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Running on Zero
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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 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 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 | from __future__ import annotations
import argparse
import csv
import os
import shutil
from pathlib import Path
from datasets import load_dataset, Audio
from tqdm import tqdm
def export_audio_file(audio_info, out_path):
out_path = Path(out_path)
out_path.parent.mkdir(parents=True, exist_ok=True)
audio_bytes = audio_info.get("bytes", None)
audio_path = audio_info.get("path", None)
if audio_bytes is not None:
with open(out_path, "wb") as f:
f.write(audio_bytes)
return True
if audio_path is not None and os.path.exists(audio_path):
shutil.copy2(audio_path, out_path)
return True
return False
def get_value(item, keys, default="unknown"):
for key in keys:
if key in item and item[key] is not None:
return item[key]
return default
def save_split(iterator, split_name, max_items, out_audio_dir):
rows = []
out_audio_dir = Path(out_audio_dir)
out_audio_dir.mkdir(parents=True, exist_ok=True)
print(f"Saving {split_name}: {max_items} samples")
count = 0
skipped = 0
for item in tqdm(iterator, desc=f"Saving {split_name}"):
if count >= max_items:
break
if "audio" not in item:
skipped += 1
continue
audio_info = item["audio"]
file_name = f"GLOBE_{split_name}_{count:06d}.wav"
out_path = out_audio_dir / file_name
ok = export_audio_file(audio_info, out_path)
if not ok:
skipped += 1
continue
text = get_value(item, ["text", "sentence", "transcript", "transcription"], "")
speaker = get_value(item, ["speaker", "speaker_id", "client_id"], "unknown")
accent = get_value(item, ["accent", "country", "region", "dialect"], "unknown")
gender = get_value(item, ["gender", "sex"], "unknown")
rows.append({
"file_path": out_path.resolve().as_posix(),
"binary_label": 0,
"attack_type": "bonafide",
"start_fake": -1,
"end_fake": -1,
"dataset": "GLOBE",
"split": split_name,
"speaker": speaker,
"accent": accent,
"gender": gender,
"text": text,
})
count += 1
print(f"{split_name} saved rows: {len(rows)}")
print(f"{split_name} skipped rows: {skipped}")
return rows
def write_csv(rows, out_csv):
out_csv = Path(out_csv)
out_csv.parent.mkdir(parents=True, exist_ok=True)
fieldnames = [
"file_path",
"binary_label",
"attack_type",
"start_fake",
"end_fake",
"dataset",
"split",
"speaker",
"accent",
"gender",
"text",
]
with open(out_csv, "w", newline="", encoding="utf-8") as f:
writer = csv.DictWriter(f, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(rows)
print("Saved:", out_csv)
print("Rows:", len(rows))
def main():
p = argparse.ArgumentParser()
p.add_argument("--max-train", type=int, default=1000)
p.add_argument("--max-val", type=int, default=200)
p.add_argument("--max-test", type=int, default=200)
p.add_argument("--out-audio-root", default="data\\globe_audio")
p.add_argument("--out-dir", default="data\\metadata")
args = p.parse_args()
print("Loading GLOBE with streaming=True...")
ds = load_dataset("MushanW/GLOBE", split="train", streaming=True)
print("Disabling audio decoding to avoid TorchCodec...")
ds = ds.cast_column("audio", Audio(decode=False))
total_needed = args.max_train + args.max_val + args.max_test
all_items = iter(ds.take(total_needed))
train_rows = save_split(
all_items,
"train",
args.max_train,
Path(args.out_audio_root) / "train",
)
val_rows = save_split(
all_items,
"val",
args.max_val,
Path(args.out_audio_root) / "val",
)
test_rows = save_split(
all_items,
"test",
args.max_test,
Path(args.out_audio_root) / "test",
)
out_dir = Path(args.out_dir)
write_csv(train_rows, out_dir / "globe_train.csv")
write_csv(val_rows, out_dir / "globe_val.csv")
write_csv(test_rows, out_dir / "globe_test.csv")
print("Done.")
if __name__ == "__main__":
main() |