mmocr/docs/en/project_zoo.py

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#!/usr/bin/env python
import os.path as osp
import re
# This script reads /projects/selected.txt and generate projectzoo.md
files = []
project_zoo = """
# SOTA Models
Here are some selected project implementations that are not yet included in
MMOCR package, but are ready to use.
"""
files = open('../../projects/selected.txt').readlines()
for file in files:
file = file.strip()
with open(osp.join('../../', file)) as f:
content = f.read()
# Extract title
expr = '# (.*?)\n'
title = re.search(expr, content).group(1)
project_zoo += f'## {title}\n\n'
# Locate the description
expr = '## Description\n(.*?)##'
description = re.search(expr, content, re.DOTALL).group(1)
project_zoo += f'{description}\n'
# check milestone 1
expr = r'- \[(.?)\] Milestone 1'
state = re.search(expr, content, re.DOTALL).group(1)
infer_state = '' if state == 'x' else ''
# check milestone 2
expr = r'- \[(.?)\] Milestone 2'
state = re.search(expr, content, re.DOTALL).group(1)
training_state = '' if state == 'x' else ''
# add table
readme_link = f'https://github.com/open-mmlab/mmocr/blob/dev-1.x/{file}'
project_zoo += '### Status \n'
project_zoo += '| Inference | Train | README |\n'
project_zoo += '| --------- | -------- | ------ |\n'
project_zoo += f'|{infer_state}|{training_state}|[link]({readme_link})|\n'
with open('projectzoo.md', 'w') as f:
f.write(project_zoo)