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#!/usr/bin/env python
import os
import os.path as osp
import re
import yaml
dataset_zoo_path = '../../dataset_zoo'
datasets = os.listdir(dataset_zoo_path)
datasets.sort()
table = '# Overview\n'
table += '## Supported Datasets\n'
table += '| Dataset Name | Text Detection | Text Recognition | Text Spotting | KIE |\n' \
'|--------------|----------------|------------------|---------------|-----|\n' # noqa: E501
details = '## Dataset Details\n'
for dataset in datasets:
meta = yaml.safe_load(
open(osp.join(dataset_zoo_path, dataset, 'metafile.yml')))
dataset_name = meta['Name']
detail_link = re.sub('[^A-Za-z0-9- ]', '',
dataset_name).replace(' ', '-').lower()
paper = meta['Paper']
data = meta['Data']
table += '| [{}](#{}) | {} | {} | {} | {} |\n'.format(
dataset,
detail_link,
'✓' if 'textdet' in data['Tasks'] else '',
'✓' if 'textrecog' in data['Tasks'] else '',
'✓' if 'textspotting' in data['Tasks'] else '',
'✓' if 'kie' in data['Tasks'] else '',
)
details += '### {}\n'.format(dataset_name)
details += "> \"{}\", *{}*, {}. [PDF]({})\n\n".format(
paper['Title'], paper['Venue'], paper['Year'], paper['URL'])
# Basic Info
details += 'A. Basic Info\n'
details += ' - Official Website: [{}]({})\n'.format(
dataset, data['Website'])
details += ' - Year: {}\n'.format(paper['Year'])
details += ' - Language: {}\n'.format(data['Language'])
details += ' - Scene: {}\n'.format(data['Scene'])
details += ' - Annotation Granularity: {}\n'.format(data['Granularity'])
details += ' - Supported Tasks: {}\n'.format(data['Tasks'])
details += ' - License: [{}]({})\n'.format(data['License']['Type'],
data['License']['Link'])
# Format
details += '<details> <summary>B. Annotation Format</summary>\n\n</br>'
sample_path = osp.join(dataset_zoo_path, dataset, 'sample_anno.md')
if osp.exists(sample_path):
with open(sample_path, 'r') as f:
samples = f.readlines()
samples = ''.join(samples)
details += samples
details += '</details>\n\n</br>'
# Reference
details += 'C. Reference\n'
details += '```bibtex\n{}\n```\n'.format(paper['BibTeX'])
datasetzoo = table + details
with open('user_guides/data_prepare/datasetzoo.md', 'w') as f:
f.write(datasetzoo)
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