Initial snapshot: hand motion pipeline (Dyn-HaMR + dex-retargeting + SPIDER)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-09-15 14:13:49 +08:00
commit 7e4ef6f98b
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+#!/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') 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') 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') 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') as f:
+    f.write(modelzoo)