131 lines
4.9 KiB
Python
131 lines
4.9 KiB
Python
import logging
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from typing import Iterable
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from docling_core.types.doc import BoundingBox, CoordOrigin
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from docling.datamodel.base_models import OcrCell, Page
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from docling.datamodel.pipeline_options import TesseractOcrOptions
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from docling.models.base_ocr_model import BaseOcrModel
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_log = logging.getLogger(__name__)
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class TesseractOcrModel(BaseOcrModel):
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def __init__(self, enabled: bool, options: TesseractOcrOptions):
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super().__init__(enabled=enabled, options=options)
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self.options: TesseractOcrOptions
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self.scale = 3 # multiplier for 72 dpi == 216 dpi.
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self.reader = None
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if self.enabled:
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setup_errmsg = (
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"tesserocr is not correctly installed. "
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"Please install it via `pip install tesserocr` to use this OCR engine. "
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"Note that tesserocr might have to be manually compiled for working with"
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"your Tesseract installation. The Docling documentation provides examples for it. "
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"Alternatively, Docling has support for other OCR engines. See the documentation."
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)
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try:
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import tesserocr
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except ImportError:
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raise ImportError(setup_errmsg)
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try:
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tesseract_version = tesserocr.tesseract_version()
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_log.debug("Initializing TesserOCR: %s", tesseract_version)
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except:
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raise ImportError(setup_errmsg)
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# Initialize the tesseractAPI
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lang = "+".join(self.options.lang)
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if self.options.path is not None:
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self.reader = tesserocr.PyTessBaseAPI(
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path=self.options.path,
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lang=lang,
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psm=tesserocr.PSM.AUTO,
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init=True,
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oem=tesserocr.OEM.DEFAULT,
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)
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else:
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self.reader = tesserocr.PyTessBaseAPI(
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lang=lang,
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psm=tesserocr.PSM.AUTO,
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init=True,
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oem=tesserocr.OEM.DEFAULT,
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)
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self.reader_RIL = tesserocr.RIL
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def __del__(self):
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if self.reader is not None:
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# Finalize the tesseractAPI
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self.reader.End()
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def __call__(self, 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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else:
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assert self.reader is not None
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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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# Skip zero area boxes
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if ocr_rect.area() == 0:
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continue
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high_res_image = page._backend.get_page_image(
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scale=self.scale, cropbox=ocr_rect
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)
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# Retrieve text snippets with their bounding boxes
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self.reader.SetImage(high_res_image)
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boxes = self.reader.GetComponentImages(
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self.reader_RIL.TEXTLINE, True
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)
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cells = []
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for ix, (im, box, _, _) in enumerate(boxes):
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# Set the area of interest. Tesseract uses Bottom-Left for the origin
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self.reader.SetRectangle(box["x"], box["y"], box["w"], box["h"])
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# Extract text within the bounding box
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text = self.reader.GetUTF8Text().strip()
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confidence = self.reader.MeanTextConf()
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left = box["x"] / self.scale
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bottom = box["y"] / self.scale
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right = (box["x"] + box["w"]) / self.scale
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top = (box["y"] + box["h"]) / self.scale
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cells.append(
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OcrCell(
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id=ix,
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text=text,
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confidence=confidence,
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bbox=BoundingBox.from_tuple(
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coord=(left, top, right, bottom),
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origin=CoordOrigin.TOPLEFT,
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),
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)
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)
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# del high_res_image
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all_ocr_cells.extend(cells)
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## Remove OCR cells which overlap with programmatic cells.
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filtered_ocr_cells = self.filter_ocr_cells(all_ocr_cells, page.cells)
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page.cells.extend(filtered_ocr_cells)
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# DEBUG code:
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# self.draw_ocr_rects_and_cells(page, ocr_rects)
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yield page
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