diff options
| -rw-r--r-- | Wrappers/Python/test/test_regularizers.py | 74 |
1 files changed, 39 insertions, 35 deletions
diff --git a/Wrappers/Python/test/test_regularizers.py b/Wrappers/Python/test/test_regularizers.py index 27e4ed3..343708f 100644 --- a/Wrappers/Python/test/test_regularizers.py +++ b/Wrappers/Python/test/test_regularizers.py @@ -15,7 +15,7 @@ from enum import Enum import timeit #from PIL import Image #from Regularizer import Regularizer -from ccpi.imaging.Regularizer import Regularizer +from ccpi.filters.Regularizer import Regularizer ############################################################################### #https://stackoverflow.com/questions/13875989/comparing-image-in-url-to-image-in-filesystem-in-python/13884956#13884956 @@ -47,8 +47,8 @@ def nrmse(im1, im2): # u = SplitBregman_TV(single(u0), 10, 30, 1e-04); -#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"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() @@ -96,7 +96,7 @@ if use_object: # reg.setParameter(input=u0, regularization_parameter=10., #number_of_iterations=30, #tolerance_constant=1e-4, #TV_Penalty=Regularizer.TotalVariationPenalty.l1) - plotme = reg() [0] + plotme = reg(output_all=True) [0] pars = reg.pars textstr = reg.printParametersToString() @@ -127,8 +127,8 @@ imgplot = plt.imshow(plotme,cmap="gray") ###################### FGP_TV ######################################### # u = FGP_TV(single(u0), 0.05, 100, 1e-04); -out2 = Regularizer.FGP_TV(input=u0, regularization_parameter=0.0005, - number_of_iterations=50) +out2 = Regularizer.FGP_TV(input=u0, regularization_parameter=5e-4, + number_of_iterations=10, output_all=True) pars = out2[-2] reg_output.append(out2) @@ -154,10 +154,14 @@ imgplot = plt.imshow(reg_output[-1][0],cmap="gray") #Den = LLT_model(single(u0), 25, 0.0003, 300, 0.0001, 0); #input, regularization_parameter , time_step, number_of_iterations, # tolerance_constant, restrictive_Z_smoothing=0 + +del out2 out2 = Regularizer.LLT_model(input=u0, regularization_parameter=25, time_step=0.0003, - tolerance_constant=0.0001, + tolerance_constant=0.001, number_of_iterations=300) +print ("call ended??") +print (out2[0].shape) pars = out2[-2] reg_output.append(out2) @@ -180,24 +184,24 @@ imgplot = plt.imshow(reg_output[-1][0],cmap="gray") # # u0 = Im + .03*randn(size(Im)); u0(u0<0) = 0; % adding noise # # 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) -pars = out2[-2] -reg_output.append(out2) +# 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) +# a=fig.add_subplot(2,3,5) -textstr = out2[-1] +# 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") +# # 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") # ###################### TGV_PD ######################################### @@ -207,25 +211,25 @@ imgplot = plt.imshow(reg_output[-1][0],cmap="gray") # # u = PrimalDual_TGV(single(u0), 0.02, 1.3, 1, 550); -out2 = Regularizer.TGV_PD(input=u0, regularization_parameter=0.05, - first_order_term=1.3, - second_order_term=1, - number_of_iterations=550) -pars = out2[-2] -reg_output.append(out2) +# out2 = Regularizer.TGV_PD(input=u0, regularization_parameter=0.05, + # first_order_term=1.3, + # second_order_term=1, + # number_of_iterations=550) +# pars = out2[-2] +# reg_output.append(out2) -a=fig.add_subplot(2,3,6) +# a=fig.add_subplot(2,3,6) -textstr = out2[-1] +# 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") +# # 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") plt.show() |