def test_n_output_spectrogram(self):
mel_spectrogram = AudioLoader.load_mel_spectrogram(
self.sample_wav_file, n_mels=128)
#
flows = [
naf.Sequential([nas.FrequencyMaskingAug(),
nas.TimeMaskingAug()]),
naf.Sometimes([nas.FrequencyMaskingAug(),
nas.TimeMaskingAug()],
pipeline_p=0.9),
naf.Sequential([
naf.Sequential(
[nas.FrequencyMaskingAug(),
nas.TimeMaskingAug()]),
naf.Sometimes(
[nas.FrequencyMaskingAug(),
nas.TimeMaskingAug()],
pipeline_p=0.9)
])
]
for flow in flows:
augmented_mel_spectrograms = flow.augment(mel_spectrogram, n=3)
self.assertGreater(len(augmented_mel_spectrograms), 1)
for augmented_mel_spectrogram in augmented_mel_spectrograms:
self.assertFalse(
np.array_equal(mel_spectrogram, augmented_mel_spectrogram))
self.assertLess(0, len(flows))
def test_spectrogram(self):
# https://freewavesamples.com/yamaha-v50-rock-beat-120-bpm
sample_wav_file = os.path.abspath(os.path.join(
os.path.dirname(__file__), '..', '..', 'data', 'Yamaha-V50-Rock-Beat-120bpm.wav'))
mel_spectrogram = LoadUtil.load_mel_spectrogram(sample_wav_file, n_mels=128)
flow = naf.Sequential([
nas.FrequencyMaskingAug(mask_factor=50),
nas.TimeMaskingAug(mask_factor=20),
nas.TimeMaskingAug(mask_factor=30)])
augmented_mel_spectrogram = flow.augment(mel_spectrogram)
for aug in flow:
if aug.name == 'FrequencyMasking_Aug':
self.assertEqual(len(mel_spectrogram[aug.model.f0]), np.count_nonzero(mel_spectrogram[aug.model.f0]))
self.assertEqual(0, np.count_nonzero(augmented_mel_spectrogram[aug.model.f0]))
elif aug.name == 'TimeMasking_Aug':
self.assertEqual(len(mel_spectrogram[:, aug.model.t0]),
np.count_nonzero(mel_spectrogram[:, aug.model.t0]))
self.assertEqual(0, np.count_nonzero(augmented_mel_spectrogram[:, aug.model.t0]))
else:
# Unexpected flow
self.assertFalse(True)
self.assertTrue(len(flow) > 0)
def test_spectrogram(self):
mel_spectrogram = AudioLoader.load_mel_spectrogram(
self.sample_wav_file, n_mels=128)
flow = naf.Sequential([
nas.FrequencyMaskingAug(stateless=False),
nas.TimeMaskingAug(stateless=False),
nas.TimeMaskingAug(stateless=False)
])
augmented_mel_spectrogram = flow.augment(mel_spectrogram)
for aug in flow:
if aug.name == 'FrequencyMasking_Aug':
aug_data = augmented_mel_spectrogram[
aug.f0:aug.f0 + aug.f, aug.time_start:aug.time_end]
orig_data = mel_spectrogram[aug.f0:aug.f0 + aug.f,
aug.time_start:aug.time_end]
self.assertEqual(orig_data.size, np.count_nonzero(orig_data))
self.assertEqual(0, np.count_nonzero(aug_data))
elif aug.name == 'TimeMasking_Aug':
self.assertEqual(len(mel_spectrogram[:, aug.t0]),
np.count_nonzero(mel_spectrogram[:, aug.t0]))
self.assertEqual(
0, np.count_nonzero(augmented_mel_spectrogram[:, aug.t0]))
else:
raise ValueError('Unexpected flow for {} augmenter'.format(
aug.name))
self.assertTrue(len(flow) > 0)
def test_no_change_source(self):
data = AudioLoader.load_mel_spectrogram(self.sample_wav_file,
n_mels=128)
aug = nas.FrequencyMaskingAug()
aug_data = aug.augment(data)
comparison = data == aug_data
self.assertFalse(comparison.all())
def __init__(self, paths, labels, augment=False):
self.paths = paths
self.labels = labels
self.flow = naf.Sequential(
[nas.FrequencyMaskingAug(),
nas.TimeMaskingAug()])
if augment:
self.augment = True
def test_multi_thread(self):
mel_spectrogram = LoadUtil.load_mel_spectrogram(self.sample_wav_file, n_mels=128)
n = 3
augs = [
nas.FrequencyMaskingAug(mask_factor=80),
nas.TimeMaskingAug(mask_factor=80)
]
for num_thread in [1, 3]:
for aug in augs:
augmented_data = aug.augment(mel_spectrogram, n=n, num_thread=num_thread)
self.assertEqual(len(augmented_data), n)
def test_substitute(self):
data = AudioLoader.load_mel_spectrogram(self.sample_wav_file,
n_mels=128)
aug = nas.FrequencyMaskingAug(stateless=False)
aug_data = aug.augment(data)
self.assertEqual(len(data[aug.f0]), np.count_nonzero(data[aug.f0]))
self.assertEqual(
0, np.count_nonzero(aug_data[aug.f0][aug.time_start:aug.time_end]))
self.assertEqual(
0, len(np.where(aug_data[aug.f0][:aug.time_start] == 0)[0]))
self.assertEqual(
0, len(np.where(aug_data[aug.f0][aug.time_end:] == 0)[0]))
def get_random_freq_mask(self):
return nas.FrequencyMaskingAug(mask_factor=40)
def test_empty_input(self):
data = np.array([])
aug = nas.FrequencyMaskingAug()
aug_data = aug.augment(data)
self.assertTrue(np.array_equal(np.array([]), aug_data))
