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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2019-11-28 23:01:03 +0000 |
|---|---|---|
| committer | Daniil Kazantsev <dkazanc@hotmail.com> | 2019-11-28 23:01:03 +0000 |
| commit | c65291e6b987283e4767a8ad2bd2d2433ca3782e (patch) | |
| tree | c3b660c9b2151f2ff1a12352daf73dfc90d1c3a3 /test | |
| parent | cdef6a981f1772ed04fe44bbe2b8251983a4ba7a (diff) | |
| download | regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.tar.gz regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.tar.bz2 regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.tar.xz regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.zip | |
all work completed on gpu version of pdtv
Diffstat (limited to 'test')
| -rw-r--r-- | test/test_CPU_regularisers.py | 11 | ||||
| -rwxr-xr-x | test/test_run_test.py | 88 |
2 files changed, 98 insertions, 1 deletions
diff --git a/test/test_CPU_regularisers.py b/test/test_CPU_regularisers.py index 95e2a3f..266ca8a 100644 --- a/test/test_CPU_regularisers.py +++ b/test/test_CPU_regularisers.py @@ -3,7 +3,7 @@ import unittest import os #import timeit import numpy as np -from ccpi.filters.regularisers import FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, Diff4th, ROF_TV +from ccpi.filters.regularisers import FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, Diff4th, ROF_TV, PD_TV from testroutines import BinReader, rmse ############################################################################### @@ -39,6 +39,15 @@ class TestRegularisers(unittest.TestCase): self.assertAlmostEqual(rms,0.02,delta=0.01) + def test_PD_TV_CPU(self): + Im,input,ref = self.getPars() + + pd_cpu,info = PD_TV(input, 0.02, 300, 0.0, 0, 0, 8, 0.0025, 'cpu'); + + rms = rmse(Im, pd_cpu) + + self.assertAlmostEqual(rms,0.02,delta=0.01) + def test_TV_ROF_CPU(self): # set parameters Im, input,ref = self.getPars() diff --git a/test/test_run_test.py b/test/test_run_test.py index e693e03..1707aec 100755 --- a/test/test_run_test.py +++ b/test/test_run_test.py @@ -164,6 +164,94 @@ class TestRegularisers(unittest.TestCase): self.assertLessEqual(diff_im.sum() , 1)
+ def test_PD_TV_CPU_vs_GPU(self):
+ print(__name__)
+ #filename = os.path.join("test","lena_gray_512.tif")
+ #plt = TiffReader()
+ filename = os.path.join("test","test_imageLena.bin")
+ plt = BinReader()
+ # read image
+ Im = plt.imread(filename)
+ Im = np.asarray(Im, dtype='float32')
+
+ Im = Im/255
+ perc = 0.05
+ u0 = Im + np.random.normal(loc = 0 ,
+ scale = perc * Im ,
+ size = np.shape(Im))
+ u_ref = Im + np.random.normal(loc = 0 ,
+ scale = 0.01 * Im ,
+ size = np.shape(Im))
+
+ # map the u0 u0->u0>0
+ # f = np.frompyfunc(lambda x: 0 if x < 0 else x, 1,1)
+ u0 = u0.astype('float32')
+ u_ref = u_ref.astype('float32')
+
+ print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+ print ("____________PD-TV bench___________________")
+ print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+
+ pars = {'algorithm' : PD_TV, \
+ 'input' : u0,\
+ 'regularisation_parameter':0.02, \
+ 'number_of_iterations' :1500 ,\
+ 'tolerance_constant':0.0,\
+ 'methodTV': 0 ,\
+ 'nonneg': 0,
+ 'lipschitz_const' : 8,
+ 'tau' : 0.0025}
+
+ print ("#############PD TV CPU####################")
+ start_time = timeit.default_timer()
+ (pd_cpu,info_vec_cpu) = PD_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['nonneg'],
+ pars['lipschitz_const'],
+ pars['tau'],'cpu')
+
+ rms = rmse(Im, pd_cpu)
+ pars['rmse'] = rms
+
+ txtstr = printParametersToString(pars)
+ txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+ print (txtstr)
+
+ print ("##############PD TV GPU##################")
+ start_time = timeit.default_timer()
+ try:
+ (pd_gpu,info_vec_gpu) = PD_TV(pars['input'],
+ pars['regularisation_parameter'],
+ pars['number_of_iterations'],
+ pars['tolerance_constant'],
+ pars['methodTV'],
+ pars['nonneg'],
+ pars['lipschitz_const'],
+ pars['tau'],'gpu')
+
+ except ValueError as ve:
+ self.skipTest("Results not comparable. GPU computing error.")
+
+ rms = rmse(Im, pd_gpu)
+ pars['rmse'] = rms
+ pars['algorithm'] = PD_TV
+ txtstr = printParametersToString(pars)
+ txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+ print (txtstr)
+
+ print ("--------Compare the results--------")
+ tolerance = 1e-05
+ diff_im = np.zeros(np.shape(pd_cpu))
+ diff_im = abs(pd_cpu - pd_gpu)
+ diff_im[diff_im > tolerance] = 1
+
+ self.assertLessEqual(diff_im.sum() , 1)
+
+
def test_SB_TV_CPU_vs_GPU(self):
print(__name__)
#filename = os.path.join("test","lena_gray_512.tif")
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