36 lines
1.9 KiB
Python
36 lines
1.9 KiB
Python
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from __future__ import annotations
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from pydantic import BaseModel, Field
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class OcrRecognizeLineRead(BaseModel):
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text: str = Field(description="识别出的文本行。")
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score: float = Field(default=0.0, ge=0.0, le=1.0, description="该行识别置信度。")
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box: list[list[int]] = Field(default_factory=list, description="文本框坐标。")
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page_index: int | None = Field(default=None, description="页码，从 0 开始。")
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class OcrRecognizeDocumentRead(BaseModel):
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filename: str = Field(description="原始文件名。")
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media_type: str = Field(description="文件媒体类型。")
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engine: str = Field(default="paddleocr_mobile", description="使用的 OCR 引擎。")
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model: str = Field(default="PP-OCRv5_mobile", description="模型族标识。")
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text: str = Field(default="", description="合并后的完整 OCR 文本。")
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summary: str = Field(default="", description="供对话和语义层复用的简短摘要。")
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avg_score: float = Field(default=0.0, ge=0.0, le=1.0, description="平均识别置信度。")
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line_count: int = Field(default=0, ge=0, description="文本行数。")
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page_count: int = Field(default=1, ge=0, description="识别页数。")
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warnings: list[str] = Field(default_factory=list, description="该文件的识别提示或警告。")
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lines: list[OcrRecognizeLineRead] = Field(default_factory=list, description="逐行识别结果。")
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class OcrRecognizeBatchRead(BaseModel):
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engine: str = Field(default="paddleocr_mobile", description="使用的 OCR 引擎。")
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model: str = Field(default="PP-OCRv5_mobile", description="模型族标识。")
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total_file_count: int = Field(default=0, ge=0, description="本次上传的总文件数。")
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success_count: int = Field(default=0, ge=0, description="成功进入 OCR 的文件数。")
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documents: list[OcrRecognizeDocumentRead] = Field(
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default_factory=list,
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description="逐文件 OCR 结果。",
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)
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