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-rw-r--r--Wrappers/Python/demos/demo_cpu_regularisers.py50
-rw-r--r--Wrappers/Python/demos/demo_cpu_regularisers3D.py67
-rw-r--r--Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py86
-rw-r--r--Wrappers/Python/demos/demo_gpu_regularisers.py49
-rw-r--r--Wrappers/Python/demos/demo_gpu_regularisers3D.py66
5 files changed, 293 insertions, 25 deletions
diff --git a/Wrappers/Python/demos/demo_cpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_regularisers.py
index 5c20244..b94f11c 100644
--- a/Wrappers/Python/demos/demo_cpu_regularisers.py
+++ b/Wrappers/Python/demos/demo_cpu_regularisers.py
@@ -12,7 +12,7 @@ import matplotlib.pyplot as plt
import numpy as np
import os
import timeit
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, FGP_dTV, TNV, NDF, DIFF4th
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, TNV, NDF, DIFF4th
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -256,6 +256,54 @@ imgplot = plt.imshow(tgv_cpu, cmap="gray")
plt.title('{}'.format('CPU results'))
#%%
+
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("______________LLT- ROF (2D)________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure()
+plt.suptitle('Performance of LLT-ROF regulariser using the CPU')
+a=fig.add_subplot(1,2,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(u0,cmap="gray")
+
+# set parameters
+pars = {'algorithm' : LLT_ROF, \
+ 'input' : u0,\
+ 'regularisation_parameterROF':0.04, \
+ 'regularisation_parameterLLT':0.01, \
+ 'number_of_iterations' :500 ,\
+ 'time_marching_parameter' :0.0025 ,\
+ }
+
+print ("#############LLT- ROF CPU####################")
+start_time = timeit.default_timer()
+lltrof_cpu = LLT_ROF(pars['input'],
+ pars['regularisation_parameterROF'],
+ pars['regularisation_parameterLLT'],
+ pars['number_of_iterations'],
+ pars['time_marching_parameter'],'cpu')
+
+rms = rmse(Im, lltrof_cpu)
+pars['rmse'] = rms
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,2,2)
+
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(lltrof_cpu, cmap="gray")
+plt.title('{}'.format('CPU results'))
+
+#%%
+
+
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("________________NDF (2D)___________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
diff --git a/Wrappers/Python/demos/demo_cpu_regularisers3D.py b/Wrappers/Python/demos/demo_cpu_regularisers3D.py
index 8ee157e..9c28de1 100644
--- a/Wrappers/Python/demos/demo_cpu_regularisers3D.py
+++ b/Wrappers/Python/demos/demo_cpu_regularisers3D.py
@@ -12,7 +12,7 @@ import matplotlib.pyplot as plt
import numpy as np
import os
import timeit
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, LLT_ROF, FGP_dTV, NDF, DIFF4th
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -85,7 +85,7 @@ print ("_______________ROF-TV (3D)_________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(1)
+fig = plt.figure()
plt.suptitle('Performance of ROF-TV regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy 15th slice of a volume')
@@ -120,13 +120,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(rof_cpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the CPU using ROF-TV'))
-
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________FGP-TV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(2)
+fig = plt.figure()
plt.suptitle('Performance of FGP-TV regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -170,12 +170,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(fgp_cpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the CPU using FGP-TV'))
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________SB-TV (3D)_________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(3)
+fig = plt.figure()
plt.suptitle('Performance of SB-TV regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -216,12 +217,58 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(sb_cpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the CPU using SB-TV'))
+#%%
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("_______________LLT-ROF (3D)_________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure()
+plt.suptitle('Performance of LLT-ROF regulariser using the CPU')
+a=fig.add_subplot(1,2,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(noisyVol[10,:,:],cmap="gray")
+
+# set parameters
+pars = {'algorithm' : LLT_ROF, \
+ 'input' : noisyVol,\
+ 'regularisation_parameterROF':0.04, \
+ 'regularisation_parameterLLT':0.015, \
+ 'number_of_iterations' :300 ,\
+ 'time_marching_parameter' :0.0025 ,\
+ }
+
+print ("#############LLT ROF CPU####################")
+start_time = timeit.default_timer()
+lltrof_cpu3D = LLT_ROF(pars['input'],
+ pars['regularisation_parameterROF'],
+ pars['regularisation_parameterLLT'],
+ pars['number_of_iterations'],
+ pars['time_marching_parameter'],'cpu')
+
+rms = rmse(idealVol, lltrof_cpu3D)
+pars['rmse'] = rms
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,2,2)
+
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(lltrof_cpu3D[10,:,:], cmap="gray")
+plt.title('{}'.format('Recovered volume on the CPU using LLT-ROF'))
+
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("________________NDF (3D)___________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(4)
+fig = plt.figure()
plt.suptitle('Performance of NDF regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy volume')
@@ -262,13 +309,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(ndf_cpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the CPU using NDF iterations'))
-
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("___Anisotropic Diffusion 4th Order (2D)____")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(5)
+fig = plt.figure()
plt.suptitle('Performance of Diff4th regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy volume')
@@ -307,13 +354,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(diff4th_cpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the CPU using DIFF4th iterations'))
-
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________FGP-dTV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(6)
+fig = plt.figure()
plt.suptitle('Performance of FGP-dTV regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
diff --git a/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py
index 46b8ffc..e45dc40 100644
--- a/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py
+++ b/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py
@@ -12,7 +12,7 @@ import matplotlib.pyplot as plt
import numpy as np
import os
import timeit
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, DIFF4th
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -352,8 +352,7 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(tgv_cpu, cmap="gray")
plt.title('{}'.format('CPU results'))
-
-print ("##############SB TV GPU##################")
+print ("##############TGV GPU##################")
start_time = timeit.default_timer()
tgv_gpu = TGV(pars['input'],
pars['regularisation_parameter'],
@@ -392,6 +391,87 @@ else:
print ("Arrays match")
#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("____________LLT-ROF bench___________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure()
+plt.suptitle('Comparison of LLT-ROF regulariser using CPU and GPU implementations')
+a=fig.add_subplot(1,4,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(u0,cmap="gray")
+
+# set parameters
+pars = {'algorithm' : LLT_ROF, \
+ 'input' : u0,\
+ 'regularisation_parameterROF':0.04, \
+ 'regularisation_parameterLLT':0.01, \
+ 'number_of_iterations' :500 ,\
+ 'time_marching_parameter' :0.0025 ,\
+ }
+
+print ("#############LLT- ROF CPU####################")
+start_time = timeit.default_timer()
+lltrof_cpu = LLT_ROF(pars['input'],
+ pars['regularisation_parameterROF'],
+ pars['regularisation_parameterLLT'],
+ pars['number_of_iterations'],
+ pars['time_marching_parameter'],'cpu')
+
+rms = rmse(Im, lltrof_cpu)
+pars['rmse'] = rms
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,4,2)
+
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(lltrof_cpu, cmap="gray")
+plt.title('{}'.format('CPU results'))
+
+print ("#############LLT- ROF GPU####################")
+start_time = timeit.default_timer()
+lltrof_gpu = LLT_ROF(pars['input'],
+ pars['regularisation_parameterROF'],
+ pars['regularisation_parameterLLT'],
+ pars['number_of_iterations'],
+ pars['time_marching_parameter'],'gpu')
+
+rms = rmse(Im, lltrof_gpu)
+pars['rmse'] = rms
+pars['algorithm'] = LLT_ROF
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,4,3)
+
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(lltrof_gpu, cmap="gray")
+plt.title('{}'.format('GPU results'))
+
+print ("--------Compare the results--------")
+tolerance = 1e-05
+diff_im = np.zeros(np.shape(lltrof_gpu))
+diff_im = abs(lltrof_cpu - lltrof_gpu)
+diff_im[diff_im > tolerance] = 1
+a=fig.add_subplot(1,4,4)
+imgplot = plt.imshow(diff_im, vmin=0, vmax=1, cmap="gray")
+plt.title('{}'.format('Pixels larger threshold difference'))
+if (diff_im.sum() > 1):
+ print ("Arrays do not match!")
+else:
+ print ("Arrays match")
+#%%
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________NDF bench___________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
diff --git a/Wrappers/Python/demos/demo_gpu_regularisers.py b/Wrappers/Python/demos/demo_gpu_regularisers.py
index 792a019..de0cbde 100644
--- a/Wrappers/Python/demos/demo_gpu_regularisers.py
+++ b/Wrappers/Python/demos/demo_gpu_regularisers.py
@@ -12,7 +12,7 @@ import matplotlib.pyplot as plt
import numpy as np
import os
import timeit
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, DIFF4th
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -254,6 +254,53 @@ imgplot = plt.imshow(tgv_gpu, cmap="gray")
plt.title('{}'.format('GPU results'))
#%%
+
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("______________LLT- ROF (2D)________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure()
+plt.suptitle('Performance of LLT-ROF regulariser using the GPU')
+a=fig.add_subplot(1,2,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(u0,cmap="gray")
+
+# set parameters
+pars = {'algorithm' : LLT_ROF, \
+ 'input' : u0,\
+ 'regularisation_parameterROF':0.04, \
+ 'regularisation_parameterLLT':0.01, \
+ 'number_of_iterations' :500 ,\
+ 'time_marching_parameter' :0.0025 ,\
+ }
+
+print ("#############LLT- ROF GPU####################")
+start_time = timeit.default_timer()
+lltrof_gpu = LLT_ROF(pars['input'],
+ pars['regularisation_parameterROF'],
+ pars['regularisation_parameterLLT'],
+ pars['number_of_iterations'],
+ pars['time_marching_parameter'],'gpu')
+
+
+rms = rmse(Im, lltrof_gpu)
+pars['rmse'] = rms
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,2,2)
+
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(lltrof_gpu, cmap="gray")
+plt.title('{}'.format('GPU results'))
+
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________NDF regulariser_____________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
diff --git a/Wrappers/Python/demos/demo_gpu_regularisers3D.py b/Wrappers/Python/demos/demo_gpu_regularisers3D.py
index 13c4e7b..d5f9a39 100644
--- a/Wrappers/Python/demos/demo_gpu_regularisers3D.py
+++ b/Wrappers/Python/demos/demo_gpu_regularisers3D.py
@@ -12,7 +12,7 @@ import matplotlib.pyplot as plt
import numpy as np
import os
import timeit
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, LLT_ROF, FGP_dTV, NDF, DIFF4th
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -86,12 +86,13 @@ for i in range (slices):
noisyRef[i,:,:] = Im + np.random.normal(loc = 0 , scale = 0.01 * Im , size = np.shape(Im))
idealVol[i,:,:] = Im
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________ROF-TV (3D)_________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(1)
+fig = plt.figure()
plt.suptitle('Performance of ROF-TV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy 15th slice of a volume')
@@ -125,13 +126,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
verticalalignment='top', bbox=props)
imgplot = plt.imshow(rof_gpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the GPU using ROF-TV'))
-
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________FGP-TV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(2)
+fig = plt.figure()
plt.suptitle('Performance of FGP-TV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -174,12 +175,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(fgp_gpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the GPU using FGP-TV'))
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________SB-TV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(3)
+fig = plt.figure()
plt.suptitle('Performance of SB-TV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -219,14 +221,58 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
verticalalignment='top', bbox=props)
imgplot = plt.imshow(sb_gpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the GPU using SB-TV'))
+#%%
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("_______________LLT-ROF (3D)_________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure()
+plt.suptitle('Performance of LLT-ROF regulariser using the GPU')
+a=fig.add_subplot(1,2,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(noisyVol[10,:,:],cmap="gray")
+
+# set parameters
+pars = {'algorithm' : LLT_ROF, \
+ 'input' : noisyVol,\
+ 'regularisation_parameterROF':0.04, \
+ 'regularisation_parameterLLT':0.015, \
+ 'number_of_iterations' :300 ,\
+ 'time_marching_parameter' :0.0025 ,\
+ }
+
+print ("#############LLT ROF CPU####################")
+start_time = timeit.default_timer()
+lltrof_gpu3D = LLT_ROF(pars['input'],
+ pars['regularisation_parameterROF'],
+ pars['regularisation_parameterLLT'],
+ pars['number_of_iterations'],
+ pars['time_marching_parameter'],'gpu')
+rms = rmse(idealVol, lltrof_gpu3D)
+pars['rmse'] = rms
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,2,2)
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(lltrof_gpu3D[10,:,:], cmap="gray")
+plt.title('{}'.format('Recovered volume on the GPU using LLT-ROF'))
+
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________NDF-TV (3D)_________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(4)
+fig = plt.figure()
plt.suptitle('Performance of NDF regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -267,13 +313,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(ndf_gpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('Recovered volume on the GPU using NDF'))
-
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("___Anisotropic Diffusion 4th Order (3D)____")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(5)
+fig = plt.figure()
plt.suptitle('Performance of DIFF4th regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -312,13 +358,13 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(diff4_gpu3D[10,:,:], cmap="gray")
plt.title('{}'.format('GPU results'))
-
+#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________FGP-dTV (3D)________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(6)
+fig = plt.figure()
plt.suptitle('Performance of FGP-dTV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-06 18:34:29 +0000