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from pathlib import Path | |
import audiotools as at | |
from audiotools import AudioSignal | |
import argbind | |
import tqdm | |
import torch | |
from torch_pitch_shift import pitch_shift, get_fast_shifts | |
from torch_time_stretch import time_stretch, get_fast_stretches | |
from audiotools.core.util import sample_from_dist | |
def augment( | |
audio_folder: Path = None, | |
dest_folder: Path = None, | |
n_augmentations: int = 10, | |
): | |
""" | |
Augment a folder of audio files by applying audiotools and pedalboard transforms. | |
The dest foler will contain a folder for each of the clean dataset's files. | |
Under each of these folders, there will be a clean file and many augmented files. | |
""" | |
assert audio_folder is not None | |
assert dest_folder is not None | |
audio_files = at.util.find_audio(audio_folder) | |
for audio_file in tqdm.tqdm(audio_files): | |
subtree = dest_folder / audio_file.relative_to(audio_folder).parent | |
subdir = subtree / audio_file.stem | |
subdir.mkdir(parents=True, exist_ok=True) | |
src = AudioSignal(audio_file).to("cuda" if torch.cuda.is_available() else "cpu") | |
for i, chunk in tqdm.tqdm(enumerate(src.windows(10, 10))): | |
# apply pedalboard transforms | |
for j in range(n_augmentations): | |
# pitch shift between -7 and 7 semitones | |
import random | |
dst = chunk.clone() | |
dst.samples = pitch_shift( | |
dst.samples, | |
shift=random.choice(get_fast_shifts(src.sample_rate, | |
condition=lambda x: x >= 0.25 and x <= 1.0)), | |
sample_rate=src.sample_rate | |
) | |
dst.samples = time_stretch( | |
dst.samples, | |
stretch=random.choice(get_fast_stretches(src.sample_rate, | |
condition=lambda x: x >= 0.667 and x <= 1.5, )), | |
sample_rate=src.sample_rate, | |
) | |
dst.cpu().write(subdir / f"{i}-{j}.wav") | |
if __name__ == "__main__": | |
args = argbind.parse_args() | |
with argbind.scope(args): | |
augment() | |