import logging import sys import tempfile from collections.abc import Iterable from pathlib import Path from typing import Optional, Type from docling_core.types.doc import BoundingBox, CoordOrigin from docling_core.types.doc.page import BoundingRectangle, TextCell from docling.datamodel.base_models import Page from docling.datamodel.document import ConversionResult from docling.datamodel.pipeline_options import ( AcceleratorOptions, OcrMacOptions, OcrOptions, ) from docling.datamodel.settings import settings from docling.models.base_ocr_model import BaseOcrModel from docling.utils.profiling import TimeRecorder _log = logging.getLogger(__name__) class OcrMacModel(BaseOcrModel): def __init__( self, enabled: bool, artifacts_path: Optional[Path], options: OcrMacOptions, accelerator_options: AcceleratorOptions, ): super().__init__( enabled=enabled, artifacts_path=artifacts_path, options=options, accelerator_options=accelerator_options, ) self.options: OcrMacOptions self.scale = 3 # multiplier for 72 dpi == 216 dpi. if self.enabled: if "darwin" != sys.platform: raise RuntimeError("OcrMac is only supported on Mac.") install_errmsg = ( "ocrmac is not correctly installed. " "Please install it via `pip install ocrmac` to use this OCR engine. " "Alternatively, Docling has support for other OCR engines. See the documentation: " "https://docling-project.github.io/docling/installation/" ) try: from ocrmac import ocrmac except ImportError: raise ImportError(install_errmsg) self.reader_RIL = ocrmac.OCR def __call__( self, conv_res: ConversionResult, page_batch: Iterable[Page] ) -> Iterable[Page]: if not self.enabled: yield from page_batch return for page in page_batch: assert page._backend is not None if not page._backend.is_valid(): yield page else: with TimeRecorder(conv_res, "ocr"): ocr_rects = self.get_ocr_rects(page) all_ocr_cells = [] for ocr_rect in ocr_rects: # Skip zero area boxes if ocr_rect.area() == 0: continue high_res_image = page._backend.get_page_image( scale=self.scale, cropbox=ocr_rect ) with tempfile.NamedTemporaryFile( suffix=".png", mode="w" ) as image_file: fname = image_file.name high_res_image.save(fname) boxes = self.reader_RIL( fname, recognition_level=self.options.recognition, framework=self.options.framework, language_preference=self.options.lang, ).recognize() im_width, im_height = high_res_image.size cells = [] for ix, (text, confidence, box) in enumerate(boxes): x = float(box[0]) y = float(box[1]) w = float(box[2]) h = float(box[3]) x1 = x * im_width y2 = (1 - y) * im_height x2 = x1 + w * im_width y1 = y2 - h * im_height left = x1 / self.scale top = y1 / self.scale right = x2 / self.scale bottom = y2 / self.scale cells.append( TextCell( index=ix, text=text, orig=text, from_ocr=True, confidence=confidence, rect=BoundingRectangle.from_bounding_box( BoundingBox.from_tuple( coord=(left, top, right, bottom), origin=CoordOrigin.TOPLEFT, ) ), ) ) # del high_res_image all_ocr_cells.extend(cells) # Post-process the cells page.cells = self.post_process_cells(all_ocr_cells, page.cells) # DEBUG code: if settings.debug.visualize_ocr: self.draw_ocr_rects_and_cells(conv_res, page, ocr_rects) yield page @classmethod def get_options_type(cls) -> Type[OcrOptions]: return OcrMacOptions