MachineHearing / process /process_raw2wav.py
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# -*- coding: utf-8 -*-
import json
import wave
from pathlib import Path
import numpy as np
import pandas as pd
ROOT = Path(__file__).resolve().parent.parent
CONVERT_TASKS = {"GWOSC", "LEAVES", "Iquique", "Llaima", "RadSeg", "RadioML"}
def main():
total = converted = 0
with (ROOT / "meta_data.jsonl").open("r", encoding="utf-8") as fin, \
(ROOT / "wav_data.jsonl").open("w", encoding="utf-8") as fout:
for line in fin:
if not line.strip():
continue
data = json.loads(line)
if data["task_name"] in CONVERT_TASKS:
data_type = data["data_type"]
assert data_type in ("csv", "npy")
src_rel = Path(data["input_ts"]["path"])
src_path = ROOT / src_rel
assert src_rel.parent.name == "raw_input" and src_path.is_file()
if data_type == "csv":
signal = pd.read_csv(src_path, header=None).values
else:
signal = np.load(src_path)
signal = signal.flatten().astype(np.float64)
assert signal.size > 0
abs_max = np.max(np.abs(signal))
if abs_max > 0:
signal = signal / abs_max
signal = (signal * 32767).astype(np.int16)
wav_rel = src_rel.parent.parent / "wav_input" / (src_rel.stem + ".wav")
wav_path = ROOT / wav_rel
wav_path.parent.mkdir(parents=True, exist_ok=True)
with wave.open(str(wav_path), "wb") as wf:
wf.setnchannels(1)
wf.setsampwidth(2)
wf.setframerate(16000)
wf.writeframes(signal.tobytes())
data["data_type"] = "wav"
data["input_ts"]["path"] = wav_rel.as_posix()
data["input_ts"]["length"] = int(signal.size)
data["input_ts"]["num_channel"] = 1
data["input_ts"]["fs"] = 16000
if data["task_name"] in ("Iquique", "RadSeg", "RadioML"):
data["input_ts"]["channel_detail"] = []
converted += 1
fout.write(json.dumps(data, ensure_ascii=False) + "\n")
total += 1
assert total == 6128 and converted == 3428
print(f"Done: {converted} WAV files, {total} JSONL records")
if __name__ == "__main__":
main()