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cli: produce TSV if no words are transcribed
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1 changed files with 10 additions and 6 deletions
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@ -101,12 +101,16 @@ def page2tsv(page_xml_file, tsv_out_file, purpose, image_url, ner_rest_endpoint,
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text_equiv.get_Unicode(), len(urls), left, right, top, bottom, text_line.id))
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text_equiv.get_Unicode(), len(urls), left, right, top, bottom, text_line.id))
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else:
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else:
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for word in words:
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for word in words:
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for text_equiv in word.get_TextEquiv():
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# XXX TODO make this configurable
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# transform OCR coordinates using `scale_factor` to derive
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textequiv = ''
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# correct coordinates for the web presentation image
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list_textequivs = word.get_TextEquiv()
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left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(word.get_Coords().points)]
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if list_textequivs:
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tsv.append((region_idx, len(line_info) - 1, left + (right - left) / 2.0,
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textequiv = list_textequivs[0].get_Unicode()
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text_equiv.get_Unicode(), len(urls), left, right, top, bottom, text_line.id))
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# transform OCR coordinates using `scale_factor` to derive
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# correct coordinates for the web presentation image
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left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(word.get_Coords().points)]
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tsv.append((region_idx, len(line_info) - 1, left + (right - left) / 2.0,
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textequiv, len(urls), left, right, top, bottom, text_line.id))
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line_info = pd.DataFrame(line_info, columns=['url_id', 'left', 'right', 'top', 'bottom', 'conf', 'line_id'])
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line_info = pd.DataFrame(line_info, columns=['url_id', 'left', 'right', 'top', 'bottom', 'conf', 'line_id'])
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