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158 lines
5.3 KiB
Python
158 lines
5.3 KiB
Python
import os
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import click
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from jinja2 import Environment, FileSystemLoader
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from markupsafe import escape
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from uniseg.graphemecluster import grapheme_clusters
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from .character_error_rate import character_error_rate_n
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from .word_error_rate import word_error_rate_n, words_normalized
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from .align import seq_align
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from .extracted_text import ExtractedText
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from .ocr_files import extract
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def gen_diff_report(gt_in, ocr_in, css_prefix, joiner, none):
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gtx = ''
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ocrx = ''
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def format_thing(t, css_classes=None, id_=None):
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if t is None:
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html_t = none
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css_classes += ' ellipsis'
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elif t == '\n':
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html_t = '<br>'
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else:
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html_t = escape(t)
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html_custom_attrs = ""
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# Set Bootstrap tooltip to the segment id
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if id_:
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html_custom_attrs += 'data-toggle="tooltip" title="{}"'.format(id_)
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if css_classes:
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return '<span class="{css_classes}" {html_custom_attrs}>{html_t}</span>'.format(css_classes=css_classes, html_t=html_t, html_custom_attrs=html_custom_attrs)
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else:
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return '{html_t}'.format(html_t=html_t)
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if isinstance(gt_in, ExtractedText):
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if not isinstance(ocr_in, ExtractedText):
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raise TypeError()
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# XXX splitting should be done in ExtractedText
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gt_things = list(grapheme_clusters(gt_in.text))
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ocr_things = list(grapheme_clusters(ocr_in.text))
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else:
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gt_things = gt_in
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ocr_things = ocr_in
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g_pos = 0
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o_pos = 0
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for k, (g, o) in enumerate(seq_align(gt_things, ocr_things)):
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css_classes = None
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gt_id = None
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ocr_id = None
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if g != o:
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css_classes = '{css_prefix}diff{k} diff'.format(css_prefix=css_prefix, k=k)
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if isinstance(gt_in, ExtractedText):
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gt_id = gt_in.segment_id_for_pos(g_pos) if g is not None else None
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ocr_id = ocr_in.segment_id_for_pos(o_pos) if o is not None else None
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# Deletions and inserts only produce one id + None, UI must
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# support this, i.e. display for the one id produced
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gtx += joiner + format_thing(g, css_classes, gt_id)
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ocrx += joiner + format_thing(o, css_classes, ocr_id)
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if g is not None:
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g_pos += len(g)
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if o is not None:
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o_pos += len(o)
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return \
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'''
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<div class="row">
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<div class="col-md-6 gt">{}</div>
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<div class="col-md-6 ocr">{}</div>
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</div>
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'''.format(gtx, ocrx)
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def process(gt, ocr, report_prefix, *, metrics=True):
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"""Check OCR result against GT.
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The @click decorators change the signature of the decorated functions, so we keep this undecorated version and use
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Click on a wrapper.
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"""
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gt_text = extract(gt)
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ocr_text = extract(ocr)
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cer, n_characters = character_error_rate_n(gt_text, ocr_text)
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wer, n_words = word_error_rate_n(gt_text, ocr_text)
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char_diff_report = gen_diff_report(gt_text, ocr_text, css_prefix='c', joiner='', none='·')
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gt_words = words_normalized(gt_text)
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ocr_words = words_normalized(ocr_text)
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word_diff_report = gen_diff_report(gt_words, ocr_words, css_prefix='w', joiner=' ', none='⋯')
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def json_float(value):
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"""Convert a float value to an JSON float.
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This is here so that float('inf') yields "Infinity", not "inf".
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"""
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if value == float('inf'):
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return 'Infinity'
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elif value == float('-inf'):
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return '-Infinity'
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else:
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return str(value)
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env = Environment(loader=FileSystemLoader(os.path.join(os.path.dirname(os.path.realpath(__file__)), 'templates')))
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env.filters['json_float'] = json_float
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for report_suffix in ('.html', '.json'):
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template_fn = 'report' + report_suffix + '.j2'
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out_fn = report_prefix + report_suffix
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template = env.get_template(template_fn)
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template.stream(
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gt=gt, ocr=ocr,
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cer=cer, n_characters=n_characters,
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wer=wer, n_words=n_words,
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char_diff_report=char_diff_report,
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word_diff_report=word_diff_report,
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metrics=metrics,
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).dump(out_fn)
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@click.command()
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@click.argument('gt', type=click.Path(exists=True))
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@click.argument('ocr', type=click.Path(exists=True))
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@click.argument('report_prefix', type=click.Path(), default='report')
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@click.option('--metrics/--no-metrics', default=True, help='Enable/disable metrics and green/red')
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def main(gt, ocr, report_prefix, metrics):
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"""
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Compare the PAGE/ALTO/text document GT against the document OCR.
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dinglehopper detects if GT/OCR are ALTO or PAGE XML documents to extract
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their text and falls back to plain text if no ALTO or PAGE is detected.
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The files GT and OCR are usually a ground truth document and the result of
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an OCR software, but you may use dinglehopper to compare two OCR results. In
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that case, use --no-metrics to disable the then meaningless metrics and also
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change the color scheme from green/red to blue.
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The comparison report will be written to $REPORT_PREFIX.{html,json}, where
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$REPORT_PREFIX defaults to "report". The reports include the character error
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rate (CER) and the word error rate (WER).
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"""
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process(gt, ocr, report_prefix, metrics=metrics)
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if __name__ == '__main__':
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main()
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