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init
Signed-off-by: felix <felixdittrich92@gmail.com>
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parent
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35f185f545
@ -151,6 +151,32 @@ class RapidOcrOptions(OcrOptions):
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)
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)
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class OnnxtrOcrOptions(OcrOptions):
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"""Options for the Onnxtr engine."""
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kind: ClassVar[Literal["onnxtr"]] = "onnxtr"
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lang: List[str] = ["en", "fr"]
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confidence_score: float = 0.5
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det_arch: str = "fast_base"
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reco_arch: str = "crnn_vgg16_bn" # NOTE: This can be also a hf hub model
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det_bs: int = 1 # NOTE: Should be 1 because docling seems not to support batch processing yet
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reco_bs: int = 512
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auto_correct_orientation: bool = False
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preserve_aspect_ratio: bool = True
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symmetric_pad: bool = True
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paragraph_break: float = 0.035
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load_in_8_bit: bool = False
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det_engine_cfg: Dict[str, Any] = {}
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reco_engine_cfg: Dict[str, Any] = {}
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clf_engine_cfg: Dict[str, Any] = {}
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model_config = ConfigDict(
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extra="forbid",
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)
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class EasyOcrOptions(OcrOptions):
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class EasyOcrOptions(OcrOptions):
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"""Options for the EasyOCR engine."""
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"""Options for the EasyOCR engine."""
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174
docling/models/onnxtr_model.py
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174
docling/models/onnxtr_model.py
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@ -0,0 +1,174 @@
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import logging
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from pathlib import Path
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from typing import Iterable, Optional, Type
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import numpy
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from docling_core.types.doc import BoundingBox, CoordOrigin
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from docling_core.types.doc.page import BoundingRectangle, TextCell
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from docling.datamodel.base_models import Page
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from docling.datamodel.document import ConversionResult
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from docling.datamodel.pipeline_options import (
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AcceleratorDevice,
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AcceleratorOptions,
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OcrOptions,
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OnnxtrOcrOptions,
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)
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from docling.datamodel.settings import settings
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from docling.models.base_ocr_model import BaseOcrModel
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from docling.utils.accelerator_utils import decide_device
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from docling.utils.profiling import TimeRecorder
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_log = logging.getLogger(__name__)
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class OnnxtrOcrModel(BaseOcrModel):
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def __init__(
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self,
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enabled: bool,
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artifacts_path: Optional[Path],
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options: OnnxtrOcrOptions,
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accelerator_options: AcceleratorOptions,
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):
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super().__init__(
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enabled=enabled,
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artifacts_path=artifacts_path,
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options=options,
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accelerator_options=accelerator_options,
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)
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self.options: OnnxtrOcrOptions
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self.scale = 3 # multiplier for 72 dpi == 216 dpi.
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if self.enabled:
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try:
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from onnxtr.models import ocr_predictor, EngineConfig, from_hub # type: ignore
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except ImportError:
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raise ImportError(
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"OnnxTR is not installed. Please install it via `pip install 'onnxtr[gpu]'` to use this OCR engine. "
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"Alternatively, Docling has support for other OCR engines. See the documentation."
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)
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if options.auto_correct_orientation:
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config = {
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"assume_straight_pages": False,
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"straighten_pages": True,
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"export_as_straight_boxes": True,
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# Disable crop orientation because we straighten the pages already
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"disable_crop_orientation": True,
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"disable_page_orientation": False,
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}
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else:
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config = {
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"assume_straight_pages": True,
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"straighten_pages": False,
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"export_as_straight_boxes": True,
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"disable_crop_orientation": False,
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"disable_page_orientation": False,
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}
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self.reader = ocr_predictor(
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det_arch=from_hub(self.options.det_arch) if self.options.det_arch.count("/") == 1 else self.options.det_arch,
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reco_arch=from_hub(self.options.reco_arch) if self.options.reco_arch.count("/") == 1 else self.options.reco_arch,
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preserve_aspect_ratio=self.options.preserve_aspect_ratio,
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symmetric_pad=self.options.symmetric_pad,
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paragraph_break=self.options.paragraph_break,
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load_in_8_bit=self.options.load_in_8_bit,
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**config,
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)
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def _to_absolute_and_docling_format(self, geom: list[list[float]], img_shape: tuple[int, int]) -> tuple[int, int, int, int]:
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"""
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Convert a bounding box or polygon from relative to absolute coordinates and return in [x1, y1, x2, y2] format.
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Args:
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geom (list): Either [[xmin, ymin], [xmax, ymax]] or [[x1, y1], ..., [x4, y4]]
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img_shape (tuple[int, int]): (height, width) of the image
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Returns:
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tuple: (x1, y1, x2, y2)
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"""
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h, w = img_shape
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scale_inv = 1 / self.scale # Precompute inverse for efficiency
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def scale_point(x: float, y: float) -> tuple[int, int]:
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"""Scale and round a point to absolute coordinates."""
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return int(round(x * w * scale_inv)), int(round(y * h * scale_inv))
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if len(geom) == 2:
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(xmin, ymin), (xmax, ymax) = geom
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x1, y1 = scale_point(xmin, ymin)
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x2, y2 = scale_point(xmax, ymax)
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elif len(geom) == 4:
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abs_points = [scale_point(*point) for point in geom]
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x1, y1 = min(p[0] for p in abs_points), min(p[1] for p in abs_points)
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x2, y2 = max(p[0] for p in abs_points), max(p[1] for p in abs_points)
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else:
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raise ValueError(f"Invalid geometry format: {geom}. Expected either 2 or 4 points.")
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return x1, y1, x2, y2
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def __call__(self, conv_res: ConversionResult, page_batch: Iterable[Page]) -> Iterable[Page]:
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if not self.enabled:
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yield from page_batch
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return
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for page in page_batch:
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assert page._backend is not None
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if not page._backend.is_valid():
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yield page
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continue
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with TimeRecorder(conv_res, "ocr"):
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ocr_rects = self.get_ocr_rects(page)
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all_ocr_cells = []
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for ocr_rect in ocr_rects:
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if ocr_rect.area() == 0:
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continue
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with page._backend.get_page_image(scale=self.scale, cropbox=ocr_rect) as high_res_image:
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im_width, im_height = high_res_image.size
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result = self.reader([numpy.array(high_res_image)])
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if result is not None:
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for p in result.pages:
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for ix, word in enumerate(
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word
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for block in p.blocks
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for line in block.lines
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for word in line.words
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):
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all_ocr_cells.append(
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TextCell(
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index=ix,
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text=word.value,
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orig=word.value,
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from_ocr=True,
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confidence=word.confidence,
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rect=BoundingRectangle.from_bounding_box(
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BoundingBox.from_tuple(
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self._to_absolute_and_docling_format(
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word.geometry, img_shape=(im_height, im_width)
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),
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origin=CoordOrigin.TOPLEFT,
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)
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),
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)
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)
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# Post-process the cells
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page.cells = self.post_process_cells(all_ocr_cells, page.cells)
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# DEBUG code:
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if settings.debug.visualize_ocr:
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self.draw_ocr_rects_and_cells(conv_res, page, ocr_rects)
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yield page
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@classmethod
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def get_options_type(cls) -> Type[OcrOptions]:
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return OnnxtrOcrOptions
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@ -3,6 +3,7 @@ from docling.models.ocr_mac_model import OcrMacModel
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from docling.models.picture_description_api_model import PictureDescriptionApiModel
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from docling.models.picture_description_api_model import PictureDescriptionApiModel
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from docling.models.picture_description_vlm_model import PictureDescriptionVlmModel
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from docling.models.picture_description_vlm_model import PictureDescriptionVlmModel
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from docling.models.rapid_ocr_model import RapidOcrModel
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from docling.models.rapid_ocr_model import RapidOcrModel
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from docling.models.onnxtr_model import OnnxtrOcrModel
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from docling.models.tesseract_ocr_cli_model import TesseractOcrCliModel
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from docling.models.tesseract_ocr_cli_model import TesseractOcrCliModel
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from docling.models.tesseract_ocr_model import TesseractOcrModel
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from docling.models.tesseract_ocr_model import TesseractOcrModel
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@ -13,6 +14,7 @@ def ocr_engines():
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EasyOcrModel,
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EasyOcrModel,
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OcrMacModel,
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OcrMacModel,
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RapidOcrModel,
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RapidOcrModel,
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OnnxtrOcrModel,
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TesseractOcrModel,
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TesseractOcrModel,
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TesseractOcrCliModel,
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TesseractOcrCliModel,
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]
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]
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@ -72,11 +72,12 @@ openpyxl = "^3.1.5"
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lxml = ">=4.0.0,<6.0.0"
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lxml = ">=4.0.0,<6.0.0"
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ocrmac = { version = "^1.0.0", markers = "sys_platform == 'darwin'", optional = true }
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ocrmac = { version = "^1.0.0", markers = "sys_platform == 'darwin'", optional = true }
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rapidocr-onnxruntime = { version = "^1.4.0", optional = true, markers = "python_version < '3.13'" }
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rapidocr-onnxruntime = { version = "^1.4.0", optional = true, markers = "python_version < '3.13'" }
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onnxtr = { extras= ["gpu", "viz"], version = "^0.6.3", optional = true, markers = "python_version < '3.13'" }
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onnxruntime = [
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onnxruntime = [
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# 1.19.2 is the last version with python3.9 support,
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# 1.19.2 is the last version with python3.9 support,
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# see https://github.com/microsoft/onnxruntime/releases/tag/v1.20.0
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# see https://github.com/microsoft/onnxruntime/releases/tag/v1.20.0
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{ version = ">=1.7.0,<1.20.0", optional = true, markers = "python_version < '3.10'" },
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{ version = "^1.7.0", optional = true, markers = "python_version < '3.10'" },
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{ version = "^1.7.0", optional = true, markers = "python_version >= '3.10'" },
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{ version = ">=1.7.0,<1.20.0", optional = true, markers = "python_version >= '3.10'" },
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]
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]
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transformers = [
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transformers = [
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@ -13,6 +13,7 @@ from docling.datamodel.pipeline_options import (
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OcrOptions,
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OcrOptions,
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PdfPipelineOptions,
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PdfPipelineOptions,
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RapidOcrOptions,
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RapidOcrOptions,
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OnnxtrOcrOptions,
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TesseractCliOcrOptions,
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TesseractCliOcrOptions,
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TesseractOcrOptions,
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TesseractOcrOptions,
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)
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)
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@ -62,6 +63,7 @@ def test_e2e_conversions():
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TesseractOcrOptions(),
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TesseractOcrOptions(),
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TesseractCliOcrOptions(),
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TesseractCliOcrOptions(),
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EasyOcrOptions(force_full_page_ocr=True),
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EasyOcrOptions(force_full_page_ocr=True),
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OnnxtrOcrOptions(force_full_page_ocr=True),
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TesseractOcrOptions(force_full_page_ocr=True),
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TesseractOcrOptions(force_full_page_ocr=True),
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TesseractOcrOptions(force_full_page_ocr=True, lang=["auto"]),
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TesseractOcrOptions(force_full_page_ocr=True, lang=["auto"]),
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TesseractCliOcrOptions(force_full_page_ocr=True),
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TesseractCliOcrOptions(force_full_page_ocr=True),
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