diff options
Diffstat (limited to 'Wrappers/Python/test')
| -rw-r--r-- | Wrappers/Python/test/test_gpu_regularizers.py | 54 |
1 files changed, 29 insertions, 25 deletions
diff --git a/Wrappers/Python/test/test_gpu_regularizers.py b/Wrappers/Python/test/test_gpu_regularizers.py index 18fbdd3..735a25d 100644 --- a/Wrappers/Python/test/test_gpu_regularizers.py +++ b/Wrappers/Python/test/test_gpu_regularizers.py @@ -40,7 +40,8 @@ filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif") Im = plt.imread(filename) Im = np.asarray(Im, dtype='float32') -perc = 0.15 +Im = Im/255 +perc = 0.075 u0 = Im + np.random.normal(loc = Im , scale = perc * Im , size = np.shape(Im)) @@ -53,49 +54,52 @@ fig = plt.figure() a=fig.add_subplot(2,3,1) a.set_title('noise') -imgplot = plt.imshow(u0#,cmap="gray" - ) +imgplot = plt.imshow(u0,cmap="gray") ## Diff4thHajiaboli start_time = timeit.default_timer() pars = {'algorithm' : Diff4thHajiaboli , \ 'input' : u0, - 'regularization_parameter':0.02 , \ -'number_of_iterations' :150 ,\ -'edge_preserving_parameter':0.001 + 'edge_preserv_parameter':0.1 , \ +'number_of_iterations' :250 ,\ +'time_marching_parameter':0.03 ,\ +'regularization_parameter':0.7 } + + d4h = Diff4thHajiaboli(pars['input'], - pars['regularization_parameter'], + pars['edge_preserv_parameter'], pars['number_of_iterations'], - pars['edge_preserving_parameter']) + pars['time_marching_parameter'], + pars['regularization_parameter']) +rms = rmse(Im, d4h) +pars['rmse'] = rms txtstr = printParametersToString(pars) txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time) print (txtstr) a=fig.add_subplot(2,3,2) # these are matplotlib.patch.Patch properties -props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) +props = dict(boxstyle='round', facecolor='wheat', alpha=0.75) # place a text box in upper left in axes coords -a.text(0.05, 0.95, txtstr, transform=a.transAxes, fontsize=14, +a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=12, verticalalignment='top', bbox=props) -imgplot = plt.imshow(d4h #, cmap="gray" - ) +imgplot = plt.imshow(d4h, cmap="gray") a=fig.add_subplot(2,3,5) # 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, 'd4h - u0', transform=a.transAxes, fontsize=14, +a.text(0.05, 0.95, 'd4h - u0', transform=a.transAxes, fontsize=12, verticalalignment='top', bbox=props) -imgplot = plt.imshow(d4h - u0 #, cmap="gray" - ) +imgplot = plt.imshow((d4h - u0)**2, cmap="gray") ## Patch Based Regul NML start_time = timeit.default_timer() - +""" pars = {'algorithm' : NML , \ 'input' : u0, 'SearchW_real':3 , \ @@ -103,13 +107,15 @@ pars = {'algorithm' : NML , \ 'h':0.05 ,# 'lambda' : 0.08 } +""" pars = { 'input' : u0, - 'regularization_parameter': 0.05,\ + 'regularization_parameter': 0.01,\ 'searching_window_ratio':3, \ 'similarity_window_ratio':1,\ - 'PB_filtering_parameter': 0.06 + 'PB_filtering_parameter': 0.2 } + nml = NML(pars['input'], pars['searching_window_ratio'], pars['similarity_window_ratio'], @@ -123,12 +129,11 @@ print (txtstr) a=fig.add_subplot(2,3,3) # these are matplotlib.patch.Patch properties -props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) +props = dict(boxstyle='round', facecolor='wheat', alpha=0.75) # place a text box in upper left in axes coords -a.text(0.05, 0.95, txtstr, transform=a.transAxes, fontsize=14, +a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=12, verticalalignment='top', bbox=props) -imgplot = plt.imshow(nml #, cmap="gray" - ) +imgplot = plt.imshow(nml, cmap="gray") a=fig.add_subplot(2,3,6) @@ -137,8 +142,7 @@ 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, 'nml - u0', transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) -imgplot = plt.imshow(nml - u0 #, cmap="gray" - ) +imgplot = plt.imshow((nml - u0)**2, cmap="gray") plt.show() -
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