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