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47 lines
1.1 KiB
47 lines
1.1 KiB
import numpy as np
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import matplotlib.pyplot as plt
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import lcn
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from scipy import misc
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# load and convert to float
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img = misc.imread('img.png')
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img = img.astype(np.float32) / 255.0
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# normalize
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img_lcn, img_std = lcn.normalize(img, 5, 0.05)
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# normalize to reasonable range between 0 and 1
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# img_lcn = img_lcn/3.0
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# img_lcn = np.maximum(img_lcn,0.0)
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# img_lcn = np.minimum(img_lcn,1.0)
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# save to file
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# misc.imsave('lcn2.png',img_lcn)
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print("Orig Image: %d x %d (%s), Min: %f, Max: %f" % \
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(img.shape[0], img.shape[1], img.dtype, img.min(), img.max()))
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print("Norm Image: %d x %d (%s), Min: %f, Max: %f" % \
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(img_lcn.shape[0], img_lcn.shape[1], img_lcn.dtype, img_lcn.min(), img_lcn.max()))
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# plot original image
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plt.figure(1)
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img_plot = plt.imshow(img)
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img_plot.set_cmap('gray')
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plt.clim(0, 1) # fix range
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plt.tight_layout()
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# plot normalized image
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plt.figure(2)
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img_lcn_plot = plt.imshow(img_lcn)
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img_lcn_plot.set_cmap('gray')
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# plt.clim(0, 1) # fix range
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plt.tight_layout()
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# plot stddev image
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plt.figure(3)
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img_std_plot = plt.imshow(img_std)
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img_std_plot.set_cmap('gray')
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# plt.clim(0, 0.1) # fix range
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plt.tight_layout()
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plt.show()
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