File size: 2,843 Bytes
4949db9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | """Report video coverage and how many people are needed to reach 3x.
Usage:
python -m evals.human_eval.coverage_report
python -m evals.human_eval.coverage_report --batch-size 11
"""
from __future__ import annotations
import argparse
import sqlite3
import sys
from collections import Counter
from evals.human_eval.config import (
COMPARISON_MODELS,
DB_PATH,
N_ANNOTATORS_PER_VIDEO,
)
def _active_video_sql() -> str:
likes = " OR ".join(f"v.dataset LIKE '{m}%'" for m in COMPARISON_MODELS)
return f"({likes})"
def _query_coverage(conn: sqlite3.Connection, exclude_bad: bool) -> list[tuple[int, int]]:
vf = _active_video_sql()
ea = ""
if exclude_bad:
has_table = conn.execute(
"SELECT 1 FROM sqlite_master WHERE type='table' AND name='excluded_annotators'"
).fetchone()
if has_table:
ea = "AND a.annotator_id NOT IN (SELECT annotator_id FROM excluded_annotators)"
return conn.execute(f"""
SELECT v.id, COUNT(a.id) AS cnt
FROM videos v
LEFT JOIN assignments a ON v.id = a.video_id AND a.status IN ('completed', 'partial')
AND a.annotator_id NOT IN (
SELECT id FROM annotators WHERE COALESCE(cohort, 'others') IN ('test')
)
{ea}
WHERE {vf}
GROUP BY v.id
""").fetchall()
def _print_report(label: str, rows: list[tuple[int, int]], target: int, batch_size: int) -> None:
total = len(rows)
dist: Counter[int] = Counter()
deficit = 0
for _, cnt in rows:
bucket = min(cnt, target)
dist[bucket] += 1
if cnt < target:
deficit += target - cnt
print(f"=== {label} ({total} active videos) ===")
for k in sorted(dist.keys()):
print(f" {k}x: {dist[k]} videos ({dist[k] / total * 100:.1f}%)")
print(f" 缺少 annotations: {deficit}")
print(f" 需要补人 (batch={batch_size}): {-(-deficit // batch_size)}")
print()
def main(argv: list[str] | None = None) -> int:
parser = argparse.ArgumentParser(description="Video coverage report")
parser.add_argument("--db", default=str(DB_PATH), help="Path to human_eval.db")
parser.add_argument("--batch-size", type=int, default=12, help="Videos per person (default: 4 groups × 3 models)")
parser.add_argument("--target", type=int, default=N_ANNOTATORS_PER_VIDEO, help="Target annotations per video")
args = parser.parse_args(argv)
conn = sqlite3.connect(args.db, timeout=30)
rows_all = _query_coverage(conn, exclude_bad=False)
rows_filt = _query_coverage(conn, exclude_bad=True)
conn.close()
_print_report("不 filter", rows_all, args.target, args.batch_size)
_print_report("Filter 后", rows_filt, args.target, args.batch_size)
return 0
if __name__ == "__main__":
sys.exit(main())
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