File: itkFFTConvolutionImageFilterTest.cxx

package info (click to toggle)
insighttoolkit5 5.4.3-5
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 704,384 kB
  • sloc: cpp: 783,592; ansic: 628,724; xml: 44,704; fortran: 34,250; python: 22,874; sh: 4,078; pascal: 2,636; lisp: 2,158; makefile: 464; yacc: 328; asm: 205; perl: 203; lex: 146; tcl: 132; javascript: 98; csh: 81
file content (239 lines) | stat: -rw-r--r-- 8,568 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/

#include "itkChangeInformationImageFilter.h"
#include "itkConstantBoundaryCondition.h"
#include "itkFFTConvolutionImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkPeriodicBoundaryCondition.h"
#include "itkSimpleFilterWatcher.h"
#include "itkTestingMacros.h"
#include "itkZeroFluxNeumannBoundaryCondition.h"

#include "itkObjectFactoryBase.h"
#include "itkVnlRealToHalfHermitianForwardFFTImageFilter.h"
#include "itkVnlHalfHermitianToRealInverseFFTImageFilter.h"
#if defined(ITK_USE_FFTWD) || defined(ITK_USE_FFTWF)
#  include "itkFFTWRealToHalfHermitianForwardFFTImageFilter.h"
#  include "itkFFTWHalfHermitianToRealInverseFFTImageFilter.h"
#endif

int
itkFFTConvolutionImageFilterTest(int argc, char * argv[])
{

  if (argc < 4)
  {
    std::cout << "Usage: " << itkNameOfTestExecutableMacro(argv) << " inputImage "
              << "kernelImage "
              << "outputImage "
              << "[sizeGreatestPrimeFactor] "
              << "[normalizeImage] "
              << "[outputRegionMode] "
              << "[boundaryCondition] " << std::endl;
    return EXIT_FAILURE;
  }

  constexpr int ImageDimension = 2;

  using PixelType = float;
  using ImageType = itk::Image<PixelType, ImageDimension>;
  using ReaderType = itk::ImageFileReader<ImageType>;

  auto reader1 = ReaderType::New();
  reader1->SetFileName(argv[1]);

  ITK_TRY_EXPECT_NO_EXCEPTION(reader1->Update());

  auto reader2 = ReaderType::New();
  reader2->SetFileName(argv[2]);

  ITK_TRY_EXPECT_NO_EXCEPTION(reader2->Update());

  using ConvolutionFilterType = itk::FFTConvolutionImageFilter<ImageType>;
  auto convoluter = ConvolutionFilterType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(convoluter, FFTConvolutionImageFilter, ConvolutionImageFilterBase);

  // Test empty image exception
  auto emptyImage = ImageType::New();
  convoluter->SetInput(emptyImage);
  try
  {
    convoluter->Update();
    std::cerr << "Failed to throw expected exception" << std::endl;
    return EXIT_FAILURE;
  }
  catch (const itk::ExceptionObject & excp)
  {
    std::cout << excp << std::endl;
    std::cout << "Caught EXPECTED exception for empty image as input" << std::endl;
  }

  // Test generality of filter by changing the image index
  using ChangeInformationFilterType = itk::ChangeInformationImageFilter<ImageType>;
  auto inputChanger = ChangeInformationFilterType::New();
  inputChanger->ChangeRegionOn();
  ImageType::OffsetType inputOffset = { { -2, 3 } };
  inputChanger->SetOutputOffset(inputOffset);
  inputChanger->SetInput(reader1->GetOutput());

  convoluter->SetInput(inputChanger->GetOutput());

  // Test generality of filter by changing the kernel index
  auto kernelChanger = ChangeInformationFilterType::New();
  kernelChanger->ChangeRegionOn();
  ImageType::OffsetType kernelOffset = { { 3, -5 } };
  kernelChanger->SetOutputOffset(kernelOffset);
  kernelChanger->SetInput(reader2->GetOutput());

  convoluter->SetKernelImage(kernelChanger->GetOutput());

  if (argc >= 5)
  {
    ConvolutionFilterType::SizeValueType sizeGreatestPrimeFactor = std::stoi(argv[4]);
    if (!itk::Math::IsPrime(sizeGreatestPrimeFactor))
    {
      std::cerr << "A prime number is expected for the greatest prime factor size!" << std::endl;
      return EXIT_FAILURE;
    }
    convoluter->SetSizeGreatestPrimeFactor(sizeGreatestPrimeFactor);
    ITK_TEST_SET_GET_VALUE(sizeGreatestPrimeFactor, convoluter->GetSizeGreatestPrimeFactor());
  }

  if (argc >= 6)
  {
    auto normalize = static_cast<bool>(std::stoi(argv[5]));
    convoluter->SetNormalize(normalize);
    ITK_TEST_SET_GET_VALUE(normalize, convoluter->GetNormalize());

    if (normalize)
    {
      convoluter->NormalizeOn();
      ITK_TEST_EXPECT_TRUE(convoluter->GetNormalize());
    }
    else
    {
      convoluter->NormalizeOff();
      ITK_TEST_EXPECT_TRUE(!convoluter->GetNormalize());
    }
  }

  if (argc >= 7)
  {
    std::string outputRegionMode(argv[6]);
    if (outputRegionMode == "SAME")
    {
      convoluter->SetOutputRegionMode(itk::ConvolutionImageFilterBaseEnums::ConvolutionImageFilterOutputRegion::SAME);
      ITK_TEST_SET_GET_VALUE(itk::ConvolutionImageFilterBaseEnums::ConvolutionImageFilterOutputRegion::SAME,
                             convoluter->GetOutputRegionMode());
    }
    else if (outputRegionMode == "VALID")
    {
      convoluter->SetOutputRegionMode(itk::ConvolutionImageFilterBaseEnums::ConvolutionImageFilterOutputRegion::VALID);
      ITK_TEST_SET_GET_VALUE(itk::ConvolutionImageFilterBaseEnums::ConvolutionImageFilterOutputRegion::VALID,
                             convoluter->GetOutputRegionMode());
    }
    else
    {
      std::cerr << "Invalid OutputRegionMode '" << outputRegionMode << "'." << std::endl;
      std::cerr << "Valid values are SAME or VALID." << std::endl;
      return EXIT_FAILURE;
    }

    if (outputRegionMode == "SAME")
    {
      convoluter->SetOutputRegionModeToSame();
      ITK_TEST_SET_GET_VALUE(ConvolutionFilterType::OutputRegionModeEnum::SAME, convoluter->GetOutputRegionMode());
    }
    else
    {
      convoluter->SetOutputRegionModeToValid();
      ITK_TEST_SET_GET_VALUE(ConvolutionFilterType::OutputRegionModeEnum::VALID, convoluter->GetOutputRegionMode());
    }
  }

  itk::ConstantBoundaryCondition<ImageType> constantBoundaryCondition;
  convoluter->SetBoundaryCondition(&constantBoundaryCondition);
  itk::PeriodicBoundaryCondition<ImageType>        periodicBoundaryCondition;
  itk::ZeroFluxNeumannBoundaryCondition<ImageType> zeroFluxNeumannBoundaryCondition;
  if (argc >= 7)
  {
    std::string boundaryCondition(argv[7]);
    if (boundaryCondition == "CONSTANT")
    {
      convoluter->SetBoundaryCondition(&constantBoundaryCondition);
      ITK_TEST_SET_GET_VALUE(&constantBoundaryCondition, convoluter->GetBoundaryCondition());
    }
    else if (boundaryCondition == "PERIODIC")
    {
      convoluter->SetBoundaryCondition(&periodicBoundaryCondition);
      ITK_TEST_SET_GET_VALUE(&periodicBoundaryCondition, convoluter->GetBoundaryCondition());
    }
    else if (boundaryCondition == "ZEROFLUXNEUMANN")
    {
      convoluter->SetBoundaryCondition(&zeroFluxNeumannBoundaryCondition);
      ITK_TEST_SET_GET_VALUE(&zeroFluxNeumannBoundaryCondition, convoluter->GetBoundaryCondition());
    }
    else
    {
      std::cerr << "Invalid BoundaryCondition '" << boundaryCondition << "'." << std::endl;
      std::cerr << "Valid values are CONSTANT, PERIODIC or ZEROFLUXNEUMANN." << std::endl;
      return EXIT_FAILURE;
    }
  }

  itk::SimpleFilterWatcher watcher(convoluter, "filter");

  ITK_TRY_EXPECT_NO_EXCEPTION(convoluter->Update());

  using WriterType = itk::ImageFileWriter<ImageType>;
  auto writer = WriterType::New();
  writer->SetFileName(argv[3]);
  writer->SetInput(convoluter->GetOutput());

  ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());


  // Test VALID output region mode with kernel that is larger than
  // the input image. Should result in a zero-size valid region.
  auto                  largeKernel = ImageType::New();
  ImageType::RegionType kernelRegion(reader1->GetOutput()->GetLargestPossibleRegion().GetSize());
  kernelRegion.PadByRadius(5);

  largeKernel->SetRegions(kernelRegion);
  largeKernel->Allocate();
  convoluter->SetOutputRegionModeToValid();
  convoluter->SetInput(reader1->GetOutput());
  convoluter->SetKernelImage(largeKernel);

  ITK_TRY_EXPECT_EXCEPTION(convoluter->Update());

  // Test for invalid request region.
  ImageType::IndexType invalidIndex;
  invalidIndex.Fill(1000);
  ImageType::SizeType invalidSize;
  invalidSize.Fill(1000);
  ImageType::RegionType invalidRequestRegion(invalidIndex, invalidSize);
  convoluter->GetOutput()->SetRequestedRegion(invalidRequestRegion);

  ITK_TRY_EXPECT_EXCEPTION(convoluter->Update());

  return EXIT_SUCCESS;
}