diff options
author | Edoardo Pasca <edo.paskino@gmail.com> | 2017-08-25 17:08:19 +0100 |
---|---|---|
committer | Edoardo Pasca <edo.paskino@gmail.com> | 2017-08-25 17:08:19 +0100 |
commit | 97c0625ab3052aa59907ce5d30809f869d4f0622 (patch) | |
tree | 9636579c6cf7234c45bf395afe8e2cb78850e679 /src | |
parent | 83250cee1deff04c34d5ed9ad2d9dbde09cadcf6 (diff) | |
parent | 447756a338dfa993e2969298af19f1f9707a409a (diff) | |
download | regularization-97c0625ab3052aa59907ce5d30809f869d4f0622.tar.gz regularization-97c0625ab3052aa59907ce5d30809f869d4f0622.tar.bz2 regularization-97c0625ab3052aa59907ce5d30809f869d4f0622.tar.xz regularization-97c0625ab3052aa59907ce5d30809f869d4f0622.zip |
Merge branch 'pythonize' of https://github.com/vais-ral/CCPi-FISTA_Reconstruction into pythonize
Diffstat (limited to 'src')
-rw-r--r-- | src/Python/test_regularizers.py | 84 |
1 files changed, 64 insertions, 20 deletions
diff --git a/src/Python/test_regularizers.py b/src/Python/test_regularizers.py index d0bccaf..d2fbca6 100644 --- a/src/Python/test_regularizers.py +++ b/src/Python/test_regularizers.py @@ -5,15 +5,15 @@ Created on Fri Aug 4 11:10:05 2017 @author: ofn77899 """ -from ccpi.viewer.CILViewer2D import Converter -import vtk +#from ccpi.viewer.CILViewer2D import Converter +#import vtk import matplotlib.pyplot as plt import numpy as np import os from enum import Enum import timeit - +#from PIL import Image #from Regularizer import Regularizer from ccpi.imaging.Regularizer import Regularizer @@ -48,12 +48,18 @@ def nrmse(im1, im2): #filename = r"C:\Users\ofn77899\Documents\GitHub\CCPi-FISTA_reconstruction\data\lena_gray_512.tif" filename = r"/home/ofn77899/Reconstruction/CCPi-FISTA_Reconstruction/data/lena_gray_512.tif" +#filename = r'/home/algol/Documents/Python/STD_test_images/lena_gray_512.tif' + +#reader = vtk.vtkTIFFReader() +#reader.SetFileName(os.path.normpath(filename)) +#reader.Update() +Im = plt.imread(filename) +#Im = Image.open('/home/algol/Documents/Python/STD_test_images/lena_gray_512.tif')/255 +#img.show() +Im = np.asarray(Im, dtype='float32') + + -reader = vtk.vtkTIFFReader() -reader.SetFileName(os.path.normpath(filename)) -reader.Update() -#vtk returns 3D images, let's take just the one slice there is as 2D -Im = Converter.vtk2numpy(reader.GetOutput()).T[0]/255 #imgplot = plt.imshow(Im) perc = 0.05 @@ -82,6 +88,7 @@ reg_output = [] use_object = True if use_object: reg = Regularizer(Regularizer.Algorithm.SplitBregman_TV) + print (reg.pars) reg.setParameter(input=u0) reg.setParameter(regularization_parameter=10.) # or @@ -115,7 +122,7 @@ props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) # place a text box in upper left in axes coords a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) -imgplot = plt.imshow(plotme) +imgplot = plt.imshow(plotme,cmap="gray") ###################### FGP_TV ######################################### # u = FGP_TV(single(u0), 0.05, 100, 1e-04); @@ -131,10 +138,28 @@ textstr = out2[-1] # these are matplotlib.patch.Patch properties props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) +out2 = Regularizer.PatchBased_Regul(input=u0, regularization_parameter=0.05, + searching_window_ratio=3, + similarity_window_ratio=1, + PB_filtering_parameter=0.08) +pars = out2[-2] +reg_output.append(out2) + +a=fig.add_subplot(2,3,5) + + +textstr = out2[-1] + +# these are matplotlib.patch.Patch properties +props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) # place a text box in upper left in axes coords a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, - verticalalignment='top', bbox=props) + verticalalignment='top', bbox=props) imgplot = plt.imshow(reg_output[-1][0]) +# place a text box in upper left in axes coords +a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, + verticalalignment='top', bbox=props) +imgplot = plt.imshow(reg_output[-1][0],cmap="gray") ###################### LLT_model ######################################### # * u0 = Im + .03*randn(size(Im)); % adding noise @@ -151,13 +176,32 @@ pars = out2[-2] reg_output.append(out2) a=fig.add_subplot(2,3,4) +out2 = Regularizer.PatchBased_Regul(input=u0, regularization_parameter=0.05, + searching_window_ratio=3, + similarity_window_ratio=1, + PB_filtering_parameter=0.08) +pars = out2[-2] +reg_output.append(out2) + +a=fig.add_subplot(2,3,5) + + +textstr = out2[-1] + +# these are matplotlib.patch.Patch properties +props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) +# place a text box in upper left in axes coords +a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, + verticalalignment='top', bbox=props) +imgplot = plt.imshow(reg_output[-1][0],cmap="gray") + textstr = out2[-1] # these are matplotlib.patch.Patch properties props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) # place a text box in upper left in axes coords a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) -imgplot = plt.imshow(reg_output[-1][0]) +imgplot = plt.imshow(reg_output[-1][0],cmap="gray") # ###################### PatchBased_Regul ######################################### # # Quick 2D denoising example in Matlab: @@ -166,9 +210,9 @@ imgplot = plt.imshow(reg_output[-1][0]) # # ImDen = PB_Regul_CPU(single(u0), 3, 1, 0.08, 0.05); out2 = Regularizer.PatchBased_Regul(input=u0, regularization_parameter=0.05, - searching_window_ratio=3, - similarity_window_ratio=1, - PB_filtering_parameter=0.08) + searching_window_ratio=3, + similarity_window_ratio=1, + PB_filtering_parameter=0.08) pars = out2[-2] reg_output.append(out2) @@ -182,7 +226,7 @@ props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) # place a text box in upper left in axes coords a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) -imgplot = plt.imshow(reg_output[-1][0]) +imgplot = plt.imshow(reg_output[-1][0],cmap="gray") # ###################### TGV_PD ######################################### @@ -193,9 +237,9 @@ imgplot = plt.imshow(reg_output[-1][0]) out2 = Regularizer.TGV_PD(input=u0, regularization_parameter=0.05, - first_order_term=1.3, - second_order_term=1, - number_of_iterations=550) + first_order_term=1.3, + second_order_term=1, + number_of_iterations=550) pars = out2[-2] reg_output.append(out2) @@ -209,8 +253,8 @@ textstr = out2[-1] props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) # place a text box in upper left in axes coords a.text(0.05, 0.95, textstr, transform=a.transAxes, fontsize=14, - verticalalignment='top', bbox=props) -imgplot = plt.imshow(reg_output[-1][0]) + verticalalignment='top', bbox=props) +imgplot = plt.imshow(reg_output[-1][0],cmap="gray") plt.show() |