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Running on Zero
Running on Zero
File size: 1,920 Bytes
127b976 | 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 | import argparse
from pathlib import Path
import pandas as pd
import random
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--audio-root", required=True)
parser.add_argument("--dataset-name", required=True)
parser.add_argument("--attack-type", required=True, choices=["tts_vc", "codec", "partial"])
parser.add_argument("--out-dir", required=True)
parser.add_argument("--train-ratio", type=float, default=0.8)
parser.add_argument("--val-ratio", type=float, default=0.1)
parser.add_argument("--seed", type=int, default=42)
args = parser.parse_args()
exts = {".wav", ".flac", ".mp3"}
files = sorted([p for p in Path(args.audio_root).rglob("*") if p.suffix.lower() in exts])
if not files:
raise RuntimeError(f"No audio files found in {args.audio_root}")
random.seed(args.seed)
random.shuffle(files)
n = len(files)
n_train = int(n * args.train_ratio)
n_val = int(n * args.val_ratio)
splits = {
"train": files[:n_train],
"val": files[n_train:n_train + n_val],
"test": files[n_train + n_val:]
}
out_dir = Path(args.out_dir)
out_dir.mkdir(parents=True, exist_ok=True)
for split, split_files in splits.items():
rows = []
for f in split_files:
rows.append({
"file_path": f.resolve().as_posix(),
"binary_label": 1,
"attack_type": args.attack_type,
"start_fake": 0.0,
"end_fake": "full",
"dataset": args.dataset_name,
"split": split
})
df = pd.DataFrame(rows)
out_path = out_dir / f"{args.dataset_name.lower()}_{split}.csv"
df.to_csv(out_path, index=False)
print(f"Saved {out_path} rows={len(df)}")
if __name__ == "__main__":
main()
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