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