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import json
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import os
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import tempfile
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import click
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import ocrd_models.ocrd_page
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from ocrd import Processor
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from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
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from ocrd_modelfactory import page_from_file
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from ocrd_models import OcrdFile
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from ocrd_models.ocrd_page_generateds import MetadataItemType, LabelsType, LabelType
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from ocrd_utils import concat_padded, getLogger, MIMETYPE_PAGE
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from pkg_resources import resource_string
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from qurator.sbb_textline_detector import textline_detector
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log = getLogger('processor.OcrdSbbTextlineDetectorRecognize')
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OCRD_TOOL = json.loads(resource_string(__name__, 'ocrd-tool.json').decode('utf8'))
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@click.command()
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@ocrd_cli_options
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def ocrd_sbb_textline_detector(*args, **kwargs):
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return ocrd_cli_wrap_processor(OcrdSbbTextlineDetectorRecognize, *args, **kwargs)
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TOOL = 'ocrd-sbb-textline-detector'
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class OcrdSbbTextlineDetectorRecognize(Processor):
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def __init__(self, *args, **kwargs):
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kwargs['ocrd_tool'] = OCRD_TOOL['tools'][TOOL]
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kwargs['version'] = OCRD_TOOL['version']
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super(OcrdSbbTextlineDetectorRecognize, self).__init__(*args, **kwargs)
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def _make_file_id(self, input_file, input_file_grp, n):
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file_id = input_file.ID.replace(input_file_grp, self.output_file_grp)
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if file_id == input_file.ID:
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file_id = concat_padded(self.output_file_grp, n)
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return file_id
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def _resolve_image_file(self, input_file: OcrdFile) -> str:
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if input_file.mimetype == MIMETYPE_PAGE:
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pcgts = page_from_file(self.workspace.download_file(input_file))
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page = pcgts.get_Page()
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image_file = page.imageFilename
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else:
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image_file = input_file.local_filename
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return image_file
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def process(self):
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for (n, input_file) in enumerate(self.input_files):
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page_id = input_file.pageId or input_file.ID
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log.info("INPUT FILE %i / %s", n, input_file)
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file_id = self._make_file_id(input_file, self.input_file_grp, n)
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# Process the files
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try:
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os.mkdir(self.output_file_grp)
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except FileExistsError:
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pass
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with tempfile.TemporaryDirectory() as tmp_dirname:
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# Segment the image
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image_file = self._resolve_image_file(input_file)
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model = self.parameter['model']
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x = textline_detector(image_file, tmp_dirname, file_id, model)
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x.run()
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# Read segmentation results
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tmp_filename = os.path.join(tmp_dirname, file_id) + '.xml'
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tmp_pcgts = ocrd_models.ocrd_page.parse(tmp_filename, silence=True)
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tmp_page = tmp_pcgts.get_Page()
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# Create a new PAGE file from the input file
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pcgts = page_from_file(self.workspace.download_file(input_file))
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page = pcgts.get_Page()
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# Merge results → PAGE file
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if page.get_PrintSpace():
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log.warning("Page already contained a printspace")
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page.set_PrintSpace(tmp_page.get_PrintSpace())
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if page.get_ReadingOrder():
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log.warning("Page already contained a reading order")
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page.set_ReadingOrder(tmp_page.get_ReadingOrder())
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if page.get_TextRegion():
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log.warning("Page already contained text regions")
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page.set_TextRegion(tmp_page.get_TextRegion())
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# Save metadata about this operation
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metadata = pcgts.get_Metadata()
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metadata.add_MetadataItem(
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MetadataItemType(type_="processingStep",
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name=self.ocrd_tool['steps'][0],
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value=TOOL,
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Labels=[LabelsType(
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externalModel="ocrd-tool",
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externalId="parameters",
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Label=[LabelType(type_=name, value=self.parameter[name])
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for name in self.parameter.keys()])]))
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self.workspace.add_file(
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ID=file_id,
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file_grp=self.output_file_grp,
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pageId=page_id,
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mimetype='application/vnd.prima.page+xml',
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local_filename=os.path.join(self.output_file_grp, file_id) + '.xml',
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content=ocrd_models.ocrd_page.to_xml(pcgts)
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)
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if __name__ == '__main__':
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ocrd_sbb_textline_detector()
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