2a2c65bf4f
* Add settings to turn visualization on or off Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Add profiling code to all models Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Refactor and fix profiling codes Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Visualization codes output PNG to debug dir Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fixes for time logging Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Optimize imports Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update lockfile Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Add start_timestamps to ProfilingItem Signed-off-by: Christoph Auer <cau@zurich.ibm.com> --------- Signed-off-by: Christoph Auer <cau@zurich.ibm.com>
101 lines
3.7 KiB
Python
101 lines
3.7 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 EasyOcrOptions
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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 EasyOcrModel(BaseOcrModel):
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def __init__(self, enabled: bool, options: EasyOcrOptions):
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super().__init__(enabled=enabled, options=options)
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self.options: EasyOcrOptions
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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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import easyocr
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except ImportError:
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raise ImportError(
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"EasyOCR is not installed. Please install it via `pip install easyocr` 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 = easyocr.Reader(
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lang_list=self.options.lang,
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model_storage_directory=self.options.model_storage_directory,
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download_enabled=self.options.download_enabled,
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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.readtext(im)
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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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## Remove OCR cells which overlap with programmatic cells.
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filtered_ocr_cells = self.filter_ocr_cells(
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all_ocr_cells, page.cells
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)
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page.cells.extend(filtered_ocr_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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