forked from mrq/DL-Art-School
76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
from scipy.io import wavfile
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from spleeter.separator import Separator
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from tqdm import tqdm
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from data.util import find_audio_files
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import os.path as osp
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from spleeter.audio.adapter import AudioAdapter
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import numpy as np
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if __name__ == '__main__':
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src_dir = 'P:\\Audiobooks-Podcasts'
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#src_dir = 'E:\\audio\\books'
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output_dir = 'D:\\data\\audio\\misc-split'
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output_dir_lq = 'D:\\data\\audio\\misc-split-with-bg'
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output_dir_garbage = 'D:\\data\\audio\\misc-split-garbage'
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#output_dir = 'E:\\audio\\books-clips'
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clip_length = 5 # In seconds
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sparsity = .1 # Only this proportion of the total clips are extracted as wavs.
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output_sample_rate=22050
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audio_loader = AudioAdapter.default()
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separator = Separator('spleeter:2stems')
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files = find_audio_files(src_dir, include_nonwav=True)
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for e, file in enumerate(tqdm(files)):
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if e < 1092:
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continue
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file_basis = osp.relpath(file, src_dir)\
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.replace('/', '_')\
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.replace('\\', '_')\
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.replace('.', '_')\
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.replace(' ', '_')\
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.replace('!', '_')\
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.replace(',', '_')
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if len(file_basis) > 100:
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file_basis = file_basis[:100]
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try:
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wave, sample_rate = audio_loader.load(file, sample_rate=output_sample_rate)
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except:
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print(f"Error with {file}")
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continue
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#if len(wave.shape) < 2:
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# continue
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# Calculate how much data we need to extract for each clip.
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clip_sz = sample_rate * clip_length
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interval = int(sample_rate * (clip_length / sparsity))
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i = 0
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while (i+clip_sz) < wave.shape[0]:
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clip = wave[i:i+clip_sz]
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sep = separator.separate(clip)
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vocals = sep['vocals']
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bg = sep['accompaniment']
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vmax = np.abs(vocals).mean()
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bmax = np.abs(bg).mean()
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# Only output to the "good" sample dir if the ratio of background noise to vocal noise is high enough.
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ratio = vmax / (bmax+.0000001)
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if ratio >= 25: # These values were derived empirically
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od = output_dir
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os = clip
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elif ratio >= 1:
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od = output_dir_lq
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os = vocals
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else:
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od = output_dir_garbage
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os = vocals
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# Strip out channels.
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if len(os.shape) > 1:
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os = os[:, 0] # Just use the first channel.
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wavfile.write(osp.join(od, f'{e}_{file_basis}_{i}.wav'), output_sample_rate, os)
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i = i + interval
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