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import argparse
import concurrent.futures
import os
from concurrent.futures import ProcessPoolExecutor
from multiprocessing import cpu_count
import librosa
import numpy as np
from rich.progress import track
from scipy.io import wavfile
def load_wav(wav_path):
return librosa.load(wav_path, sr=None)
def trim_wav(wav, top_db=40):
return librosa.effects.trim(wav, top_db=top_db)
def normalize_peak(wav, threshold=1.0):
peak = np.abs(wav).max()
if peak > threshold:
wav = 0.98 * wav / peak
return wav
def resample_wav(wav, sr, target_sr):
return librosa.resample(wav, orig_sr=sr, target_sr=target_sr)
def save_wav_to_path(wav, save_path, sr):
wavfile.write(
save_path,
sr,
(wav * np.iinfo(np.int16).max).astype(np.int16)
)
def process(item):
spkdir, wav_name, args = item
speaker = spkdir.replace("\\", "/").split("/")[-1]
wav_path = os.path.join(args.in_dir, speaker, wav_name)
if os.path.exists(wav_path) and '.wav' in wav_path:
os.makedirs(os.path.join(args.out_dir2, speaker), exist_ok=True)
wav, sr = load_wav(wav_path)
wav, _ = trim_wav(wav)
wav = normalize_peak(wav)
resampled_wav = resample_wav(wav, sr, args.sr2)
if not args.skip_loudnorm:
resampled_wav /= np.max(np.abs(resampled_wav))
save_path2 = os.path.join(args.out_dir2, speaker, wav_name)
save_wav_to_path(resampled_wav, save_path2, args.sr2)
"""
def process_all_speakers():
process_count = 30 if os.cpu_count() > 60 else (os.cpu_count() - 2 if os.cpu_count() > 4 else 1)
with ThreadPoolExecutor(max_workers=process_count) as executor:
for speaker in speakers:
spk_dir = os.path.join(args.in_dir, speaker)
if os.path.isdir(spk_dir):
print(spk_dir)
futures = [executor.submit(process, (spk_dir, i, args)) for i in os.listdir(spk_dir) if i.endswith("wav")]
for _ in tqdm(concurrent.futures.as_completed(futures), total=len(futures)):
pass
"""
# multi process
def process_all_speakers():
process_count = 30 if os.cpu_count() > 60 else (os.cpu_count() - 2 if os.cpu_count() > 4 else 1)
with ProcessPoolExecutor(max_workers=process_count) as executor:
for speaker in speakers:
spk_dir = os.path.join(args.in_dir, speaker)
if os.path.isdir(spk_dir):
print(spk_dir)
futures = [executor.submit(process, (spk_dir, i, args)) for i in os.listdir(spk_dir) if i.endswith("wav")]
for _ in track(concurrent.futures.as_completed(futures), total=len(futures), description="resampling:"):
pass
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--sr2", type=int, default=44100, help="sampling rate")
parser.add_argument("--in_dir", type=str, default="./dataset_raw", help="path to source dir")
parser.add_argument("--out_dir2", type=str, default="./dataset/44k", help="path to target dir")
parser.add_argument("--skip_loudnorm", action="store_true", help="Skip loudness matching if you have done it")
args = parser.parse_args()
print(f"CPU count: {cpu_count()}")
speakers = os.listdir(args.in_dir)
process_all_speakers()
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