3b53bd38c8
* Update easyocr_model.py Added this line of code to get recog_network of easyocr parameter recog_network = self.options.recog_network Signed-off-by: itsainii <aininawawii@gmail.com> * Update pipeline_options.py Added this line in EasyOcrOptions function recog_network: Optional[str] = 'standard' Signed-off-by: itsainii <aininawawii@gmail.com> * Add Easyocr recog_network parameter Signed-off-by: itsainii <aininawawii@gmail.com> --------- Signed-off-by: itsainii <aininawawii@gmail.com>
132 lines
4.8 KiB
Python
132 lines
4.8 KiB
Python
import logging
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import warnings
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from typing import Iterable
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import numpy
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import torch
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from docling_core.types.doc import BoundingBox, CoordOrigin
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from docling.datamodel.base_models import Cell, OcrCell, 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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EasyOcrOptions,
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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 EasyOcrModel(BaseOcrModel):
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def __init__(
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self,
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enabled: bool,
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options: EasyOcrOptions,
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accelerator_options: AcceleratorOptions,
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):
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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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if self.options.use_gpu is None:
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device = decide_device(accelerator_options.device)
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# Enable easyocr GPU if running on CUDA, MPS
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use_gpu = any(
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[
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device.startswith(x)
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for x in [
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AcceleratorDevice.CUDA.value,
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AcceleratorDevice.MPS.value,
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]
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]
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)
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else:
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warnings.warn(
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"Deprecated field. Better to set the `accelerator_options.device` in `pipeline_options`. "
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"When `use_gpu and accelerator_options.device == AcceleratorDevice.CUDA` the GPU is used "
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"to run EasyOCR. Otherwise, EasyOCR runs in CPU."
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)
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use_gpu = self.options.use_gpu
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self.reader = easyocr.Reader(
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lang_list=self.options.lang,
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gpu=use_gpu,
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model_storage_directory=self.options.model_storage_directory,
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recog_network=self.options.recog_network,
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download_enabled=self.options.download_enabled,
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verbose=False,
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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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# 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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