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@@ -3,31 +3,26 @@ import numpy as np |
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import matplotlib.image as mpimg |
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import matplotlib.image as mpimg |
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import wave |
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import wave |
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from array import array |
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from array import array |
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from progressbar import ProgressBar |
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def write_column(output_file, pixels, rescale=.1): |
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""" Write a single column of sound """ |
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curve = np.fft.ifft(pixels, len(pixels)*2).real |
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curve = np.array((curve-np.average(curve))*rescale, dtype=int) |
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data = array("h", curve).tostring() |
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output_file.writeframes(data) |
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def make_wav(image_filename): |
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def make_wav(image_filename): |
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""" Make a WAV file having a spectrogram resembling an image """ |
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""" Make a WAV file having a spectrogram resembling an image """ |
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# Load image |
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image = mpimg.imread(image_filename) |
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image = mpimg.imread(image_filename) |
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image = np.sum(image, axis = 2).T[:, ::-1] |
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image = np.sum(image, axis = 2).T[:, ::-1] |
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image = image**2 |
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image = image**3 # ??? |
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w, h = image.shape |
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# Fourier transform, normalize, remove DC bias |
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data = np.fft.irfft(image, h*2, axis=1).reshape((w*h*2)) |
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data -= np.average(data) |
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data *= (2**15.-1)/np.amax(data) |
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data = array("h", np.int_(data)).tostring() |
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# Write to disk |
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output_file = wave.open(image_filename+".wav", "w") |
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output_file = wave.open(image_filename+".wav", "w") |
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output_file.setparams((1, 2, 44100, 0, "NONE", "not compressed")) |
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output_file.setparams((1, 2, 44100, 0, "NONE", "not compressed")) |
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pb = ProgressBar().start() |
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n = float(len(image)) |
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for index, column in enumerate(image): |
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write_column(output_file, column) |
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pb.update(index*100/n) |
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output_file.writeframes(data) |
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output_file.close() |
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output_file.close() |
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print "Wrote %s.wav" % image_filename |
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print "Wrote %s.wav" % image_filename |
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