From 58f5ce047b063d53906e38047b6ae744ccdbd4eb Mon Sep 17 00:00:00 2001
From: Daniil Kazantsev <dkazanc@hotmail.com>
Date: Thu, 12 Apr 2018 10:25:21 +0100
Subject: dTV method added
---
.../Python/test/__pycache__/metrics.cpython-35.pyc | Bin 823 -> 0 bytes
Wrappers/Python/test/run_test.py | 149 ---------------------
2 files changed, 149 deletions(-)
delete mode 100644 Wrappers/Python/test/__pycache__/metrics.cpython-35.pyc
delete mode 100644 Wrappers/Python/test/run_test.py
(limited to 'Wrappers/Python/test')
diff --git a/Wrappers/Python/test/__pycache__/metrics.cpython-35.pyc b/Wrappers/Python/test/__pycache__/metrics.cpython-35.pyc
deleted file mode 100644
index 2196a53..0000000
Binary files a/Wrappers/Python/test/__pycache__/metrics.cpython-35.pyc and /dev/null differ
diff --git a/Wrappers/Python/test/run_test.py b/Wrappers/Python/test/run_test.py
deleted file mode 100644
index 04bbd40..0000000
--- a/Wrappers/Python/test/run_test.py
+++ /dev/null
@@ -1,149 +0,0 @@
-import unittest
-import numpy as np
-import os
-from ccpi.filters.regularisers import ROF_TV, FGP_TV
-import matplotlib.pyplot as plt
-
-def rmse(im1, im2):
- rmse = np.sqrt(np.sum((im1 - im2) ** 2) / float(im1.size))
- return rmse
-
-class TestRegularisers(unittest.TestCase):
-
- def setUp(self):
- pass
-
- def test_cpu_regularisers(self):
- filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif")
-
- # read noiseless image
- Im = plt.imread(filename)
- Im = np.asarray(Im, dtype='float32')
-
- Im = Im/255
- tolerance = 1e-05
- rms_rof_exp = 0.006812507 #expected value for ROF model
- rms_fgp_exp = 0.019152347 #expected value for FGP model
-
- # set parameters for ROF-TV
- pars_rof_tv = {'algorithm': ROF_TV, \
- 'input' : Im,\
- 'regularisation_parameter':0.04,\
- 'number_of_iterations': 50,\
- 'time_marching_parameter': 0.0025
- }
- # set parameters for FGP-TV
- pars_fgp_tv = {'algorithm' : FGP_TV, \
- 'input' : Im,\
- 'regularisation_parameter':0.04, \
- 'number_of_iterations' :50 ,\
- 'tolerance_constant':1e-08,\
- 'methodTV': 0 ,\
- 'nonneg': 0 ,\
- 'printingOut': 0
- }
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- print ("_________testing ROF-TV (2D, CPU)__________")
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- res = True
- rof_cpu = ROF_TV(pars_rof_tv['input'],
- pars_rof_tv['regularisation_parameter'],
- pars_rof_tv['number_of_iterations'],
- pars_rof_tv['time_marching_parameter'],'cpu')
- rms_rof = rmse(Im, rof_cpu)
- # now compare obtained rms with the expected value
- self.assertLess(abs(rms_rof-rms_rof_exp) , tolerance)
- """
- if abs(rms_rof-self.rms_rof_exp) > self.tolerance:
- raise TypeError('ROF-TV (2D, CPU) test FAILED')
- else:
- print ("test PASSED")
- """
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- print ("_________testing FGP-TV (2D, CPU)__________")
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- fgp_cpu = FGP_TV(pars_fgp_tv['input'],
- pars_fgp_tv['regularisation_parameter'],
- pars_fgp_tv['number_of_iterations'],
- pars_fgp_tv['tolerance_constant'],
- pars_fgp_tv['methodTV'],
- pars_fgp_tv['nonneg'],
- pars_fgp_tv['printingOut'],'cpu')
- rms_fgp = rmse(Im, fgp_cpu)
- # now compare obtained rms with the expected value
- self.assertLess(abs(rms_fgp-rms_fgp_exp) , tolerance)
- """
- if abs(rms_fgp-self.rms_fgp_exp) > self.tolerance:
- raise TypeError('FGP-TV (2D, CPU) test FAILED')
- else:
- print ("test PASSED")
- """
- self.assertTrue(res)
- def test_gpu_regularisers(self):
- filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif")
-
- # read noiseless image
- Im = plt.imread(filename)
- Im = np.asarray(Im, dtype='float32')
-
- Im = Im/255
- tolerance = 1e-05
- rms_rof_exp = 0.006812507 #expected value for ROF model
- rms_fgp_exp = 0.019152347 #expected value for FGP model
-
- # set parameters for ROF-TV
- pars_rof_tv = {'algorithm': ROF_TV, \
- 'input' : Im,\
- 'regularisation_parameter':0.04,\
- 'number_of_iterations': 50,\
- 'time_marching_parameter': 0.0025
- }
- # set parameters for FGP-TV
- pars_fgp_tv = {'algorithm' : FGP_TV, \
- 'input' : Im,\
- 'regularisation_parameter':0.04, \
- 'number_of_iterations' :50 ,\
- 'tolerance_constant':1e-08,\
- 'methodTV': 0 ,\
- 'nonneg': 0 ,\
- 'printingOut': 0
- }
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- print ("_________testing ROF-TV (2D, GPU)__________")
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- res = True
- rof_gpu = ROF_TV(pars_rof_tv['input'],
- pars_rof_tv['regularisation_parameter'],
- pars_rof_tv['number_of_iterations'],
- pars_rof_tv['time_marching_parameter'],'gpu')
- rms_rof = rmse(Im, rof_gpu)
- # now compare obtained rms with the expected value
- self.assertLess(abs(rms_rof-rms_rof_exp) , tolerance)
- """
- if abs(rms_rof-self.rms_rof_exp) > self.tolerance:
- raise TypeError('ROF-TV (2D, GPU) test FAILED')
- else:
- print ("test PASSED")
- """
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- print ("_________testing FGP-TV (2D, GPU)__________")
- print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
- fgp_gpu = FGP_TV(pars_fgp_tv['input'],
- pars_fgp_tv['regularisation_parameter'],
- pars_fgp_tv['number_of_iterations'],
- pars_fgp_tv['tolerance_constant'],
- pars_fgp_tv['methodTV'],
- pars_fgp_tv['nonneg'],
- pars_fgp_tv['printingOut'],'gpu')
- rms_fgp = rmse(Im, fgp_gpu)
- # now compare obtained rms with the expected value
- self.assertLess(abs(rms_fgp-rms_fgp_exp) , tolerance)
- """
- if abs(rms_fgp-self.rms_fgp_exp) > self.tolerance:
- raise TypeError('FGP-TV (2D, GPU) test FAILED')
- else:
- print ("test PASSED")
- """
- self.assertTrue(res)
-if __name__ == '__main__':
- unittest.main()
\ No newline at end of file
--
cgit v1.2.3