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authorDaniil Kazantsev <dkazanc@hotmail.com>2018-04-16 13:38:40 +0100
committerDaniil Kazantsev <dkazanc@hotmail.com>2018-04-16 13:38:40 +0100
commit80c5a5e5de2aca8d5c7b96f0adc91b5738cc9025 (patch)
treeebf4da0a18f0af799ae771b52513ac59a1228e1a /Wrappers/Python/demos
parent7ae26b005c5f3d9ca0181ab1cf06b6ee8df5ed69 (diff)
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SB TV method CPU/GPU added
Diffstat (limited to 'Wrappers/Python/demos')
-rw-r--r--Wrappers/Python/demos/demo_cpu_regularisers.py103
-rw-r--r--Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py90
-rw-r--r--Wrappers/Python/demos/demo_gpu_regularisers.py102
3 files changed, 283 insertions, 12 deletions
diff --git a/Wrappers/Python/demos/demo_cpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_regularisers.py
index 00beb0b..0e4355b 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, FGP_dTV
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, FGP_dTV
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -141,13 +141,60 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(fgp_cpu, cmap="gray")
plt.title('{}'.format('CPU results'))
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("_______________SB-TV (2D)__________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure(3)
+plt.suptitle('Performance of SB-TV 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' : SB_TV, \
+ 'input' : u0,\
+ 'regularisation_parameter':0.04, \
+ 'number_of_iterations' :150 ,\
+ 'tolerance_constant':1e-06,\
+ 'methodTV': 0 ,\
+ 'printingOut': 0
+ }
+
+print ("#############SB TV CPU####################")
+start_time = timeit.default_timer()
+sb_cpu = SB_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['printingOut'],'cpu')
+
+
+rms = rmse(Im, sb_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(sb_cpu, cmap="gray")
+plt.title('{}'.format('CPU results'))
+
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_____________FGP-dTV (2D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(3)
+fig = plt.figure(4)
plt.suptitle('Performance of FGP-dTV regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -223,7 +270,7 @@ print ("_______________ROF-TV (3D)_________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(4)
+fig = plt.figure(5)
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')
@@ -263,7 +310,7 @@ print ("_______________FGP-TV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(5)
+fig = plt.figure(6)
plt.suptitle('Performance of FGP-TV regulariser using the CPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -307,13 +354,59 @@ 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(7)
+plt.suptitle('Performance of SB-TV 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' : SB_TV, \
+ 'input' : noisyVol,\
+ 'regularisation_parameter':0.04, \
+ 'number_of_iterations' :150 ,\
+ 'tolerance_constant':0.00001,\
+ 'methodTV': 0 ,\
+ 'printingOut': 0
+ }
+
+print ("#############SB TV CPU####################")
+start_time = timeit.default_timer()
+sb_cpu3D = SB_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['printingOut'],'cpu')
+
+rms = rmse(idealVol, sb_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(sb_cpu3D[10,:,:], cmap="gray")
+plt.title('{}'.format('Recovered volume on the CPU using SB-TV'))
+
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________FGP-dTV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(6)
+fig = plt.figure(8)
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 310cf75..d8e2da7 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, FGP_dTV
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, FGP_dTV
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -218,13 +218,99 @@ if (diff_im.sum() > 1):
else:
print ("Arrays match")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("____________SB-TV bench___________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure(3)
+plt.suptitle('Comparison of SB-TV 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' : SB_TV, \
+ 'input' : u0,\
+ 'regularisation_parameter':0.04, \
+ 'number_of_iterations' :150 ,\
+ 'tolerance_constant':1e-05,\
+ 'methodTV': 0 ,\
+ 'printingOut': 0
+ }
+
+print ("#############SB-TV CPU####################")
+start_time = timeit.default_timer()
+sb_cpu = SB_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['printingOut'],'cpu')
+
+
+rms = rmse(Im, sb_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(sb_cpu, cmap="gray")
+plt.title('{}'.format('CPU results'))
+
+
+print ("##############SB TV GPU##################")
+start_time = timeit.default_timer()
+sb_gpu = SB_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['printingOut'],'gpu')
+
+rms = rmse(Im, sb_gpu)
+pars['rmse'] = rms
+pars['algorithm'] = SB_TV
+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(sb_gpu, cmap="gray")
+plt.title('{}'.format('GPU results'))
+
+print ("--------Compare the results--------")
+tolerance = 1e-05
+diff_im = np.zeros(np.shape(rof_cpu))
+diff_im = abs(sb_cpu - sb_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 ("____________FGP-dTV bench___________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(3)
+fig = plt.figure(4)
plt.suptitle('Comparison of FGP-dTV regulariser using CPU and GPU implementations')
a=fig.add_subplot(1,4,1)
a.set_title('Noisy Image')
diff --git a/Wrappers/Python/demos/demo_gpu_regularisers.py b/Wrappers/Python/demos/demo_gpu_regularisers.py
index 24a3c88..25d8d85 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, FGP_dTV
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, FGP_dTV
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -139,12 +139,59 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(fgp_gpu, cmap="gray")
plt.title('{}'.format('GPU results'))
+
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
-print ("____________FGP-dTV bench___________________")
+print ("____________SB-TV bench___________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
fig = plt.figure(3)
+plt.suptitle('Performance of the SB-TV 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' : SB_TV, \
+ 'input' : u0,\
+ 'regularisation_parameter':0.04, \
+ 'number_of_iterations' :150 ,\
+ 'tolerance_constant':1e-06,\
+ 'methodTV': 0 ,\
+ 'printingOut': 0
+ }
+
+print ("##############SB TV GPU##################")
+start_time = timeit.default_timer()
+sb_gpu = SB_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['printingOut'],'gpu')
+
+rms = rmse(Im, sb_gpu)
+pars['rmse'] = rms
+pars['algorithm'] = SB_TV
+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(sb_gpu, cmap="gray")
+plt.title('{}'.format('GPU results'))
+
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("____________FGP-dTV bench___________________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure(4)
plt.suptitle('Performance of the FGP-dTV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -219,7 +266,7 @@ print ("_______________ROF-TV (3D)_________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(4)
+fig = plt.figure(5)
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')
@@ -259,7 +306,7 @@ print ("_______________FGP-TV (3D)__________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(5)
+fig = plt.figure(6)
plt.suptitle('Performance of FGP-TV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')
@@ -302,13 +349,58 @@ 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(7)
+plt.suptitle('Performance of SB-TV 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' : SB_TV, \
+ 'input' : noisyVol,\
+ 'regularisation_parameter':0.04, \
+ 'number_of_iterations' :100 ,\
+ 'tolerance_constant':1e-05,\
+ 'methodTV': 0 ,\
+ 'printingOut': 0
+ }
+
+print ("#############SB TV GPU####################")
+start_time = timeit.default_timer()
+sb_gpu3D = SB_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['printingOut'],'gpu')
+
+rms = rmse(idealVol, sb_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(sb_gpu3D[10,:,:], cmap="gray")
+plt.title('{}'.format('Recovered volume on the GPU using SB-TV'))
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("_______________FGP-dTV (3D)________________")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
## plot
-fig = plt.figure(6)
+fig = plt.figure(8)
plt.suptitle('Performance of FGP-dTV regulariser using the GPU')
a=fig.add_subplot(1,2,1)
a.set_title('Noisy Image')