|
|
|
import functools as func |
|
import glob |
|
import os.path as osp |
|
import re |
|
|
|
import numpy as np |
|
|
|
url_prefix = 'https://github.com/open-mmlab/mmyolo/blob/main/' |
|
|
|
files = sorted(glob.glob('../configs/*/README.md')) |
|
|
|
stats = [] |
|
titles = [] |
|
num_ckpts = 0 |
|
|
|
for f in files: |
|
url = osp.dirname(f.replace('../', url_prefix)) |
|
|
|
with open(f) as content_file: |
|
content = content_file.read() |
|
|
|
title = content.split('\n')[0].replace('# ', '').strip() |
|
ckpts = { |
|
x.lower().strip() |
|
for x in re.findall(r'\[model\]\((https?.*)\)', content) |
|
} |
|
|
|
if len(ckpts) == 0: |
|
continue |
|
|
|
_papertype = [x for x in re.findall(r'\[([A-Z]+)\]', content)] |
|
assert len(_papertype) > 0 |
|
papertype = _papertype[0] |
|
|
|
paper = {(papertype, title)} |
|
|
|
titles.append(title) |
|
num_ckpts += len(ckpts) |
|
|
|
statsmsg = f""" |
|
\t* [{papertype}] [{title}]({url}) ({len(ckpts)} ckpts) |
|
""" |
|
stats.append((paper, ckpts, statsmsg)) |
|
|
|
allpapers = func.reduce(lambda a, b: a.union(b), [p for p, _, _ in stats]) |
|
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""" |
|
# Model Zoo Statistics |
|
|
|
* Number of papers: {len(set(titles))} |
|
{countstr} |
|
|
|
* Number of checkpoints: {num_ckpts} |
|
|
|
{msglist} |
|
""" |
|
|
|
with open('modelzoo_statistics.md', 'w') as f: |
|
f.write(modelzoo) |
|
|