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@ -1,3 +1,4 @@
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import numpy as np
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import click
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import pandas as pd
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from io import StringIO
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@ -9,6 +10,7 @@ import json
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from .ned import ned
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from .ner import ner
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from .tsv import read_tsv, write_tsv, extract_doc_links
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from .ocr import get_conf_color
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@click.command()
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@ -67,13 +69,18 @@ def annotate_tsv(tsv_file, annotated_tsv_file):
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@click.option('--noproxy', type=bool, is_flag=True, help='disable proxy. default: enabled.')
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@click.option('--scale-factor', type=float, default=0.5685, help='default: 0.5685')
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@click.option('--ned-threshold', type=float, default=None)
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@click.option('--min-confidence', type=float, default=None)
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@click.option('--max-confidence', type=float, default=None)
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def page2tsv(page_xml_file, tsv_out_file, purpose, image_url, ner_rest_endpoint, ned_rest_endpoint, noproxy, scale_factor,
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ned_threshold):
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ned_threshold, min_confidence, max_confidence):
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if purpose == "NERD":
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out_columns = ['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'ID', 'url_id', 'left', 'right', 'top', 'bottom']
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elif purpose == "OCR":
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out_columns = ['TEXT', 'url_id', 'left', 'right', 'top', 'bottom']
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if min_confidence is not None and max_confidence is not None:
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out_columns += ['ocrconf']
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else:
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raise RuntimeError("Unknown purpose.")
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@ -107,7 +114,12 @@ def page2tsv(page_xml_file, tsv_out_file, purpose, image_url, ner_rest_endpoint,
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left, right, top, bottom = min(x_points), max(x_points), min(y_points), max(y_points)
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line_info.append((line_number, len(urls), left, right, top, bottom))
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if min_confidence is not None and max_confidence is not None:
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conf = np.mean([float(text.attrib['conf']) for text in text_line.findall('./{%s}TextEquiv' % xmlns)])
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else:
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conf = np.nan
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line_info.append((line_number, len(urls), left, right, top, bottom, conf))
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for word in text_line.findall('./{%s}Word' % xmlns):
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@ -128,7 +140,10 @@ def page2tsv(page_xml_file, tsv_out_file, purpose, image_url, ner_rest_endpoint,
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tsv.append((rgn_number, line_number, left + (right - left) / 2.0, text,
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len(urls), left, right, top, bottom))
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line_info = pd.DataFrame(line_info, columns=['line', 'url_id', 'left', 'right', 'top', 'bottom'])
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line_info = pd.DataFrame(line_info, columns=['line', 'url_id', 'left', 'right', 'top', 'bottom', 'conf'])
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if min_confidence is not None and max_confidence is not None:
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line_info['ocrconf'] = line_info.conf.map(lambda x: get_conf_color(x, min_confidence, max_confidence))
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tsv = pd.DataFrame(tsv, columns=['rid', 'line', 'hcenter'] + ['TEXT', 'url_id', 'left', 'right', 'top', 'bottom'])
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