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104 lines
4.2 KiB
Python
104 lines
4.2 KiB
Python
import logging
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from typing import Iterable
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import numpy
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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.document import ConversionResult
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from docling.datamodel.pipeline_options import RapidOcrOptions
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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.profiling import TimeRecorder
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_log = logging.getLogger(__name__)
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class RapidOcrModel(BaseOcrModel):
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def __init__(self, enabled: bool, options: RapidOcrOptions):
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super().__init__(enabled=enabled, options=options)
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self.options: RapidOcrOptions
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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 rapidocr_onnxruntime import RapidOCR
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except ImportError:
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raise ImportError(
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"RapidOCR is not installed. Please install it via `pip install rapidocr_onnxruntime` 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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self.reader = RapidOCR(
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text_score = self.options.text_score,
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cls_use_cuda = self.options.cls_use_cuda,
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rec_use_cuda = self.options.rec_use_cuda,
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det_use_cuda = self.options.det_use_cuda,
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det_use_dml = self.options.det_use_dml,
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cls_use_dml = self.options.cls_use_dml,
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rec_use_dml = self.options.rec_use_dml,
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print_verbose = self.options.print_verbose,
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det_model_path = self.options.det_model_path,
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cls_model_path = self.options.cls_model_path,
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rec_model_path = self.options.rec_model_path,
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)
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def __call__(
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self, conv_res: ConversionResult, page_batch: Iterable[Page]
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) -> 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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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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# 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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im = numpy.array(high_res_image)
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result, _ = self.reader(im, use_det=self.options.use_det, use_cls=self.options.use_cls, use_rec=self.options.use_rec)
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del high_res_image
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del im
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cells = [
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OcrCell(
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id=ix,
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text=line[1],
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confidence=line[2],
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bbox=BoundingBox.from_tuple(
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coord=(
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(line[0][0][0] / self.scale) + ocr_rect.l,
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(line[0][0][1] / self.scale) + ocr_rect.t,
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(line[0][2][0] / self.scale) + ocr_rect.l,
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(line[0][2][1] / self.scale) + ocr_rect.t,
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),
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origin=CoordOrigin.TOPLEFT,
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),
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)
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for ix, line in enumerate(result)
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]
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all_ocr_cells.extend(cells)
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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 |