File size: 3,430 Bytes
f98e127 | 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 | #!/usr/bin/env python3
"""Cut every reviewed Minerva line from the local videos into a training set, split by video.
Usage: python scripts/minerva_dataset.py # -> data/minerva/{clips/,train.csv,dev.csv,test.csv}
python scripts/minerva_dataset.py --test 5 --dev 4 --seed 1
Nothing is uploaded: the clips stay on this machine (data/minerva/ is git-ignored). The split is by video, never by
line, so a speaker or a scene heard in training is never in dev/test. The CSVs have the columns train/finetune.py
reads (`audio,ipa`) plus `item,video,ar` for the benchmark (scripts/minerva_benchmark.py). Clips already cut are
kept, so a rerun only cuts what is missing.
"""
from __future__ import annotations
import argparse
import csv
import random
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from app import lab # noqa: E402
from scripts.import_minerva import source_file, wav_segment # noqa: E402
ROOT = Path(__file__).resolve().parent.parent
def split(videos: list[dict], n_test: int, n_dev: int, seed: int) -> dict[str, str]:
"""{video id: "train" | "dev" | "test"}, reproducible for a seed."""
ids = sorted(v["id"] for v in videos)
random.Random(seed).shuffle(ids)
return {vid: "test" if k < n_test else "dev" if k < n_test + n_dev else "train" for k, vid in enumerate(ids)}
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
ap.add_argument("--videos-dir", type=Path, default=Path("/home/eyalshw/Videos/minerva"))
ap.add_argument("--out", type=Path, default=ROOT / "data" / "minerva")
ap.add_argument("--test", type=int, default=5, help="videos held out for the benchmark")
ap.add_argument("--dev", type=int, default=4, help="videos held out for choosing checkpoints and thresholds")
ap.add_argument("--seed", type=int, default=0)
args = ap.parse_args()
videos = list(lab.minerva_metadata())
parts = split(videos, args.test, args.dev, args.seed)
clips = args.out / "clips"
clips.mkdir(parents=True, exist_ok=True)
rows: dict[str, list[dict]] = {"train": [], "dev": [], "test": []}
cut = 0
for video in videos:
source = source_file(args.videos_dir, video["id"])
for segment in video["segments"]:
path = clips / f"{video['id']}-{segment['line']:02d}.wav"
if not path.exists():
path.write_bytes(wav_segment(source, segment["start"], segment["end"]))
cut += 1
rows[parts[video["id"]]].append({"audio": str(path.relative_to(args.out)), "ipa": segment["ipa"],
"item": segment["item"], "video": video["id"], "ar": segment["ar"]})
print(f"{parts[video['id']]:<5} {video['id']} {len(video['segments']):>3} lines {video['title']}")
for part, items in rows.items():
with open(args.out / f"{part}.csv", "w", encoding="utf-8", newline="") as f:
w = csv.DictWriter(f, fieldnames=["audio", "ipa", "item", "video", "ar"])
w.writeheader()
w.writerows(items)
seconds = sum(s["end"] - s["start"] for v in videos for s in v["segments"])
print(f"cut {cut} new clips; " + ", ".join(f"{p} {len(r)}" for p, r in rows.items())
+ f" lines; {seconds / 60:.0f} min in all -> {args.out}")
return 0
if __name__ == "__main__":
sys.exit(main())
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