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OCR/backend/app/schemas/task.py
egg 940a406dce chore: backup before code cleanup
Backup commit before executing remove-unused-code proposal.
This includes all pending changes and new features.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-11 11:55:39 +08:00

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19 KiB
Python

"""
Tool_OCR - Task Management Schemas
"""
from typing import Optional, List
from datetime import datetime
from pydantic import BaseModel, Field
from enum import Enum
class TaskStatusEnum(str, Enum):
"""Task status enumeration"""
PENDING = "pending"
PROCESSING = "processing"
COMPLETED = "completed"
FAILED = "failed"
class ProcessingTrackEnum(str, Enum):
"""Processing track enumeration for dual-track processing"""
OCR = "ocr" # PaddleOCR PP-StructureV3 for scanned documents
DIRECT = "direct" # PyMuPDF for editable PDFs
HYBRID = "hybrid" # Mixed processing
AUTO = "auto" # Auto-detect best track
class LayoutModelEnum(str, Enum):
"""Layout detection model selection for OCR track.
Different models are optimized for different document types:
- CHINESE: PP-DocLayout_plus-L (83.2% mAP), optimized for complex Chinese documents
- DEFAULT: PubLayNet-based (~94% mAP), optimized for English academic papers
- CDLA: CDLA model (~86% mAP), specialized Chinese document layout analysis
"""
CHINESE = "chinese" # PP-DocLayout_plus-L - Best for Chinese documents (recommended)
DEFAULT = "default" # PubLayNet-based - Best for English documents
CDLA = "cdla" # CDLA model - Alternative for Chinese layout
class PreprocessingModeEnum(str, Enum):
"""Preprocessing mode for layout detection enhancement.
- AUTO: Analyze image quality and automatically apply optimal preprocessing
- MANUAL: Use user-specified preprocessing configuration
- DISABLED: Skip preprocessing entirely
"""
AUTO = "auto" # Analyze and apply automatically (default)
MANUAL = "manual" # Use specified configuration
DISABLED = "disabled" # Skip preprocessing
class PreprocessingContrastEnum(str, Enum):
"""Contrast enhancement method for preprocessing.
- NONE: No contrast enhancement
- HISTOGRAM: Standard histogram equalization
- CLAHE: Contrast Limited Adaptive Histogram Equalization (recommended for most cases)
- DOCUMENT: Background normalization + CLAHE (recommended for scanned documents)
Removes uneven illumination before enhancement. Best for scans with
yellowed paper, shadow, or scanner lighting issues.
"""
NONE = "none"
HISTOGRAM = "histogram"
CLAHE = "clahe"
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.
Used to configure image preprocessing before PP-Structure layout detection.
Preprocessing helps detect tables with faint lines or low contrast borders.
Original image is preserved for element extraction.
"""
contrast: PreprocessingContrastEnum = Field(
default=PreprocessingContrastEnum.CLAHE,
description="Contrast enhancement method"
)
contrast_strength: float = Field(
default=1.0,
ge=0.5,
le=3.0,
description="Contrast enhancement strength (0.5=subtle, 1.0=normal, 2.0=strong, 3.0=maximum)"
)
sharpen: bool = Field(
default=True,
description="Enable sharpening for faint lines"
)
sharpen_strength: float = Field(
default=1.0,
ge=0.5,
le=2.0,
description="Sharpening strength (0.5=subtle, 1.0=normal, 1.5=strong, 2.0=maximum)"
)
binarize: bool = Field(
default=False,
description="Enable binarization (aggressive, for very low contrast). Not recommended for most documents."
)
remove_scan_artifacts: bool = Field(
default=True,
description="Remove horizontal scan line artifacts. Recommended for scanned documents to prevent misdetection of scanner light bar lines as table borders."
)
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)")
edge_strength: float = Field(..., description="Edge strength (Sobel gradient mean)")
class PreprocessingPreviewRequest(BaseModel):
"""Request for preprocessing preview."""
page: int = Field(default=1, ge=1, description="Page number to preview")
mode: PreprocessingModeEnum = Field(
default=PreprocessingModeEnum.AUTO,
description="Preprocessing mode"
)
config: Optional[PreprocessingConfig] = Field(
None,
description="Manual configuration (only used when mode='manual')"
)
class PreprocessingPreviewResponse(BaseModel):
"""Response for preprocessing preview."""
original_url: str = Field(..., description="URL to original image")
preprocessed_url: str = Field(..., description="URL to preprocessed image")
quality_metrics: ImageQualityMetrics = Field(..., description="Image quality analysis")
auto_config: PreprocessingConfig = Field(..., description="Auto-detected configuration")
mode_used: PreprocessingModeEnum = Field(..., description="Mode that was applied")
class TaskCreate(BaseModel):
"""Task creation request"""
filename: Optional[str] = Field(None, description="Original filename")
file_type: Optional[str] = Field(None, description="File MIME type")
class TaskUpdate(BaseModel):
"""Task update request"""
status: Optional[TaskStatusEnum] = None
error_message: Optional[str] = None
processing_time_ms: Optional[int] = None
result_json_path: Optional[str] = None
result_markdown_path: Optional[str] = None
result_pdf_path: Optional[str] = None
class TaskFileResponse(BaseModel):
"""Task file response schema"""
id: int
original_name: Optional[str] = None
stored_path: Optional[str] = None
file_size: Optional[int] = None
mime_type: Optional[str] = None
file_hash: Optional[str] = None
created_at: datetime
class Config:
from_attributes = True
class TaskResponse(BaseModel):
"""Task response schema"""
id: int
user_id: int
task_id: str
filename: Optional[str] = None
file_type: Optional[str] = None
status: TaskStatusEnum
result_json_path: Optional[str] = None
result_markdown_path: Optional[str] = None
result_pdf_path: Optional[str] = None
error_message: Optional[str] = None
processing_time_ms: Optional[int] = None
created_at: datetime
updated_at: datetime
completed_at: Optional[datetime] = None
file_deleted: bool = False
class Config:
from_attributes = True
class TaskDetailResponse(TaskResponse):
"""Detailed task response with files"""
files: List[TaskFileResponse] = []
# Dual-track processing field (extracted from result metadata)
processing_track: Optional[ProcessingTrackEnum] = None
class TaskListResponse(BaseModel):
"""Paginated task list response"""
tasks: List[TaskResponse]
total: int
page: int
page_size: int
has_more: bool
class TaskStatsResponse(BaseModel):
"""User task statistics"""
total: int
pending: int
processing: int
completed: int
failed: int
class TaskHistoryQuery(BaseModel):
"""Task history query parameters"""
status: Optional[TaskStatusEnum] = None
filename: Optional[str] = None
date_from: Optional[datetime] = None
date_to: Optional[datetime] = None
page: int = Field(default=1, ge=1)
page_size: int = Field(default=50, ge=1, le=100)
order_by: str = Field(default="created_at")
order_desc: bool = Field(default=True)
class UploadFileInfo(BaseModel):
"""Uploaded file information"""
filename: str
file_size: int
file_type: str
class UploadResponse(BaseModel):
"""File upload response"""
task_id: str = Field(..., description="Created task ID")
filename: str = Field(..., description="Original filename")
file_size: int = Field(..., description="File size in bytes")
file_type: str = Field(..., description="File MIME type")
status: TaskStatusEnum = Field(..., description="Initial task status")
# ===== Dual-Track Processing Schemas =====
class PPStructureV3Params(BaseModel):
"""PP-StructureV3 fine-tuning parameters for OCR track.
DEPRECATED: This class is deprecated and will be removed in a future version.
Use `layout_model` parameter in ProcessingOptions instead.
"""
layout_detection_threshold: Optional[float] = Field(
None, ge=0, le=1,
description="Layout block detection score threshold (lower=more blocks, higher=high confidence only)"
)
layout_nms_threshold: Optional[float] = Field(
None, ge=0, le=1,
description="Layout NMS IoU threshold (lower=aggressive overlap removal, higher=allow more overlap)"
)
layout_merge_bboxes_mode: Optional[str] = Field(
None, pattern="^(union|large|small)$",
description="Bbox merging strategy: 'small'=conservative, 'large'=aggressive, 'union'=middle"
)
layout_unclip_ratio: Optional[float] = Field(
None, gt=0,
description="Layout bbox expansion ratio (larger=looser boxes, smaller=tighter boxes)"
)
text_det_thresh: Optional[float] = Field(
None, ge=0, le=1,
description="Text detection score threshold (lower=detect more small/low-contrast text, higher=cleaner)"
)
text_det_box_thresh: Optional[float] = Field(
None, ge=0, le=1,
description="Text box candidate threshold (lower=more text boxes, higher=fewer false positives)"
)
text_det_unclip_ratio: Optional[float] = Field(
None, gt=0,
description="Text box expansion ratio (larger=looser boxes, smaller=tighter boxes)"
)
class ProcessingOptions(BaseModel):
"""Processing options for dual-track OCR"""
use_dual_track: bool = Field(default=True, description="Enable dual-track processing")
force_track: Optional[ProcessingTrackEnum] = Field(None, description="Force specific track (ocr/direct)")
language: str = Field(default="ch", description="OCR language code")
include_layout: bool = Field(default=True, description="Include layout analysis")
include_images: bool = Field(default=True, description="Extract and save images")
confidence_threshold: Optional[float] = Field(None, ge=0, le=1, description="OCR confidence threshold")
# Layout model selection (OCR track only)
layout_model: Optional[LayoutModelEnum] = Field(
default=LayoutModelEnum.CHINESE,
description="Layout detection model: 'chinese' (recommended for Chinese docs), 'default' (English docs), 'cdla' (Chinese layout)"
)
# Layout preprocessing (OCR track only)
preprocessing_mode: PreprocessingModeEnum = Field(
default=PreprocessingModeEnum.AUTO,
description="Preprocessing mode: 'auto' (analyze and apply), 'manual' (use config), 'disabled'"
)
preprocessing_config: Optional[PreprocessingConfig] = Field(
None,
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"""
use_dual_track: bool = Field(default=True, description="Enable dual-track processing")
force_track: Optional[ProcessingTrackEnum] = Field(None, description="Force specific track")
language: str = Field(default="ch", description="OCR language")
include_layout: bool = Field(default=True, description="Include layout analysis")
class DocumentAnalysisResponse(BaseModel):
"""Document type analysis response"""
task_id: str
filename: str
recommended_track: ProcessingTrackEnum
confidence: float = Field(..., ge=0, le=1, description="Detection confidence")
reason: str = Field(..., description="Reason for recommendation")
document_info: dict = Field(default_factory=dict, description="Document metadata")
is_editable: bool = Field(..., description="Whether document has extractable text")
text_coverage: Optional[float] = Field(None, description="Percentage of text coverage")
page_count: Optional[int] = Field(None, description="Number of pages")
class ProcessingMetadata(BaseModel):
"""Processing metadata included in responses"""
processing_track: ProcessingTrackEnum
processing_time_seconds: float
language: str
page_count: int
total_elements: int
total_text_regions: int
total_tables: int
total_images: int
average_confidence: Optional[float] = None
unified_format: bool = True
class TaskResponseWithMetadata(TaskResponse):
"""Extended task response with processing metadata"""
processing_track: Optional[ProcessingTrackEnum] = None
processing_metadata: Optional[ProcessingMetadata] = None
class ExportOptions(BaseModel):
"""Export format options"""
format: str = Field(default="json", description="Export format: json, markdown, pdf, unified")
include_metadata: bool = Field(default=True, description="Include processing metadata")
include_statistics: bool = Field(default=True, description="Include document statistics")
legacy_format: bool = Field(default=False, description="Use legacy JSON format for compatibility")