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# Copyright 2024 The YourMT3 Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Please see the details in the LICENSE file.
import numpy as np
import torch
import json
import soundfile as sf
from utils.datasets_train import get_cache_data_loader
def get_filelist(track_id: int) -> dict:
filelist = '../../data/yourmt3_indexes/slakh_train_file_list.json'
with open(filelist, 'r') as f:
fl = json.load(f)
new_filelist = dict()
for key, value in fl.items():
if int(key) == track_id:
new_filelist[0] = value
return new_filelist
def get_ds(track_id: int, random_amp_range: list = [1., 1.], stem_aug_prob: float = 0.8):
filelist = get_filelist(track_id)
dl = get_cache_data_loader(filelist,
'train',
1,
1,
random_amp_range=random_amp_range,
stem_aug_prob=stem_aug_prob,
shuffle=False)
ds = dl.dataset
return ds
def gen_audio(track_id: int, n_segments: int = 30, random_amp_range: list = [1., 1.], stem_aug_prob: float = 0.8):
ds = get_ds(track_id, random_amp_range, stem_aug_prob)
audio = []
for i in range(n_segments):
audio.append(ds.__getitem__(0)[0])
# audio.append(ds.__getitem__(i)[0])
audio = torch.concat(audio, dim=2).numpy()[0, 0, :]
sf.write('audio.wav', audio, 16000, subtype='PCM_16')
gen_audio(1, 20)
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