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-rw-r--r--Wrappers/Python/demo/test_cpu_regularizers.py10
1 files changed, 3 insertions, 7 deletions
diff --git a/Wrappers/Python/demo/test_cpu_regularizers.py b/Wrappers/Python/demo/test_cpu_regularizers.py
index 7f08605..1d97857 100644
--- a/Wrappers/Python/demo/test_cpu_regularizers.py
+++ b/Wrappers/Python/demo/test_cpu_regularizers.py
@@ -137,7 +137,7 @@ pars = {'algorithm' : TV_FGP_CPU , \
'printingOut': 0
}
-out = TV_FGP_CPU (pars['input'],
+fgp = TV_FGP_CPU(pars['input'],
pars['regularization_parameter'],
pars['number_of_iterations'],
pars['tolerance_constant'],
@@ -145,7 +145,6 @@ out = TV_FGP_CPU (pars['input'],
pars['nonneg'],
pars['printingOut'])
-fgp = out[0]
rms = rmse(Im, fgp)
pars['rmse'] = rms
@@ -154,7 +153,7 @@ txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
print (txtstr)
-a=fig.add_subplot(2,4,4)
+a=fig.add_subplot(2,4,3)
# these are matplotlib.patch.Patch properties
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
@@ -168,7 +167,6 @@ a.text(0.05, 0.95, txtstr, transform=a.transAxes, fontsize=14,
###################### LLT_model #########################################
-"""
start_time = timeit.default_timer()
pars = {'algorithm': LLT_model , \
@@ -203,8 +201,6 @@ a.text(0.05, 0.95, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(llt,\
cmap="gray"
)
-"""
-
# ###################### PatchBased_Regul #########################################
# # Quick 2D denoising example in Matlab:
# # Im = double(imread('lena_gray_256.tif'))/255; % loading image
@@ -286,7 +282,7 @@ start_time = timeit.default_timer()
pars = {'algorithm': TV_ROF_CPU , \
'input' : u0,\
- 'regularization_parameter':0.04,\
+ 'regularization_parameter':0.07,\
'marching_step': 0.0025,\
'number_of_iterations': 300
}