mmpose-0.29.0/docs/en/stats.py

#!/usr/bin/env python
# Copyright (c) OpenMMLab. All rights reserved.
import functools as func
import glob
import re
from os.path import basename, splitext

import numpy as np
import titlecase


def anchor(name):
 return re.sub(r'-+', '-', re.sub(r'[^a-zA-Z0-9]', '-',
 name.strip().lower())).strip('-')


# Count algorithms

files = sorted(glob.glob('topics/*.md'))

stats = []

for f in files:
 with open(f, 'r', encoding='utf-8') as content_file:
 content = content_file.read()

 # title
 title = content.split('\n')[0].replace('#', '')

 # count papers
 papers = set(
 (papertype, titlecase.titlecase(paper.lower().strip()))
 for (papertype, paper) in re.findall(
 r'<!--\s*\[([A-Z]*?)\]\s*-->\s*\n.*?\btitle\s*=\s*{(.*?)}',
 content, re.DOTALL))
 # paper links
 revcontent = '\n'.join(list(reversed(content.splitlines())))
 paperlinks = {}
 for _, p in papers:
 print(p)
 paperlinks[p] = ', '.join(
 ((f'[{paperlink} ⇨]'
 f'(topics/{splitext(basename(f))[0]}.html#{anchor(paperlink)})')
 for paperlink in re.findall(
 rf'\btitle\s*=\s*{{\s*{p}\s*}}.*?\n### (.*?)\s*[,;]?\s*\n',
 revcontent, re.DOTALL | re.IGNORECASE)))
 print(' ', paperlinks[p])
 paperlist = '\n'.join(
 sorted(f' - [{t}] {x} ({paperlinks[x]})' for t, x in papers))
 # count configs
 configs = set(x.lower().strip()
 for x in re.findall(r'.*configs/.*\.py', content))

 # count ckpts
 ckpts = set(x.lower().strip()
 for x in re.findall(r'https://download.*\.pth', content)
 if 'mmpose' in x)

 statsmsg = f"""
## [{title}]({f})

* Number of checkpoints: {len(ckpts)}
* Number of configs: {len(configs)}
* Number of papers: {len(papers)}
{paperlist}

 """

 stats.append((papers, configs, ckpts, statsmsg))

allpapers = func.reduce(lambda a, b: a.union(b), [p for p, _, _, _ in stats])
allconfigs = func.reduce(lambda a, b: a.union(b), [c for _, c, _, _ in stats])
allckpts = func.reduce(lambda a, b: a.union(b), [c for _, _, c, _ in stats])

# Summarize

msglist = '\n'.join(x for _, _, _, x in stats)
papertypes, papercounts = np.unique([t for t, _ in allpapers],
 return_counts=True)
countstr = '\n'.join(
 [f' - {t}: {c}' for t, c in zip(papertypes, papercounts)])

modelzoo = f"""
# Overview

* Number of checkpoints: {len(allckpts)}
* Number of configs: {len(allconfigs)}
* Number of papers: {len(allpapers)}
{countstr}

For supported datasets, see [datasets overview](datasets.md).

{msglist}

"""

with open('modelzoo.md', 'w', encoding='utf-8') as f:
 f.write(modelzoo)

# Count datasets

files = sorted(glob.glob('tasks/*.md'))
# files = sorted(glob.glob('docs/tasks/*.md'))

datastats = []

for f in files:
 with open(f, 'r', encoding='utf-8') as content_file:
 content = content_file.read()

 # title
 title = content.split('\n')[0].replace('#', '')

 # count papers
 papers = set(
 (papertype, titlecase.titlecase(paper.lower().strip()))
 for (papertype, paper) in re.findall(
 r'<!--\s*\[([A-Z]*?)\]\s*-->\s*\n.*?\btitle\s*=\s*{(.*?)}',
 content, re.DOTALL))
 # paper links
 revcontent = '\n'.join(list(reversed(content.splitlines())))
 paperlinks = {}
 for _, p in papers:
 print(p)
 paperlinks[p] = ', '.join(
 (f'[{p} ⇨](tasks/{splitext(basename(f))[0]}.html#{anchor(p)})'
 for p in re.findall(
 rf'\btitle\s*=\s*{{\s*{p}\s*}}.*?\n## (.*?)\s*[,;]?\s*\n',
 revcontent, re.DOTALL | re.IGNORECASE)))
 print(' ', paperlinks[p])
 paperlist = '\n'.join(
 sorted(f' - [{t}] {x} ({paperlinks[x]})' for t, x in papers))
 # count configs
 configs = set(x.lower().strip()
 for x in re.findall(r'https.*configs/.*\.py', content))

 # count ckpts
 ckpts = set(x.lower().strip()
 for x in re.findall(r'https://download.*\.pth', content)
 if 'mmpose' in x)

 statsmsg = f"""
## [{title}]({f})

* Number of papers: {len(papers)}
{paperlist}

 """

 datastats.append((papers, configs, ckpts, statsmsg))

alldatapapers = func.reduce(lambda a, b: a.union(b),
 [p for p, _, _, _ in datastats])

# Summarize

msglist = '\n'.join(x for _, _, _, x in stats)
datamsglist = '\n'.join(x for _, _, _, x in datastats)
papertypes, papercounts = np.unique([t for t, _ in alldatapapers],
 return_counts=True)
countstr = '\n'.join(
 [f' - {t}: {c}' for t, c in zip(papertypes, papercounts)])

modelzoo = f"""
# Overview

* Number of papers: {len(alldatapapers)}
{countstr}

For supported pose algorithms, see [modelzoo overview](modelzoo.md).

{datamsglist}
"""

with open('datasets.md', 'w', encoding='utf-8') as f:
 f.write(modelzoo)