Carol-Bert-VITS2 / resample.py
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import os
import argparse
import librosa
import numpy as np
from multiprocessing import Pool, cpu_count
import soundfile
from scipy.io import wavfile
from tqdm import tqdm
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_dir, speaker), exist_ok=True)
wav, sr = librosa.load(wav_path, sr=args.sr)
soundfile.write(
os.path.join(args.out_dir, speaker, wav_name),
wav,
sr
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--sr", type=int, default=44100, help="sampling rate")
parser.add_argument("--in_dir", type=str, default="./raw", help="path to source dir")
parser.add_argument("--out_dir", type=str, default="./dataset", help="path to target dir")
args = parser.parse_args()
# processs = 8
processs = cpu_count()-2 if cpu_count() >4 else 1
pool = Pool(processes=processs)
for speaker in os.listdir(args.in_dir):
spk_dir = os.path.join(args.in_dir, speaker)
if os.path.isdir(spk_dir):
print(spk_dir)
for _ in tqdm(pool.imap_unordered(process, [(spk_dir, i, args) for i in os.listdir(spk_dir) if i.endswith("wav")])):
pass