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Initial commit
This commit is contained in:
Christoph Auer
0
docling/datamodel/__init__.py
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0
docling/datamodel/__init__.py
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247
docling/datamodel/base_models.py
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247
docling/datamodel/base_models.py
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@@ -0,0 +1,247 @@
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from enum import Enum, auto
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from io import BytesIO
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from typing import Any, Dict, List, Optional, Tuple, Union
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from PIL.Image import Image
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from pydantic import BaseModel, ConfigDict, model_validator
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from docling.backend.abstract_backend import PdfPageBackend
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class ConversionStatus(str, Enum):
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PENDING = auto()
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STARTED = auto()
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FAILURE = auto()
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SUCCESS = auto()
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SUCCESS_WITH_ERRORS = auto()
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class DocInputType(str, Enum):
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PATH = auto()
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STREAM = auto()
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class CoordOrigin(str, Enum):
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TOPLEFT = auto()
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BOTTOMLEFT = auto()
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class PageSize(BaseModel):
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width: float = 0.0
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height: float = 0.0
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class BoundingBox(BaseModel):
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l: float # left
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t: float # top
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r: float # right
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b: float # bottom
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coord_origin: CoordOrigin = CoordOrigin.TOPLEFT
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@property
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def width(self):
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return self.r - self.l
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@property
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def height(self):
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return abs(self.t - self.b)
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def as_tuple(self):
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if self.coord_origin == CoordOrigin.TOPLEFT:
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return (self.l, self.t, self.r, self.b)
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elif self.coord_origin == CoordOrigin.BOTTOMLEFT:
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return (self.l, self.b, self.r, self.t)
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@classmethod
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def from_tuple(cls, coord: Tuple[float], origin: CoordOrigin):
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if origin == CoordOrigin.TOPLEFT:
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return BoundingBox(
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l=coord[0], t=coord[1], r=coord[2], b=coord[3], coord_origin=origin
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)
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elif origin == CoordOrigin.BOTTOMLEFT:
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return BoundingBox(
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l=coord[0], b=coord[1], r=coord[2], t=coord[3], coord_origin=origin
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)
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def area(self) -> float:
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return (self.r - self.l) * (self.b - self.t)
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def intersection_area_with(self, other: "BoundingBox") -> float:
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# Calculate intersection coordinates
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left = max(self.l, other.l)
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top = max(self.t, other.t)
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right = min(self.r, other.r)
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bottom = min(self.b, other.b)
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# Calculate intersection dimensions
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width = right - left
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height = bottom - top
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# If the bounding boxes do not overlap, width or height will be negative
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if width <= 0 or height <= 0:
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return 0.0
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return width * height
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def to_bottom_left_origin(self, page_height) -> "BoundingBox":
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if self.coord_origin == CoordOrigin.BOTTOMLEFT:
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return self
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elif self.coord_origin == CoordOrigin.TOPLEFT:
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return BoundingBox(
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l=self.l,
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r=self.r,
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t=page_height - self.t,
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b=page_height - self.b,
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coord_origin=CoordOrigin.BOTTOMLEFT,
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)
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def to_top_left_origin(self, page_height):
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if self.coord_origin == CoordOrigin.TOPLEFT:
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return self
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elif self.coord_origin == CoordOrigin.BOTTOMLEFT:
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return BoundingBox(
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l=self.l,
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r=self.r,
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t=page_height - self.t, # self.b
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b=page_height - self.b, # self.t
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coord_origin=CoordOrigin.TOPLEFT,
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)
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class Cell(BaseModel):
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id: int
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text: str
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bbox: BoundingBox
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class OcrCell(Cell):
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confidence: float
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class Cluster(BaseModel):
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id: int
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label: str
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bbox: BoundingBox
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confidence: float = 1.0
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cells: List[Cell] = []
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class BasePageElement(BaseModel):
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label: str
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id: int
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page_no: int
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cluster: Cluster
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text: Optional[str] = None
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class LayoutPrediction(BaseModel):
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clusters: List[Cluster] = []
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class TableCell(BaseModel):
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bbox: BoundingBox
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row_span: int
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col_span: int
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start_row_offset_idx: int
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end_row_offset_idx: int
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start_col_offset_idx: int
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end_col_offset_idx: int
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text: str
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column_header: bool = False
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row_header: bool = False
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row_section: bool = False
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@model_validator(mode="before")
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@classmethod
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def from_dict_format(cls, data: Any) -> Any:
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if isinstance(data, Dict):
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text = data["bbox"].get("token", "")
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if not len(text):
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text_cells = data.pop("text_cell_bboxes", None)
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if text_cells:
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for el in text_cells:
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text += el["token"] + " "
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text = text.strip()
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data["text"] = text
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return data
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class TableElement(BasePageElement):
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otsl_seq: List[str]
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num_rows: int = 0
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num_cols: int = 0
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table_cells: List[TableCell]
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class TableStructurePrediction(BaseModel):
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table_map: Dict[int, TableElement] = {}
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class TextElement(BasePageElement):
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...
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class FigureData(BaseModel):
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pass
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class FigureElement(BasePageElement):
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data: Optional[FigureData] = None
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provenance: Optional[str] = None
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predicted_class: Optional[str] = None
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confidence: Optional[float] = None
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class FigureClassificationPrediction(BaseModel):
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figure_count: int = 0
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figure_map: Dict[int, FigureElement] = {}
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class EquationPrediction(BaseModel):
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equation_count: int = 0
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equation_map: Dict[int, TextElement] = {}
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class PagePredictions(BaseModel):
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layout: LayoutPrediction = None
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tablestructure: TableStructurePrediction = None
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figures_classification: FigureClassificationPrediction = None
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equations_prediction: EquationPrediction = None
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PageElement = Union[TextElement, TableElement, FigureElement]
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class AssembledUnit(BaseModel):
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elements: List[PageElement]
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body: List[PageElement]
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headers: List[PageElement]
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class Page(BaseModel):
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model_config = ConfigDict(arbitrary_types_allowed=True)
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page_no: int
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page_hash: str = None
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size: PageSize = None
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image: Image = None
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cells: List[Cell] = None
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predictions: PagePredictions = PagePredictions()
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assembled: AssembledUnit = None
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_backend: PdfPageBackend = None # Internal PDF backend
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class DocumentStream(BaseModel):
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model_config = ConfigDict(arbitrary_types_allowed=True)
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filename: str
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stream: BytesIO
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class PipelineOptions(BaseModel):
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do_table_structure: bool = True
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do_ocr: bool = False
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351
docling/datamodel/document.py
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351
docling/datamodel/document.py
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@@ -0,0 +1,351 @@
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import logging
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from io import BytesIO
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from pathlib import Path, PurePath
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from typing import ClassVar, Dict, Iterable, List, Optional, Type, Union
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from deepsearch.documents.core.export import export_to_markdown
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from docling_core.types import BaseCell, BaseText
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from docling_core.types import BoundingBox as DsBoundingBox
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from docling_core.types import Document as DsDocument
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from docling_core.types import DocumentDescription as DsDocumentDescription
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from docling_core.types import FileInfoObject as DsFileInfoObject
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from docling_core.types import PageDimensions, PageReference, Prov, Ref
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from docling_core.types import Table as DsSchemaTable
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from docling_core.types import TableCell
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from pydantic import BaseModel
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from docling.backend.abstract_backend import PdfDocumentBackend
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from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
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from docling.datamodel.base_models import (
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AssembledUnit,
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ConversionStatus,
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DocumentStream,
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FigureElement,
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Page,
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TableElement,
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TextElement,
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)
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from docling.datamodel.settings import DocumentLimits
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from docling.utils.utils import create_file_hash
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_log = logging.getLogger(__name__)
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layout_label_to_ds_type = {
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"Title": "title",
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"Document Index": "table-of-path_or_stream",
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"Section-header": "subtitle-level-1",
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"Checkbox-Selected": "checkbox-selected",
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"Checkbox-Unselected": "checkbox-unselected",
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"Caption": "caption",
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"Page-header": "page-header",
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"Page-footer": "page-footer",
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"Footnote": "footnote",
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"Table": "table",
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"Formula": "equation",
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"List-item": "paragraph",
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"Code": "paragraph",
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"Picture": "figure",
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"Text": "paragraph",
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}
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class InputDocument(BaseModel):
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file: PurePath = None
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document_hash: Optional[str] = None
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valid: bool = False
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limits: DocumentLimits = DocumentLimits()
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filesize: Optional[int] = None
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page_count: Optional[int] = None
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_backend: PdfDocumentBackend = None # Internal PDF backend used
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def __init__(
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self,
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path_or_stream: Union[BytesIO, Path],
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filename: Optional[str] = None,
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limits: Optional[DocumentLimits] = None,
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pdf_backend=PyPdfiumDocumentBackend,
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):
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super().__init__()
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self.limits = limits or DocumentLimits()
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try:
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if isinstance(path_or_stream, Path):
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self.file = path_or_stream
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self.filesize = path_or_stream.stat().st_size
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if self.filesize > self.limits.max_file_size:
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self.valid = False
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else:
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self.document_hash = create_file_hash(path_or_stream)
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self._backend = pdf_backend(path_or_stream=path_or_stream)
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elif isinstance(path_or_stream, BytesIO):
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self.file = PurePath(filename)
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self.filesize = path_or_stream.getbuffer().nbytes
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if self.filesize > self.limits.max_file_size:
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self.valid = False
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else:
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self.document_hash = create_file_hash(path_or_stream)
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self._backend = pdf_backend(path_or_stream=path_or_stream)
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if self.document_hash and self._backend.page_count() > 0:
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self.page_count = self._backend.page_count()
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if self.page_count <= self.limits.max_num_pages:
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self.valid = True
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except (FileNotFoundError, OSError) as e:
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_log.exception(
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f"File {self.file.name} not found or cannot be opened.", exc_info=e
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)
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# raise
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except RuntimeError as e:
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_log.exception(
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f"An unexpected error occurred while opening the document {self.file.name}",
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exc_info=e,
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)
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# raise
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class ConvertedDocument(BaseModel):
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input: InputDocument
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status: ConversionStatus = ConversionStatus.PENDING # failure, success
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errors: List[Dict] = [] # structure to keep errors
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pages: List[Page] = []
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assembled: AssembledUnit = None
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output: DsDocument = None
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def to_ds_document(self) -> DsDocument:
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title = ""
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desc = DsDocumentDescription(logs=[])
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page_hashes = [
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PageReference(hash=p.page_hash, page=p.page_no, model="default")
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for p in self.pages
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]
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file_info = DsFileInfoObject(
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filename=self.input.file.name,
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document_hash=self.input.document_hash,
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num_pages=self.input.page_count,
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page_hashes=page_hashes,
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)
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main_text = []
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tables = []
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figures = []
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page_no_to_page = {p.page_no: p for p in self.pages}
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for element in self.assembled.elements:
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# Convert bboxes to lower-left origin.
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target_bbox = DsBoundingBox(
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element.cluster.bbox.to_bottom_left_origin(
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page_no_to_page[element.page_no].size.height
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).as_tuple()
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)
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if isinstance(element, TextElement):
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main_text.append(
|
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BaseText(
|
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text=element.text,
|
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obj_type=layout_label_to_ds_type.get(element.label),
|
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name=element.label,
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prov=[
|
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Prov(
|
||||
bbox=target_bbox,
|
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page=element.page_no,
|
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span=[0, len(element.text)],
|
||||
)
|
||||
],
|
||||
)
|
||||
)
|
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elif isinstance(element, TableElement):
|
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index = len(tables)
|
||||
ref_str = f"#/tables/{index}"
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main_text.append(
|
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Ref(
|
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name=element.label,
|
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obj_type=layout_label_to_ds_type.get(element.label),
|
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ref=ref_str,
|
||||
),
|
||||
)
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# Initialise empty table data grid (only empty cells)
|
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table_data = [
|
||||
[
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TableCell(
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text="",
|
||||
# bbox=[0,0,0,0],
|
||||
spans=[[i, j]],
|
||||
obj_type="body",
|
||||
)
|
||||
for j in range(element.num_cols)
|
||||
]
|
||||
for i in range(element.num_rows)
|
||||
]
|
||||
|
||||
# Overwrite cells in table data for which there is actual cell content.
|
||||
for cell in element.table_cells:
|
||||
for i in range(
|
||||
min(cell.start_row_offset_idx, element.num_rows),
|
||||
min(cell.end_row_offset_idx, element.num_rows),
|
||||
):
|
||||
for j in range(
|
||||
min(cell.start_col_offset_idx, element.num_cols),
|
||||
min(cell.end_col_offset_idx, element.num_cols),
|
||||
):
|
||||
celltype = "body"
|
||||
if cell.column_header:
|
||||
celltype = "col_header"
|
||||
elif cell.row_header:
|
||||
celltype = "row_header"
|
||||
|
||||
def make_spans(cell):
|
||||
for rspan in range(
|
||||
min(cell.start_row_offset_idx, element.num_rows),
|
||||
min(cell.end_row_offset_idx, element.num_rows),
|
||||
):
|
||||
for cspan in range(
|
||||
min(
|
||||
cell.start_col_offset_idx, element.num_cols
|
||||
),
|
||||
min(cell.end_col_offset_idx, element.num_cols),
|
||||
):
|
||||
yield [rspan, cspan]
|
||||
|
||||
spans = list(make_spans(cell))
|
||||
table_data[i][j] = TableCell(
|
||||
text=cell.text,
|
||||
bbox=cell.bbox.to_bottom_left_origin(
|
||||
page_no_to_page[element.page_no].size.height
|
||||
).as_tuple(),
|
||||
# col=j,
|
||||
# row=i,
|
||||
spans=spans,
|
||||
obj_type=celltype,
|
||||
# col_span=[cell.start_col_offset_idx, cell.end_col_offset_idx],
|
||||
# row_span=[cell.start_row_offset_idx, cell.end_row_offset_idx]
|
||||
)
|
||||
|
||||
tables.append(
|
||||
DsSchemaTable(
|
||||
num_cols=element.num_cols,
|
||||
num_rows=element.num_rows,
|
||||
obj_type=layout_label_to_ds_type.get(element.label),
|
||||
data=table_data,
|
||||
prov=[
|
||||
Prov(
|
||||
bbox=target_bbox,
|
||||
page=element.page_no,
|
||||
span=[0, 0],
|
||||
)
|
||||
],
|
||||
)
|
||||
)
|
||||
|
||||
elif isinstance(element, FigureElement):
|
||||
index = len(figures)
|
||||
ref_str = f"#/figures/{index}"
|
||||
main_text.append(
|
||||
Ref(
|
||||
name=element.label,
|
||||
obj_type=layout_label_to_ds_type.get(element.label),
|
||||
ref=ref_str,
|
||||
),
|
||||
)
|
||||
figures.append(
|
||||
BaseCell(
|
||||
prov=[
|
||||
Prov(
|
||||
bbox=target_bbox,
|
||||
page=element.page_no,
|
||||
span=[0, 0],
|
||||
)
|
||||
],
|
||||
obj_type=layout_label_to_ds_type.get(element.label),
|
||||
# data=[[]],
|
||||
)
|
||||
)
|
||||
|
||||
page_dimensions = [
|
||||
PageDimensions(page=p.page_no, height=p.size.height, width=p.size.width)
|
||||
for p in self.pages
|
||||
]
|
||||
|
||||
ds_doc = DsDocument(
|
||||
name=title,
|
||||
description=desc,
|
||||
file_info=file_info,
|
||||
main_text=main_text,
|
||||
tables=tables,
|
||||
figures=figures,
|
||||
page_dimensions=page_dimensions,
|
||||
)
|
||||
|
||||
return ds_doc
|
||||
|
||||
def render_as_dict(self):
|
||||
if self.output:
|
||||
return self.output.model_dump(by_alias=True, exclude_none=True)
|
||||
else:
|
||||
return {}
|
||||
|
||||
def render_as_markdown(self):
|
||||
if self.output:
|
||||
return export_to_markdown(
|
||||
self.output.model_dump(by_alias=True, exclude_none=True)
|
||||
)
|
||||
else:
|
||||
return ""
|
||||
|
||||
|
||||
class DocumentConversionInput(BaseModel):
|
||||
|
||||
_path_or_stream_iterator: Iterable[Union[Path, DocumentStream]] = None
|
||||
limits: Optional[DocumentLimits] = DocumentLimits()
|
||||
|
||||
DEFAULT_BACKEND: ClassVar = PyPdfiumDocumentBackend
|
||||
|
||||
def docs(
|
||||
self, pdf_backend: Optional[Type[PdfDocumentBackend]] = None
|
||||
) -> Iterable[InputDocument]:
|
||||
|
||||
pdf_backend = pdf_backend or DocumentConversionInput.DEFAULT_BACKEND
|
||||
|
||||
for obj in self._path_or_stream_iterator:
|
||||
if isinstance(obj, Path):
|
||||
yield InputDocument(
|
||||
path_or_stream=obj, limits=self.limits, pdf_backend=pdf_backend
|
||||
)
|
||||
elif isinstance(obj, DocumentStream):
|
||||
yield InputDocument(
|
||||
path_or_stream=obj.stream,
|
||||
filename=obj.filename,
|
||||
limits=self.limits,
|
||||
pdf_backend=pdf_backend,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def from_paths(cls, paths: Iterable[Path], limits: Optional[DocumentLimits] = None):
|
||||
paths = [Path(p) for p in paths]
|
||||
|
||||
doc_input = cls(limits=limits)
|
||||
doc_input._path_or_stream_iterator = paths
|
||||
|
||||
return doc_input
|
||||
|
||||
@classmethod
|
||||
def from_streams(
|
||||
cls, streams: Iterable[DocumentStream], limits: Optional[DocumentLimits] = None
|
||||
):
|
||||
doc_input = cls(limits=limits)
|
||||
doc_input._path_or_stream_iterator = streams
|
||||
|
||||
return doc_input
|
||||
32
docling/datamodel/settings.py
Normal file
32
docling/datamodel/settings.py
Normal file
@@ -0,0 +1,32 @@
|
||||
import sys
|
||||
|
||||
from pydantic import BaseModel
|
||||
from pydantic_settings import BaseSettings
|
||||
|
||||
|
||||
class DocumentLimits(BaseModel):
|
||||
max_num_pages: int = sys.maxsize
|
||||
max_file_size: int = sys.maxsize
|
||||
|
||||
|
||||
class BatchConcurrencySettings(BaseModel):
|
||||
doc_batch_size: int = 2
|
||||
doc_batch_concurrency: int = 2
|
||||
page_batch_size: int = 4
|
||||
page_batch_concurrency: int = 2
|
||||
|
||||
# doc_batch_size: int = 1
|
||||
# doc_batch_concurrency: int = 1
|
||||
# page_batch_size: int = 1
|
||||
# page_batch_concurrency: int = 1
|
||||
|
||||
# model_concurrency: int = 2
|
||||
|
||||
# To force models into single core: export OMP_NUM_THREADS=1
|
||||
|
||||
|
||||
class AppSettings(BaseSettings):
|
||||
perf: BatchConcurrencySettings
|
||||
|
||||
|
||||
settings = AppSettings(perf=BatchConcurrencySettings())
|
||||
Reference in New Issue
Block a user