def isolateVocals(self, path, fftWindowSize, phaseIterations=10):
console.log("Attempting to isolate vocals from", path)
audio, sampleRate = conversion.loadAudioFile(path)
spectrogram, phase = conversion.audioFileToSpectrogram(audio, fftWindowSize=fftWindowSize)
console.log("Retrieved spectrogram; processing...")
expandedSpectrogram = conversion.expandToGrid(spectrogram, self.peakDownscaleFactor)
expandedSpectrogramWithBatchAndChannels = expandedSpectrogram[np.newaxis, :, :, np.newaxis]
print(expandedSpectrogramWithBatchAndChannels.shape)
# 预测
predictedSpectrogramWithBatchAndChannels = self.model.predict(expandedSpectrogramWithBatchAndChannels)
predictedSpectrogram = predictedSpectrogramWithBatchAndChannels[0, :, :, 0] # o /// o
newSpectrogram = predictedSpectrogram[:spectrogram.shape[0], :spectrogram.shape[1]]
console.log("Processed spectrogram; reconverting to audio")
newAudio = conversion.spectrogramToAudioFile(newSpectrogram, sampleRate, fftWindowSize=fftWindowSize, phaseIterations=phaseIterations)
pathParts = os.path.split(path)
fileNameParts = os.path.splitext(pathParts[1])
outputFileNameBase = os.path.join(pathParts[0], fileNameParts[0] + "_unet")
console.log("Converted to audio; writing to", outputFileNameBase)
conversion.saveAudioFile(newAudio, outputFileNameBase + ".wav", sampleRate)
conversion.saveSpectrogram(newSpectrogram, outputFileNameBase + ".png")
conversion.saveSpectrogram(spectrogram, os.path.join(pathParts[0], fileNameParts[0]) + ".png")
console.log("Vocal isolation complete")
if acapellaSlices.__len__() > 0:
self.x.extend(mashupSlices)
self.y.extend(acapellaSlices)
console.info(count, "Created spectrogram for",
fileName, "with length",
acapellaSlices.__len__())
# Add a "channels" channel to please the network
self.x = np.array(self.x)[:, :, :, np.newaxis]
self.y = np.array(self.y)[:, :, :, np.newaxis]
console.info('Train data shape: x: ', self.x.shape, ' y: ',
self.y.shape)
# Save to file if asked
if saveDataAsH5:
h5f = h5py.File(h5Path, "w")
h5f.create_dataset("x", data=self.x)
h5f.create_dataset("y", data=self.y)
h5f.close()
if __name__ == "__main__":
# Simple testing code to use while developing
console.h1("Loading Data")
d = Data(sys.argv[1], 1536)
console.h1("Writing Sample Data")
conversion.saveSpectrogram(d.x[0], "x_sample_0.png")
conversion.saveSpectrogram(d.y[0], "y_sample_0.png")
audio = conversion.spectrogramToAudioFile(d.x[0], 1536)
conversion.saveAudioFile(audio, "x_sample.wav", 22050)