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d8a0e2f | 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 | """Print the motion-score percentile ladder of the candidate pool.
The pool is everything select_clips.py would keep *except* the motion cut, so the
number printed here is exactly the value to pass as --motion-lo.
"""
import argparse, csv, json, os, re, bisect
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
META = os.path.join(ROOT, "meta")
csv.field_size_limit(10**9)
TALKING = re.compile(r"\b(talk|talks|talking|interview|interviews|interviewed|"
r"podcast|podcasts)\b", re.I)
ap = argparse.ArgumentParser()
ap.add_argument("--n-frames", type=int, default=10)
ap.add_argument("--step", type=float, default=0.5)
ap.add_argument("--margin", type=float, default=0.25)
ap.add_argument("--motion-hi", type=float, default=60.0)
ap.add_argument("--min-aesthetic", type=float, default=5.0)
ap.add_argument("--keep-talking", action="store_true")
ap.add_argument("--at", type=float, default=None, help="report the percentile of this score")
A = ap.parse_args()
MIN_SEC = (A.n_frames - 1) * A.step + A.margin
idx = {json.loads(l)["clip"] for l in open(os.path.join(META, "part_index.jsonl"))}
mot = []
with open(os.path.join(META, "OpenVid-1M.csv"), newline="") as f:
for r in csv.DictReader(f):
v = r["video"]
if v.startswith(("celebv_", "pixabay_")) or v not in idx:
continue
try:
m, sec, aes = float(r["motion score"]), float(r["seconds"]), float(r["aesthetic score"])
except ValueError:
continue
if sec < MIN_SEC or m > A.motion_hi or aes < A.min_aesthetic:
continue
if not A.keep_talking and TALKING.search(r["caption"]):
continue
mot.append(m)
mot.sort()
n = len(mot)
print(f"candidate pool (no motion cut): {n:,} clips")
for top in (10, 20, 30, 40, 50, 70, 100):
print(f" top {top:>3}% -> motion >= {mot[int(n * (1 - top/100))]:.4f}")
if A.at is not None:
print(f" motion {A.at} sits at top {100 - bisect.bisect_left(mot, A.at)*100/n:.1f}%")
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