import argparse import concurrent.futures import os from concurrent.futures import ProcessPoolExecutor from multiprocessing import cpu_count import librosa import numpy as np from scipy.io import wavfile from tqdm import tqdm 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 tqdm(concurrent.futures.as_completed(futures), total=len(futures)): 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()