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Fixing the stft/istft computations

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akhlif
2020-02-27 11:05:06 +01:00
parent 31f823aaa4
commit 6001ae12a9
1 changed files with 14 additions and 5 deletions
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19
spleeter/separator.py
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@@ -98,14 +98,23 @@ class Separator(object):
prediction.pop('audio_id') prediction.pop('audio_id')
return prediction return prediction
def stft(self, waveform, inverse=False): def stft(self, data, inverse=False):
"""
Single entrypoint for both stft and istft. This computes stft and istft with librosa on stereo data. The two
channels are processed separately and are concatenated together in the result. The expected input formats are:
(n_samples, 2) for stft and (T, F, 2) for istft.
:param data: np.array with either the waveform or the complex spectrogram depending on the parameter inverse
:param inverse: should a stft or an istft be computed.
:return: Stereo data as numpy array for the transform. The channels are stored in the last dimension
"""
N = self._params["frame_length"] N = self._params["frame_length"]
H = self._params["frame_step"] H = self._params["frame_step"]
win = hann(N, sym=False) win = hann(N, sym=False)
fstft = istft if inverse else stft fstft = istft if inverse else stft
win_len_arg = "win_length" if inverse else "n_fft" win_len_arg = {"win_length": None} if inverse else {"n_fft": N}
s1 = fstft(waveform[:, 0], hop_length=H, window=win, center=False, **{win_len_arg: N}) dl, dr = (data[:, :, 0].T, data[:, :, 1].T) if inverse else (data[:, 0], data[:, 1])
s2 = fstft(waveform[:, 1], hop_length=H, window=win, center=False, **{win_len_arg: N}) s1 = fstft(dl, hop_length=H, window=win, center=False, **win_len_arg)
s2 = fstft(dr, hop_length=H, window=win, center=False, **win_len_arg)
s1 = np.expand_dims(s1.T, 2-inverse) s1 = np.expand_dims(s1.T, 2-inverse)
s2 = np.expand_dims(s2.T, 2-inverse) s2 = np.expand_dims(s2.T, 2-inverse)
return np.concatenate([s1, s2], axis=2-inverse) return np.concatenate([s1, s2], axis=2-inverse)
@@ -127,7 +136,7 @@ class Separator(object):
saver.restore(sess, latest_checkpoint) saver.restore(sess, latest_checkpoint)
outputs = sess.run(outputs, feed_dict=input_provider.get_feed_dict(features, stft, audio_id)) outputs = sess.run(outputs, feed_dict=input_provider.get_feed_dict(features, stft, audio_id))
for inst in builder.instruments: for inst in builder.instruments:
out[inst] = self.stft(outputs[inst], inverse=True) out[inst] = self.stft(outputs[inst], inverse=True)[:waveform.shape[0], :]
return out return out
def separate_to_file( def separate_to_file(