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align the padding in librosa to what is now done in tf backend

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This commit is contained in:
mmoussallam
2020-07-24 16:32:32 +02:00
parent e7cd9f8aaa
commit 0016e35192
3 changed files with 27 additions and 73 deletions
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8
spleeter/separator.py
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@@ -123,7 +123,7 @@ class Separator(object):
data = np.asfortranarray(data)
N = self._params["frame_length"]
H = self._params["frame_step"]
F = int(N/2) + 1
win = hann(N, sym=False)
fstft = istft if inverse else stft
win_len_arg = {"win_length": None,
@@ -131,12 +131,10 @@ class Separator(object):
n_channels = data.shape[-1]
out = []
for c in range(n_channels):
d = np.concatenate((np.zeros((F, 1)), data[:, :, c].T, np.zeros(
(F, 1))), axis=1) if inverse else data[:, c]
d = np.concatenate((np.zeros((N, )), data[:, c], np.zeros((N, )))) if not inverse else data[:, :, c].T
s = fstft(d, hop_length=H, window=win, center=False, **win_len_arg)
if inverse:
s = s[H:]
s = s[:length]
s = s[N:N+length]
s = np.expand_dims(s.T, 2-inverse)
out.append(s)
if len(out) == 1:

74
tests/test_eval.py
View File

@@ -29,57 +29,29 @@ BACKENDS = ["tensorflow", "librosa"]
TEST_CONFIGURATIONS = {el:el for el in BACKENDS}
res_4stems = {
"librosa": {
"vocals": {
"SDR": 0.000,
"SAR": -16.212,
"SIR": -4.172,
"ISR": 0.000
},
"drums": {
"SDR": -0.077,
"SAR": -15.739,
"SIR": -5.045,
"ISR": 0.001
},
"bass":{
"SDR": -0.000,
"SAR": -10.665,
"SIR": -5.646,
"ISR": -0.000
},
"other":{
"SDR": -1.309,
"SAR": -14.573,
"SIR": -4.705,
"ISR": -0.014
}
"vocals": {
"SDR": 3.25e-05,
"SAR": -11.153575,
"SIR": -1.3849,
"ISR": 2.75e-05
},
"tensorflow": {
"vocals": {
"SDR": 3.25e-05,
"SAR": -11.153575,
"SIR": -1.3849,
"ISR": 2.75e-05
},
"drums": {
"SDR": -0.079505,
"SAR": -15.7073575,
"SIR": -4.972755,
"ISR": 0.0013575
},
"bass":{
"SDR": 2.5e-06,
"SAR": -10.3520575,
"SIR": -4.272325,
"ISR": 2.5e-06
},
"other":{
"SDR": -1.359175,
"SAR": -14.7076775,
"SIR": -4.761505,
"ISR": -0.01528
}
"drums": {
"SDR": -0.079505,
"SAR": -15.7073575,
"SIR": -4.972755,
"ISR": 0.0013575
},
"bass":{
"SDR": 2.5e-06,
"SAR": -10.3520575,
"SIR": -4.272325,
"ISR": 2.5e-06
},
"other":{
"SDR": -1.359175,
"SAR": -14.7076775,
"SIR": -4.761505,
"ISR": -0.01528
}
}
@@ -109,4 +81,4 @@ def test_evaluate(backend):
metrics = evaluate.entrypoint(arguments, params)
for instrument, metric in metrics.items():
for m, value in metric.items():
assert np.allclose(np.median(value), res_4stems[backend][instrument][m], atol=1e-3)
assert np.allclose(np.median(value), res_4stems[instrument][m], atol=1e-3)

18
tests/test_separator.py
View File

@@ -53,29 +53,13 @@ def test_separator_backends(test_file):
stft_matrix, inverse=True, length=waveform.shape[0])
assert np.allclose(reconstructed, waveform, atol=3e-2)
# # now also test that tensorflow and librosa STFT provide same results
from spleeter.audio.spectrogram import compute_spectrogram_tf
tf_waveform = tf.convert_to_tensor(waveform, tf.float32)
spectrogram_tf = compute_spectrogram_tf(tf_waveform,
separator_tf._params['frame_length'],
separator_tf._params['frame_step'],)
with tf.Session() as sess:
spectrogram_tf_eval = spectrogram_tf.eval()
# check that stfts are equivalent
assert stft_matrix.shape == spectrogram_tf_eval.shape
assert np.allclose(
np.abs(stft_matrix), spectrogram_tf_eval, atol=1e-2)
# compare both separation, it should be close
out_tf = separator_tf._separate_tensorflow(waveform, test_file)
out_lib = separator_lib._separate_librosa(waveform, test_file)
for instrument in out_lib.keys():
# test that both outputs are close everywhere
assert np.allclose(out_tf[instrument], out_lib[instrument], atol=0.025)
# it should be even more similar outside edges zones
assert np.allclose(out_tf[instrument][4096:-4096,:], out_lib[instrument][4096:-4096,:], atol=0.002)
assert np.allclose(out_tf[instrument], out_lib[instrument], atol=1e-5)
@pytest.mark.parametrize('test_file, configuration, backend', TEST_CONFIGURATIONS)