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authorEdoardo Pasca <edo.paskino@gmail.com>2018-01-22 16:31:15 +0000
committerEdoardo Pasca <edo.paskino@gmail.com>2018-01-23 22:45:21 +0000
commit6593e5793c5387d60807764dfebaa29c66ccb4f4 (patch)
tree8c586615c4465d4316faaf713d556ee391eaad21 /Wrappers
parent3cc20874098867aab11313b7fb1d1f65c400fa0c (diff)
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debugging #13
Diffstat (limited to 'Wrappers')
-rw-r--r--Wrappers/Python/test/test_regularizers.py74
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()