File size: 4,045 Bytes
7e6c03a | 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 | from pathlib import Path
from concurrent.futures import ProcessPoolExecutor, as_completed
import os
import pandas as pd
import soundfile as sf
from tqdm import tqdm
# ============================================================
# Paths
# ============================================================
AUDIO_ROOT = Path("/home/debarpanb1/TREA_2.0/GISE/isolated_events")
CSV_PATH = Path("/home/debarpanb1/TREA_2.0/GISE/meta/gise_metadata.csv")
OUTPUT_PATH = Path("/home/debarpanb1/TREA_2.0/GISE/meta/gise_audio_format_check.csv")
NUM_WORKERS = min(16, os.cpu_count() or 4)
# ============================================================
# Worker
# ============================================================
def check_one(row_dict):
relative_path = Path(row_dict["relative_path"])
audio_path = AUDIO_ROOT / relative_path
row_dict["audio_path"] = str(audio_path)
row_dict["exists"] = audio_path.exists()
row_dict["read_success"] = False
row_dict["read_error"] = ""
if not audio_path.exists():
row_dict["read_error"] = "missing_audio_file"
return row_dict
try:
info = sf.info(str(audio_path))
row_dict["sample_rate"] = info.samplerate
row_dict["channels"] = info.channels
row_dict["frames"] = info.frames
row_dict["duration"] = info.frames / info.samplerate
row_dict["format"] = info.format
row_dict["subtype"] = info.subtype
row_dict["endian"] = info.endian
row_dict["sections"] = info.sections
row_dict["read_success"] = True
except Exception as e:
row_dict["read_error"] = repr(e)
return row_dict
# ============================================================
# Main
# ============================================================
def main():
df = pd.read_csv(CSV_PATH)
records = df.to_dict("records")
print(f"Checking {len(records)} GISE files with {NUM_WORKERS} workers...")
results = []
with ProcessPoolExecutor(max_workers=NUM_WORKERS) as executor:
futures = [executor.submit(check_one, row) for row in records]
for future in tqdm(as_completed(futures), total=len(futures)):
results.append(future.result())
out_df = pd.DataFrame(results)
out_df.to_csv(OUTPUT_PATH, index=False)
print("\nDone.")
print(f"Saved detailed check to: {OUTPUT_PATH}")
print("\nExists:")
print(out_df["exists"].value_counts(dropna=False))
print("\nRead success:")
print(out_df["read_success"].value_counts(dropna=False))
print("\nSample rates:")
print(out_df["sample_rate"].value_counts(dropna=False).sort_index())
print("\nChannels:")
print(out_df["channels"].value_counts(dropna=False).sort_index())
print("\nFormats:")
print(out_df["format"].value_counts(dropna=False))
print("\nSubtypes:")
print(out_df["subtype"].value_counts(dropna=False))
print("\nDuration summary:")
print(out_df["duration"].describe())
print("\nDuration filter counts:")
print("duration < 0.5s:", (out_df["duration"] < 0.5).sum())
print("0.5s <= duration <= 10s:", ((out_df["duration"] >= 0.5) & (out_df["duration"] <= 10.0)).sum())
print("duration > 10s:", (out_df["duration"] > 10.0).sum())
print("\nNon-22050 files:")
non_22050 = out_df[out_df["sample_rate"] != 22050]
print(len(non_22050))
if len(non_22050) > 0:
print(non_22050[["relative_path", "sample_rate", "channels", "format", "subtype", "duration"]].head(20))
print("\nNon-PCM_16 files:")
non_pcm16 = out_df[out_df["subtype"] != "PCM_16"]
print(len(non_pcm16))
if len(non_pcm16) > 0:
print(non_pcm16[["relative_path", "sample_rate", "channels", "format", "subtype", "duration"]].head(20))
print("\nNon-mono files:")
non_mono = out_df[out_df["channels"] != 1]
print(len(non_mono))
if len(non_mono) > 0:
print(non_mono[["relative_path", "sample_rate", "channels", "format", "subtype", "duration"]].head(20))
if __name__ == "__main__":
main() |