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-rw-r--r--src/Python/test_regularizers.py124
1 files changed, 85 insertions, 39 deletions
diff --git a/src/Python/test_regularizers.py b/src/Python/test_regularizers.py
index 755804a..86849eb 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
@@ -46,12 +46,20 @@ def nrmse(im1, im2):
# u0 = Im + .05*randn(size(Im)); u0(u0 < 0) = 0;
# u = SplitBregman_TV(single(u0), 10, 30, 1e-04);
-filename = r"C:\Users\ofn77899\Documents\GitHub\CCPi-FISTA_reconstruction\data\lena_gray_512.tif"
-reader = vtk.vtkTIFFReader()
-reader.SetFileName(os.path.normpath(filename))
-reader.Update()
+#filename = r"C:\Users\ofn77899\Documents\GitHub\CCPi-FISTA_reconstruction\data\lena_gray_512.tif"
+#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
+#Im = Converter.vtk2numpy(reader.GetOutput()).T[0]/255
+filename = '/home/algol/Documents/Python/STD_test_images/lena_gray_512.tif'
+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')
+
+
+
#imgplot = plt.imshow(Im)
perc = 0.05
@@ -80,6 +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
@@ -113,7 +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);
@@ -129,10 +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
@@ -149,13 +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:
@@ -163,24 +209,24 @@ imgplot = plt.imshow(reg_output[-1][0])
# # 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])
+# 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 #########################################
@@ -190,25 +236,25 @@ imgplot = plt.imshow(reg_output[-1][0])
# # 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])
+# 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()
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-07 16:39:52 +0000