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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() | |