension adjustment for debugging + +- [x] **Task 2.3**: Pass adjusted dimensions to UnifiedDocument + - File: `backend/app/services/ocr_to_unified_converter.py` + - Verified: `Page.dimensions` uses the adjusted width/height from `enhanced_results` + - No coordinate transformation needed (already based on rotated image) + +## Phase 3: Testing & Validation + +- [ ] **Task 3.1**: Test with portrait PDF containing landscape scan + - Verify output PDF is landscape + - Verify text is correctly oriented + - Verify text positioning is accurate + +- [ ] **Task 3.2**: Test with landscape PDF containing portrait scan + - Verify output PDF is portrait + - Verify text is correctly oriented + +- [ ] **Task 3.3**: Test with correctly oriented documents + - Verify no regression for normal documents + - Both portrait and landscape normal scans + +- [ ] **Task 3.4**: Test edge cases + - 180° rotated documents (upside down) + - Documents with mixed text orientations + +## Dependencies +- Task 1.1 and 1.2 can be done in parallel +- Task 2.1 depends on Task 1.2 +- Task 2.2 depends on Task 2.1 +- Task 2.3 depends on Task 2.2 +- All Phase 3 tasks depend on Phase 2 completion + +## Implementation Summary + +### Files Modified: +1. `backend/app/core/config.py` - Enabled `use_doc_orientation_classify=True` +2. `backend/app/services/pp_structure_enhanced.py` - Extract and return `detected_rotation` +3. `backend/app/services/ocr_service.py` - Adjust dimensions and add rotation to result + +### Key Changes: +- PP-StructureV3 now detects document orientation (0°/90°/180°/270°) +- When 90° or 270° rotation detected, page dimensions are swapped (width ↔ height) +- `detected_rotation` is included in OCR result for debugging/logging +- Coordinates from PP-StructureV3 are already in the rotated coordinate space diff --git a/openspec/changes/simplify-frontend-ocr-config/proposal.md b/openspec/changes/simplify-frontend-ocr-config/proposal.md new file mode 100644 index 0000000..e5aca50 --- /dev/null +++ b/openspec/changes/simplify-frontend-ocr-config/proposal.md @@ -0,0 +1,25 @@ +# Change: 簡化前端 OCR 配置選項 + +## Why +OCR track 已改為使用 simple OCR 模式，不再需要前端的複雜配置選項（如表格偵測模式、OCR 預設、進階參數等）。這些配置增加了使用者的認知負擔，且不再影響實際處理結果。 + +## What Changes +- **BREAKING** 移除前端的 OCR 處理預設選擇器 (`OCRPresetSelector`) +- **BREAKING** 移除前端的表格偵測配置選擇器 (`TableDetectionSelector`) +- **BREAKING** 移除前端相關的 TypeScript 類型定義 (`OCRPreset`, `OCRConfig`, `TableDetectionConfig`, `TableParsingMode` 等) +- 保留版面模型選擇功能 (`LayoutModelSelector`): `chinese | default | cdla` +- 保留影像前處理配置功能 (`PreprocessingSettings`): auto/manual/disabled 模式及相關參數 +- 簡化後端 API 的 `ProcessingOptions`，移除不再使用的參數 + +## Impact +- Affected specs: `ocr-processing` +- Affected code: + - **前端需刪除的檔案**: + - `frontend/src/components/OCRPresetSelector.tsx` + - `frontend/src/components/TableDetectionSelector.tsx` + - **前端需修改的檔案**: + - `frontend/src/types/apiV2.ts` - 移除未使用的類型定義 + - `frontend/src/pages/ProcessingPage.tsx` - 移除已註解的相關 import 和邏輯 + - **後端需修改的檔案**: + - `backend/app/schemas/task.py` - 移除 `ProcessingOptions` 中的 `ocr_preset`, `ocr_config`, `table_detection` 欄位 + - `backend/app/routers/tasks.py` - 清理對應的參數處理邏輯 diff --git a/openspec/changes/simplify-frontend-ocr-config/specs/ocr-processing/spec.md b/openspec/changes/simplify-frontend-ocr-config/specs/ocr-processing/spec.md new file mode 100644 index 0000000..a3c89f4 --- /dev/null +++ b/openspec/changes/simplify-frontend-ocr-config/specs/ocr-processing/spec.md @@ -0,0 +1,127 @@ +# ocr-processing Specification Delta + +## REMOVED Requirements + +### Requirement: OCR Preset Selection +**Reason**: OCR track 已改為 simple OCR 模式，不再需要前端提供複雜的預設配置。後端統一使用預設參數處理。 +**Migration**: 移除前端 `OCRPresetSelector` 組件及相關類型定義。後端自動使用最佳預設配置。 + +### Requirement: Table Detection Configuration +**Reason**: 表格偵測設定（有框線/無框線表格開關、區域偵測開關）不再需要由前端控制。後端統一使用預設的表格偵測策略。 +**Migration**: 移除前端 `TableDetectionSelector` 組件及 `TableDetectionConfig` 類型。後端使用內建預設值。 + +### Requirement: OCR Advanced Parameters +**Reason**: 進階 OCR 參數（如 `table_parsing_mode`, `layout_threshold`, `enable_chart_recognition` 等）不再需要前端配置。 +**Migration**: 移除前端 `OCRConfig` 類型及相關 UI。後端固定使用 simple OCR 模式的預設參數。 + +## MODIFIED Requirements + +### Requirement: Layout Model Selection +The system SHALL allow users to select a layout detection model optimized for their document type, providing a simple choice between pre-configured models instead of manual parameter tuning. + +#### Scenario: User selects Chinese document model +- **GIVEN** a user is processing Chinese business documents (forms, contracts, invoices) +- **WHEN** the user selects "Chinese Document Model" (PP-DocLayout-S) +- **THEN** the OCR engine SHALL use the PP-DocLayout-S layout detection model +- **AND** the model SHALL be optimized for 23 Chinese document element types +- **AND** table and form detection accuracy SHALL be improved over the default model + +#### Scenario: User selects standard model for English documents +- **GIVEN** a user is processing English academic papers or reports +- **WHEN** the user selects "Standard Model" (PubLayNet-based) +- **THEN** the OCR engine SHALL use the default PubLayNet-based layout detection model +- **AND** the model SHALL be optimized for English document layouts + +#### Scenario: User selects CDLA model for specialized Chinese layout +- **GIVEN** a user is processing Chinese documents with complex layouts +- **WHEN** the user selects "CDLA Model" +- **THEN** the OCR engine SHALL use the picodet_lcnet_x1_0_fgd_layout_cdla model +- **AND** the model SHALL provide specialized Chinese document layout analysis + +#### Scenario: Layout model is sent via API request +- **GIVEN** a frontend application with model selection UI +- **WHEN** the user starts task processing with a selected model +- **THEN** the frontend SHALL send the model choice in the request body: + ```json + POST /api/v2/tasks/{task_id}/start + { + "use_dual_track": true, + "force_track": "ocr", + "language": "ch", + "layout_model": "chinese" + } + ``` +- **AND** the backend SHALL configure PP-StructureV3 with the corresponding model +- **AND** the frontend SHALL NOT send `ocr_preset`, `ocr_config`, or `table_detection` parameters + +#### Scenario: Default model when not specified +- **GIVEN** an API request without `layout_model` parameter +- **WHEN** the task is started +- **THEN** the system SHALL use "chinese" (PP-DocLayout-S) as the default model +- **AND** processing SHALL work correctly without requiring model selection + +#### Scenario: Invalid model name is rejected +- **GIVEN** a request with an invalid `layout_model` value +- **WHEN** the user sends `layout_model: "invalid_model"` +- **THEN** the API SHALL return 422 Validation Error +- **AND** provide a clear error message listing valid model options + +### Requirement: Layout Model Selection UI +The frontend SHALL provide a simple, user-friendly interface for selecting layout detection models with clear descriptions of each option. + +#### Scenario: Model options are displayed with descriptions +- **GIVEN** the model selection UI is displayed +- **WHEN** the user views the available options +- **THEN** the UI SHALL show the following options: + - "Chinese Document Model (Recommended)" - for Chinese forms, contracts, invoices + - "Standard Model" - for English academic papers, reports + - "CDLA Model" - for specialized Chinese layout analysis +- **AND** each option SHALL have a brief description of its use case + +#### Scenario: Chinese model is selected by default +- **GIVEN** the user opens the task processing interface +- **WHEN** the model selection is displayed +- **THEN** "Chinese Document Model" SHALL be pre-selected as the default +- **AND** the user MAY change the selection before starting processing + +#### Scenario: Model selection is visible only for OCR track +- **GIVEN** a document processing interface +- **WHEN** the user selects processing track +- **THEN** layout model selection SHALL be shown ONLY when OCR track is selected or auto-detected +- **AND** SHALL be hidden for Direct track (which does not use PP-StructureV3) + +#### Scenario: Simplified configuration options +- **GIVEN** the OCR track processing interface +- **WHEN** the user configures processing options +- **THEN** the UI SHALL only show: + - Layout model selection (chinese/default/cdla) + - Image preprocessing settings (auto/manual/disabled) +- **AND** SHALL NOT show: + - OCR preset selection + - Table detection configuration + - Advanced OCR parameters + +### Requirement: Simplified Processing Options API +The backend API SHALL accept a simplified `ProcessingOptions` schema without complex OCR configuration parameters. + +#### Scenario: API accepts minimal configuration +- **GIVEN** a start task API request +- **WHEN** the request body contains: + ```json + { + "use_dual_track": true, + "force_track": "ocr", + "language": "ch", + "layout_model": "chinese", + "preprocessing_mode": "auto" + } + ``` +- **THEN** the API SHALL accept the request +- **AND** process the task using backend default values for all other parameters + +#### Scenario: Legacy parameters are ignored +- **GIVEN** a start task API request with legacy parameters +- **WHEN** the request contains `ocr_preset`, `ocr_config`, or `table_detection` +- **THEN** the API SHALL ignore these parameters +- **AND** use backend default values instead +- **AND** NOT return an error (backward compatibility) diff --git a/openspec/changes/simplify-frontend-ocr-config/tasks.md b/openspec/changes/simplify-frontend-ocr-config/tasks.md new file mode 100644 index 0000000..c81c80a --- /dev/null +++ b/openspec/changes/simplify-frontend-ocr-config/tasks.md @@ -0,0 +1,51 @@ +# Tasks: 簡化前端 OCR 配置選項 + +## 1. 前端清理 + +### 1.1 移除未使用的組件 +- [x] 1.1.1 刪除 `frontend/src/components/OCRPresetSelector.tsx` +- [x] 1.1.2 刪除 `frontend/src/components/TableDetectionSelector.tsx` + +### 1.2 清理 TypeScript 類型定義 +- [x] 1.2.1 從 `frontend/src/types/apiV2.ts` 移除以下類型: + - `TableDetectionConfig` (第 121-125 行) + - `OCRPreset` (第 131 行) + - `TableParsingMode` (第 140 行) + - `OCRConfig` (第 146-166 行) + - `OCRPresetInfo` (第 171-177 行) +- [x] 1.2.2 從 `ProcessingOptions` interface 移除以下欄位: + - `table_detection` + - `ocr_preset` + - `ocr_config` + +### 1.3 清理 ProcessingPage +- [x] 1.3.1 確認 `frontend/src/pages/ProcessingPage.tsx` 中沒有引用已移除的類型或組件 +- [x] 1.3.2 移除相關的註解說明（如果有）- 保留說明性註解 + +## 2. 後端清理 + +### 2.1 清理 Schema 定義 +- [x] 2.1.1 從 `backend/app/schemas/task.py` 移除未使用的 Enum 和 Model: + - `TableDetectionConfig` + - `OCRPresetEnum` + - `TableParsingModeEnum` + - `OCRConfig` + - `OCR_PRESET_CONFIGS` +- [x] 2.1.2 從 `ProcessingOptions` 移除以下欄位: + - `table_detection` + - `ocr_preset` + - `ocr_config` + +### 2.2 清理 API 端點邏輯 +- [x] 2.2.1 檢查 `backend/app/routers/tasks.py` 中的 `start_task` 端點，移除對已刪除欄位的處理 +- [x] 2.2.2 更新 `process_task_ocr` 函數簽名和呼叫 + +### 2.3 清理 Service 層 +- [x] 2.3.1 檢查 `backend/app/services/ocr_service.py`，確認沒有依賴已移除的配置項 + - 注意：ocr_service.py 保留這些參數作為可選項，使用預設值處理。這是正確的設計，保持後端彈性。 + +## 3. 驗證 + +- [x] 3.1 確認 TypeScript 編譯無新錯誤（與本次變更相關的錯誤） +- [ ] 3.2 確認後端 API 仍正常運作（需手動測試） +- [ ] 3.3 測試上傳 -> 處理 -> 結果查看的完整流程（需手動測試） diff --git a/openspec/specs/ocr-processing/spec.md b/openspec/specs/ocr-processing/spec.md index 6cfe845..9317d42 100644 --- a/openspec/specs/ocr-processing/spec.md +++ b/openspec/specs/ocr-processing/spec.md @@ -14,12 +14,21 @@ The system SHALL detect and fill gaps in PP-StructureV3 output by supplementing - **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 center-point and IoU +#### 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 its center point falls inside any PP-StructureV3 element bbox -- **OR** if IoU with any PP-StructureV3 element exceeds 0.15 threshold -- **AND** regions not meeting either criterion SHALL be marked as uncovered +- **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 @@ -33,9 +42,9 @@ The system SHALL detect and fill gaps in PP-StructureV3 output by supplementing - **THEN** the system SHALL skip that region - **AND** only supplement regions with confidence >= 0.3 -#### Scenario: Deduplication prevents repeated text +#### Scenario: Deduplication uses IoA instead of IoU - **GIVEN** a Raw OCR region being considered for supplementation -- **WHEN** the region has IoU > 0.5 with any existing PP-StructureV3 TEXT element +- **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 @@ -99,10 +108,12 @@ The system SHALL provide configurable parameters for gap filling behavior. - **THEN** the system SHALL activate gap filling - **AND** supplement uncovered regions -#### Scenario: IoU thresholds are configurable -- **GIVEN** custom IoU thresholds configured: - - gap_filling_iou_threshold: 0.2 - - gap_filling_dedup_iou_threshold: 0.6 +#### 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 @@ -113,6 +124,12 @@ The system SHALL provide configurable parameters for gap filling behavior. - **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 + ### Requirement: Layout Model Selection The system SHALL allow users to select a layout detection model optimized for their document type, providing a simple choice between pre-configured models instead of manual parameter tuning. @@ -258,3 +275,37 @@ The system SHALL provide configurable thresholds for cell validation. - **THEN** the system SHALL use the custom values - **AND** apply them consistently to all pages +### 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 +