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import os |
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import argparse |
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import librosa |
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import numpy as np |
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from multiprocessing import Pool, cpu_count |
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from scipy.io import wavfile |
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from tqdm import tqdm |
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def process(item): |
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spkdir, wav_name, args = item |
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speaker = spkdir.replace("\\", "/").split("/")[-1] |
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wav_path = os.path.join(args.in_dir, speaker, wav_name) |
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if os.path.exists(wav_path) and '.wav' in wav_path: |
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os.makedirs(os.path.join(args.out_dir2, speaker), exist_ok=True) |
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wav, sr = librosa.load(wav_path, sr=None) |
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wav, _ = librosa.effects.trim(wav, top_db=20) |
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peak = np.abs(wav).max() |
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if peak > 1.0: |
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wav = 0.98 * wav / peak |
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wav2 = librosa.resample(wav, orig_sr=sr, target_sr=args.sr2) |
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wav2 /= max(wav2.max(), -wav2.min()) |
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save_name = wav_name |
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save_path2 = os.path.join(args.out_dir2, speaker, save_name) |
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wavfile.write( |
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save_path2, |
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args.sr2, |
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(wav2 * np.iinfo(np.int16).max).astype(np.int16) |
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) |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser() |
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parser.add_argument("--sr2", type=int, default=44100, help="sampling rate") |
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parser.add_argument("--in_dir", type=str, default="./dataset_raw", help="path to source dir") |
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parser.add_argument("--out_dir2", type=str, default="./dataset/44k", help="path to target dir") |
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args = parser.parse_args() |
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processs = 30 if cpu_count() > 60 else (cpu_count()-2 if cpu_count() > 4 else 1) |
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pool = Pool(processes=processs) |
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for speaker in os.listdir(args.in_dir): |
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spk_dir = os.path.join(args.in_dir, speaker) |
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if os.path.isdir(spk_dir): |
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print(spk_dir) |
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for _ in tqdm(pool.imap_unordered(process, [(spk_dir, i, args) for i in os.listdir(spk_dir) if i.endswith("wav")])): |
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pass |
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