diff options
-rwxr-xr-x | Core/regularizers_GPU/TV_ROF/TV_ROF_GPU.cu | 2 | ||||
-rw-r--r-- | Wrappers/Python/demo/test_cpu_regularizers.py | 10 | ||||
-rw-r--r-- | Wrappers/Python/src/gpu_regularizers.pyx | 2 | ||||
-rw-r--r-- | Wrappers/Python/test/test_cpu_vs_gpu_regularizers.py | 123 | ||||
-rw-r--r-- | Wrappers/Python/test/test_gpu_regularizers.py | 16 |
5 files changed, 138 insertions, 15 deletions
diff --git a/Core/regularizers_GPU/TV_ROF/TV_ROF_GPU.cu b/Core/regularizers_GPU/TV_ROF/TV_ROF_GPU.cu index 73a52e1..897b5d0 100755 --- a/Core/regularizers_GPU/TV_ROF/TV_ROF_GPU.cu +++ b/Core/regularizers_GPU/TV_ROF/TV_ROF_GPU.cu @@ -312,7 +312,7 @@ extern "C" void TV_ROF_GPU_kernel(float* Input, float* Output, int N, int M, int int dev = 0; CHECK(cudaSetDevice(dev)); - float *d_input, *d_update, *d_D1, *d_D2; + float *d_input, *d_update, *d_D1, *d_D2; CHECK(cudaMalloc((void**)&d_input,N*M*Z*sizeof(float))); CHECK(cudaMalloc((void**)&d_update,N*M*Z*sizeof(float))); diff --git a/Wrappers/Python/demo/test_cpu_regularizers.py b/Wrappers/Python/demo/test_cpu_regularizers.py index 5908c3c..d147b85 100644 --- a/Wrappers/Python/demo/test_cpu_regularizers.py +++ b/Wrappers/Python/demo/test_cpu_regularizers.py @@ -284,9 +284,9 @@ start_time = timeit.default_timer() pars = {'algorithm': ROF_TV , \ 'input' : u0,\ - 'regularization_parameter':1,\ - 'marching_step': 0.003,\ - 'number_of_iterations': 300 + 'regularization_parameter':25,\ + 'marching_step': 0.001,\ + 'number_of_iterations': 350 } rof = ROF_TV(pars['input'], pars['number_of_iterations'], @@ -307,9 +307,7 @@ 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, txtstr, transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) -imgplot = plt.imshow(tgv, cmap="gray") - - +imgplot = plt.imshow(rof, cmap="gray") plt.show() diff --git a/Wrappers/Python/src/gpu_regularizers.pyx b/Wrappers/Python/src/gpu_regularizers.pyx index fcb91cc..c724471 100644 --- a/Wrappers/Python/src/gpu_regularizers.pyx +++ b/Wrappers/Python/src/gpu_regularizers.pyx @@ -345,7 +345,7 @@ def ROFTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, # Running CUDA code here TV_ROF_GPU_kernel( &inputData[0,0], &B[0,0], - dims[0], dims[1], 0, + dims[0], dims[1], 1, iterations , time_marching_parameter, regularization_parameter); diff --git a/Wrappers/Python/test/test_cpu_vs_gpu_regularizers.py b/Wrappers/Python/test/test_cpu_vs_gpu_regularizers.py new file mode 100644 index 0000000..8c91c73 --- /dev/null +++ b/Wrappers/Python/test/test_cpu_vs_gpu_regularizers.py @@ -0,0 +1,123 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Created on Thu Feb 22 11:39:43 2018 + +Testing CPU implementation against GPU one + +@author: algol +""" + +import matplotlib.pyplot as plt +import numpy as np +import os +import timeit +from ccpi.filters.gpu_regularizers import Diff4thHajiaboli, NML, GPU_ROF_TV +from ccpi.filters.cpu_regularizers_cython import ROF_TV +############################################################################### +def printParametersToString(pars): + txt = r'' + for key, value in pars.items(): + if key== 'algorithm' : + txt += "{0} = {1}".format(key, value.__name__) + elif key == 'input': + txt += "{0} = {1}".format(key, np.shape(value)) + else: + txt += "{0} = {1}".format(key, value) + txt += '\n' + return txt +############################################################################### +def rmse(im1, im2): + a, b = im1.shape + rmse = np.sqrt(np.sum((im1 - im2) ** 2) / float(a * b)) + return rmse + +filename = os.path.join(".." , ".." , ".." , "data" ,"lena_gray_512.tif") + +# read image +Im = plt.imread(filename) +Im = np.asarray(Im, dtype='float32') + +Im = Im/255 +perc = 0.075 +u0 = Im + np.random.normal(loc = Im , + scale = perc * 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 = f(u0).astype('float32') + +## plot +fig = plt.figure(1) +plt.suptitle('Comparison of ROF-TV regularizer using CPU and GPU implementations') +a=fig.add_subplot(1,4,1) +a.set_title('Noisy Image') +imgplot = plt.imshow(u0,cmap="gray") + + +# set parameters +pars = {'algorithm': ROF_TV , \ + 'input' : u0,\ + 'regularization_parameter':12,\ + 'time_marching_parameter': 0.001,\ + 'number_of_iterations': 600 + } +print ("#################ROF TV CPU#####################") +start_time = timeit.default_timer() +rof_cpu = ROF_TV(pars['input'], + pars['number_of_iterations'], + pars['regularization_parameter'], + pars['time_marching_parameter'] + ) +#tgv = out +rms = rmse(Im, rof_cpu) +pars['rmse'] = rms + +txtstr = printParametersToString(pars) +txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time) +print (txtstr) +a=fig.add_subplot(1,4,2) + +# these are matplotlib.patch.Patch properties +props = dict(boxstyle='round', facecolor='wheat', alpha=0.75) +# place a text box in upper left in axes coords +a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14, + verticalalignment='top', bbox=props) +imgplot = plt.imshow(rof_cpu, cmap="gray") +plt.title('{}'.format('CPU results')) + + +print ("#################ROF TV GPU#####################") +start_time = timeit.default_timer() +rof_gpu = GPU_ROF_TV(pars['input'], + pars['number_of_iterations'], + pars['time_marching_parameter'], + pars['regularization_parameter']) + +rms = rmse(Im, rof_gpu) +pars['rmse'] = rms +txtstr = printParametersToString(pars) +txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time) +print (txtstr) +a=fig.add_subplot(1,4,3) + +# these are matplotlib.patch.Patch properties +props = dict(boxstyle='round', facecolor='wheat', alpha=0.75) +# place a text box in upper left in axes coords +a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14, + verticalalignment='top', bbox=props) +imgplot = plt.imshow(rof_gpu, cmap="gray") +plt.title('{}'.format('GPU results')) + + +print ("--------Compare the results--------") +tolerance = 1e-06 +diff_im = abs(rof_cpu - rof_gpu) +diff_im[diff_im > tolerance] = 1 +a=fig.add_subplot(1,4,4) +imgplot = plt.imshow(diff_im, vmin=0, vmax=1, cmap="gray") +plt.title('{}'.format('Pixels larger threshold difference')) +if (diff_im.sum() > 1): + print ("Arrays do not match!") +else: + print ("Arrays match")
\ No newline at end of file diff --git a/Wrappers/Python/test/test_gpu_regularizers.py b/Wrappers/Python/test/test_gpu_regularizers.py index 9e37627..29f5bad 100644 --- a/Wrappers/Python/test/test_gpu_regularizers.py +++ b/Wrappers/Python/test/test_gpu_regularizers.py @@ -93,7 +93,8 @@ 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=12, verticalalignment='top', bbox=props) -imgplot = plt.imshow((d4h - u0), cmap="gray") +imgplot = plt.imshow((d4h - u0)**2, vmin=0, vmax=0.03, cmap="gray") +plt.colorbar(ticks=[0, 0.03], orientation='vertical') ## Patch Based Regul NML @@ -142,7 +143,8 @@ 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, vmin=0, vmax=0.03, cmap="gray") +plt.colorbar(ticks=[0, 0.03], orientation='vertical') @@ -152,9 +154,9 @@ start_time = timeit.default_timer() pars = { 'algorithm' : GPU_ROF_TV , \ 'input' : u0, - 'regularization_parameter': 1,\ - 'time_marching_parameter': 0.003, \ - 'number_of_iterations':300 + 'regularization_parameter': 25,\ + 'time_marching_parameter': 0.001, \ + 'number_of_iterations':350 } rof_tv = GPU_ROF_TV(pars['input'], @@ -183,6 +185,6 @@ 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, 'rof_tv - u0', transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) -imgplot = plt.imshow((rof_tv - u0), cmap="gray") - +imgplot = plt.imshow((rof_tv - u0)**2, vmin=0, vmax=0.03, cmap="gray") +plt.colorbar(ticks=[0, 0.03], orientation='vertical') plt.show() |