De-limiter / utils /read_wave_utils.py
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first commit
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import random
import math
import numpy as np
import librosa
import torchaudio
def load_wav_arbitrary_position_mono(filename, sample_rate, seq_duration):
# mono
# seq_duration[second]
length = torchaudio.info(filename).num_frames
read_length = librosa.time_to_samples(seq_duration, sr=sample_rate)
if length > read_length:
random_start = random.randint(0, int(length - read_length - 1)) / sample_rate
X, sr = librosa.load(
filename, sr=None, offset=random_start, duration=seq_duration
)
else:
random_start = 0
total_pad_length = read_length - length
X, sr = librosa.load(filename, sr=None, offset=0, duration=seq_duration)
pad_left = random.randint(0, total_pad_length)
X = np.pad(X, (pad_left, total_pad_length - pad_left))
return X
def load_wav_specific_position_mono(
filename, sample_rate, seq_duration, start_position
):
# mono
# seq_duration[second]
# start_position[second]
length = torchaudio.info(filename).num_frames
read_length = librosa.time_to_samples(seq_duration, sr=sample_rate)
start_pos_sec = max(
start_position, 0
) # if start_position is minus, then start from 0.
start_pos_sample = librosa.time_to_samples(start_pos_sec, sr=sample_rate)
if (
length <= start_pos_sample
): # if start position exceeds audio length, then start from 0.
start_pos_sec = 0
start_pos_sample = 0
X, sr = librosa.load(filename, sr=None, offset=start_pos_sec, duration=seq_duration)
if length < start_pos_sample + read_length:
X = np.pad(X, (0, (start_pos_sample + read_length) - length))
return X
# load wav file from arbitrary positions of 16bit stereo wav file
def load_wav_arbitrary_position_stereo(
filename, sample_rate, seq_duration, return_pos=False
):
# stereo
# seq_duration[second]
length = torchaudio.info(filename).num_frames
read_length = librosa.time_to_samples(seq_duration, sr=sample_rate)
random_start_sample = random.randint(
0, int(length - math.ceil(seq_duration * sample_rate) - 1)
)
random_start_sec = librosa.samples_to_time(random_start_sample, sr=sample_rate)
X, sr = librosa.load(
filename, sr=None, mono=False, offset=random_start_sec, duration=seq_duration
)
if length < random_start_sample + read_length:
X = np.pad(X, ((0, 0), (0, (random_start_sample + read_length) - length)))
if return_pos:
return X, random_start_sec
else:
return X
def load_wav_specific_position_stereo(
filename, sample_rate, seq_duration, start_position
):
# stereo
# seq_duration[second]
# start_position[second]
length = torchaudio.info(filename).num_frames
read_length = librosa.time_to_samples(seq_duration, sr=sample_rate)
start_pos_sec = max(
start_position, 0
) # if start_position is minus, then start from 0.
start_pos_sample = librosa.time_to_samples(start_pos_sec, sr=sample_rate)
if (
length <= start_pos_sample
): # if start position exceeds audio length, then start from 0.
start_pos_sec = 0
start_pos_sample = 0
X, sr = librosa.load(
filename, sr=None, mono=False, offset=start_pos_sec, duration=seq_duration
)
if length < start_pos_sample + read_length:
X = np.pad(X, ((0, 0), (0, (start_pos_sample + read_length) - length)))
return X