diff options
Diffstat (limited to 'Wrappers')
| -rw-r--r-- | Wrappers/Python/demos/demo_cpu_regularisers.py | 2 | ||||
| -rw-r--r-- | Wrappers/Python/test/run_test.py | 102 |
2 files changed, 103 insertions, 1 deletions
diff --git a/Wrappers/Python/demos/demo_cpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_regularisers.py index 487bac7..50beee8 100644 --- a/Wrappers/Python/demos/demo_cpu_regularisers.py +++ b/Wrappers/Python/demos/demo_cpu_regularisers.py @@ -31,7 +31,7 @@ def printParametersToString(pars): filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif") # read image -Im = plt.imread(filename) +Im = plt.imread(filename) Im = np.asarray(Im, dtype='float32') Im = Im/255 diff --git a/Wrappers/Python/test/run_test.py b/Wrappers/Python/test/run_test.py new file mode 100644 index 0000000..883cdf2 --- /dev/null +++ b/Wrappers/Python/test/run_test.py @@ -0,0 +1,102 @@ +import unittest +import numpy as np +import os +from ccpi.filters.regularisers import ROF_TV, FGP_TV +from qualitymetrics import rmse +import matplotlib.pyplot as plt + +class TestRegularisers(unittest.TestCase): + def __init__(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 + self.u0 = Im + self.Im = Im + self.tolerance = 0.00001 + self.rms_rof_exp = 0.01 #expected value for ROF model + self.rms_fgp_exp = 0.01 #expected value for FGP model + + # set parameters for ROF-TV + self.pars_rof_tv = {'algorithm': ROF_TV, \ + 'input' : self.u0,\ + 'regularisation_parameter':0.04,\ + 'number_of_iterations': 50,\ + 'time_marching_parameter': 0.0025 + } + # set parameters for FGP-TV + self.pars_fgp_tv = {'algorithm' : FGP_TV, \ + 'input' : self.u0,\ + 'regularisation_parameter':0.04, \ + 'number_of_iterations' :50 ,\ + 'tolerance_constant':0.00001,\ + 'methodTV': 0 ,\ + 'nonneg': 0 ,\ + 'printingOut': 0 + } + def test_cpu_regularisers(self): + print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") + print ("_________testing ROF-TV (2D, CPU)__________") + print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") + rof_cpu = ROF_TV(self.pars_rof_tv['input'], + self.pars_rof_tv['regularisation_parameter'], + self.pars_rof_tv['number_of_iterations'], + self.pars_rof_tv['time_marching_parameter'],'cpu') + rms_rof = rmse(self.Im, rof_cpu) + # now compare obtained rms with the expected value + 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(self.pars_fgp_tv['input'], + self.pars_fgp_tv['regularisation_parameter'], + self.pars_fgp_tv['number_of_iterations'], + self.pars_fgp_tv['tolerance_constant'], + self.pars_fgp_tv['methodTV'], + self.pars_fgp_tv['nonneg'], + self.pars_fgp_tv['printingOut'],'cpu') + rms_fgp = rmse(self.Im, fgp_cpu) + # now compare obtained rms with the expected value + if abs(rms_fgp-self.rms_fgp_exp) > self.tolerance: + raise TypeError('FGP-TV (2D, CPU) test FAILED') + else: + print ("test PASSED") + def test_gpu_regularisers(self): + print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") + print ("_________testing ROF-TV (2D, GPU)__________") + print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") + rof_gpu = ROF_TV(self.pars_rof_tv['input'], + self.pars_rof_tv['regularisation_parameter'], + self.pars_rof_tv['number_of_iterations'], + self.pars_rof_tv['time_marching_parameter'],'gpu') + rms_rof = rmse(self.Im, rof_gpu) + # now compare obtained rms with the expected value + 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(self.pars_fgp_tv['input'], + self.pars_fgp_tv['regularisation_parameter'], + self.pars_fgp_tv['number_of_iterations'], + self.pars_fgp_tv['tolerance_constant'], + self.pars_fgp_tv['methodTV'], + self.pars_fgp_tv['nonneg'], + self.pars_fgp_tv['printingOut'],'gpu') + rms_fgp = rmse(self.Im, fgp_gpu) + if abs(rms_fgp-self.rms_fgp_exp) > self.tolerance: + raise TypeError('FGP-TV (2D, GPU) test FAILED') + else: + print ("test PASSED") + # now compare obtained rms with the expected value + self.assertLess(...) +if __name__ == "__main__": + unittest.main()
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