ref: 44f448b2ffa12c7920f35a34d3dd6a44e784fe66
dir: /dnn/torch/osce/data/simple_bwe_dataset.py/
"""
/* Copyright (c) 2024 Amazon
Written by Jan Buethe */
/*
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER
OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
"""
import os
from torch.utils.data import Dataset
import numpy as np
from utils.bwe_features import bwe_feature_factory
class SimpleBWESet(Dataset):
FRAME_SIZE_16K = 160
def __init__(self,
path,
frames_per_sample=100,
spec_num_bands=32,
max_instafreq_bin=40,
upsampling_delay48=13,
):
self.frames_per_sample = frames_per_sample
self.upsampling_delay48 = upsampling_delay48
self.signal_16k = np.fromfile(os.path.join(path, 'signal_16kHz.s16'), dtype=np.int16)
self.signal_48k = np.fromfile(os.path.join(path, 'signal_48kHz.s16'), dtype=np.int16)
num_frames = min(len(self.signal_16k) // self.FRAME_SIZE_16K,
len(self.signal_48k) // (3 * self.FRAME_SIZE_16K))
self.create_features = bwe_feature_factory(spec_num_bands=spec_num_bands, max_instafreq_bin=max_instafreq_bin)
self.frame_offset = 6
self.len = (num_frames - self.frame_offset) // frames_per_sample
def __len__(self):
return self.len
def __getitem__(self, index):
frame_start = self.frames_per_sample * index + self.frame_offset
frame_stop = frame_start + self.frames_per_sample
signal_start16 = frame_start * self.FRAME_SIZE_16K
signal_stop16 = frame_stop * self.FRAME_SIZE_16K
x_16 = self.signal_16k[signal_start16 : signal_stop16].astype(np.float32) / 2**15
history_16 = self.signal_16k[signal_start16 - 320 : signal_start16].astype(np.float32) / 2**15
# dithering
x_16 += (np.random.rand(len(x_16)) - 0.5) / 2**15
history_16 += (np.random.rand(len(history_16)) - 0.5) / 2**15
x_48 = self.signal_48k[3 * signal_start16 - self.upsampling_delay48
: 3 * signal_stop16 - self.upsampling_delay48].astype(np.float32) / 2**15
features = self.create_features(
x_16,
history_16
)
return {
'features' : features,
'x_16' : x_16.astype(np.float32),
'x_48' : x_48.astype(np.float32),
}