matlab cmake fixed, rof tv eps

2 files changed, 21 insertions, 23 deletions

diff --git a/demos/demo_cpu_regularisers.py b/demos/demo_cpu_regularisers.py
index 32b97ce..4866811 100644
--- a/demos/demo_cpu_regularisers.py
+++ b/demos/demo_cpu_regularisers.py
@@ -32,7 +32,7 @@ def printParametersToString(pars):
 ###############################################################################
 
 #filename = os.path.join( "data" ,"lena_gray_512.tif")
-filename = "/home/algol/Documents/DEV/CCPi-Regularisation-Toolkit/test/lena_gray_512.tif"
+filename = "/home/kjy41806/Documents/SOFT/CCPi-Regularisation-Toolkit/test/lena_gray_512.tif"
 
 # read image
 Im = plt.imread(filename)
@@ -86,13 +86,13 @@ imgplot = plt.imshow(u0,cmap="gray")
 pars = {'algorithm': ROF_TV, \
         'input' : u0,\
         'regularisation_parameter':0.02,\
-        'number_of_iterations': 5000,\
-        'time_marching_parameter': 0.000385,\
+        'number_of_iterations': 1000,\
+        'time_marching_parameter': 0.001,\
         'tolerance_constant':1e-06}
 
 print ("#############ROF TV CPU####################")
 start_time = timeit.default_timer()
-(rof_cpu,info_vec) = ROF_TV(pars['input'],
+(rof_cpu,info_vec_cpu) = ROF_TV(pars['input'],
              pars['regularisation_parameter'],
              pars['number_of_iterations'],
              pars['time_marching_parameter'],
@@ -130,14 +130,14 @@ imgplot = plt.imshow(u0,cmap="gray")
 pars = {'algorithm' : FGP_TV, \
         'input' : u0,\
         'regularisation_parameter':0.02, \
-        'number_of_iterations' :800 ,\
+        'number_of_iterations' :200 ,\
         'tolerance_constant':1e-06,\
         'methodTV': 0 ,\
         'nonneg': 0}
         
 print ("#############FGP TV CPU####################")
 start_time = timeit.default_timer()
-fgp_cpu,info_vec = FGP_TV(pars['input'], 
+fgp_cpu,info_vec_cpu = FGP_TV(pars['input'], 
               pars['regularisation_parameter'],
               pars['number_of_iterations'],
               pars['tolerance_constant'], 
diff --git a/demos/demo_gpu_regularisers.py b/demos/demo_gpu_regularisers.py
index 89bb948..212ad5a 100644
--- a/demos/demo_gpu_regularisers.py
+++ b/demos/demo_gpu_regularisers.py
@@ -83,16 +83,18 @@ imgplot = plt.imshow(u0,cmap="gray")
 # set parameters
 pars = {'algorithm': ROF_TV, \
         'input' : u0,\
-        'regularisation_parameter':0.04,\
-        'number_of_iterations': 1200,\
-        'time_marching_parameter': 0.0025
-        }
+        'regularisation_parameter':0.02,\
+        'number_of_iterations': 5000,\
+        'time_marching_parameter': 0.001,\
+        'tolerance_constant':1e-06}
+
 print ("##############ROF TV GPU##################")
 start_time = timeit.default_timer()
-rof_gpu = ROF_TV(pars['input'], 
-                     pars['regularisation_parameter'],
-                     pars['number_of_iterations'], 
-                     pars['time_marching_parameter'],'gpu')
+(rof_gpu, info_vec_gpu) = ROF_TV(pars['input'],
+             pars['regularisation_parameter'],
+             pars['number_of_iterations'],
+             pars['time_marching_parameter'],
+             pars['tolerance_constant'], 'gpu')
 
 Qtools = QualityTools(Im, rof_gpu)
 pars['rmse'] = Qtools.rmse()
@@ -125,23 +127,20 @@ imgplot = plt.imshow(u0,cmap="gray")
 # set parameters
 pars = {'algorithm' : FGP_TV, \
         'input' : u0,\
-        'regularisation_parameter':0.04, \
-        'number_of_iterations' :1200 ,\
+        'regularisation_parameter':0.02, \
+        'number_of_iterations' :300 ,\
         'tolerance_constant':1e-06,\
         'methodTV': 0 ,\
-        'nonneg': 0 ,\
-        'printingOut': 0 
-        }
+        'nonneg': 0}
 
 print ("##############FGP TV GPU##################")
 start_time = timeit.default_timer()
-fgp_gpu = FGP_TV(pars['input'], 
+(fgp_gpu, info_vec_gpu) = FGP_TV(pars['input'], 
               pars['regularisation_parameter'],
               pars['number_of_iterations'],
               pars['tolerance_constant'], 
               pars['methodTV'],
-              pars['nonneg'],
-              pars['printingOut'],'gpu')
+              pars['nonneg'],'gpu')
 Qtools = QualityTools(Im, fgp_gpu)
 pars['rmse'] = Qtools.rmse()
 pars['algorithm'] = FGP_TV
@@ -157,7 +156,6 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
          verticalalignment='top', bbox=props)
 imgplot = plt.imshow(fgp_gpu, cmap="gray")
 plt.title('{}'.format('GPU results'))
-
 #%%
 print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
 print ("____________SB-TV regulariser______________")