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
|
/*=========================================================================
*
* 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 <iostream>
#include "itkRescaleIntensityImageFilter.h"
#include "itkRandomImageSource.h"
#include "itkTestingMacros.h"
#include "itkUnaryFunctorImageFilter.h"
int
itkRescaleIntensityImageFilterTest(int, char *[])
{
std::cout << "itkRescaleIntensityImageFilterTest Start" << std::endl;
// Define the dimension of the images
constexpr unsigned int ImageDimension = 3;
// Declare the pixel types of the images
using PixelType = float;
// Declare the types of the images
using TestInputImage = itk::Image<PixelType, ImageDimension>;
using TestOutputImage = itk::Image<PixelType, ImageDimension>;
TestInputImage::RegionType region;
TestInputImage::SizeType size;
size.Fill(64);
TestInputImage::IndexType index;
index.Fill(0);
region.SetIndex(index);
region.SetSize(size);
using FilterType = itk::RescaleIntensityImageFilter<TestInputImage, TestOutputImage>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, RescaleIntensityImageFilter, UnaryFunctorImageFilter);
// Now generate a real image
using SourceType = itk::RandomImageSource<TestInputImage>;
auto source = SourceType::New();
TestInputImage::SizeValueType randomSize[3] = { 17, 8, 20 };
// Set up source
source->SetSize(randomSize);
double minValue = -128.0;
double maxValue = 127.0;
source->SetMin(static_cast<TestInputImage::PixelType>(minValue));
source->SetMax(static_cast<TestInputImage::PixelType>(maxValue));
filter->SetFunctor(filter->GetFunctor());
filter->SetInput(source->GetOutput());
const double desiredMinimum = -1.0;
constexpr double desiredMaximum = 1.0;
filter->SetOutputMinimum(desiredMinimum);
ITK_TEST_SET_GET_VALUE(desiredMinimum, filter->GetOutputMinimum());
filter->SetOutputMaximum(desiredMaximum);
ITK_TEST_SET_GET_VALUE(desiredMaximum, filter->GetOutputMaximum());
ITK_TRY_EXPECT_NO_EXCEPTION(filter->UpdateLargestPossibleRegion());
using CalculatorType = itk::MinimumMaximumImageCalculator<TestOutputImage>;
auto calculator = CalculatorType::New();
calculator->SetImage(filter->GetOutput());
calculator->Compute();
const double tolerance = 1e-7;
const double obtainedMinimum = calculator->GetMinimum();
const double obtainedMaximum = calculator->GetMaximum();
if (!itk::Math::FloatAlmostEqual(obtainedMinimum, desiredMinimum, 10, tolerance))
{
std::cerr << "Error in minimum" << std::endl;
std::cerr << "Expected minimum = " << desiredMinimum << std::endl;
std::cerr << "Obtained minimum = " << obtainedMinimum << std::endl;
return EXIT_FAILURE;
}
if (!itk::Math::FloatAlmostEqual(obtainedMaximum, desiredMaximum, 10, tolerance))
{
std::cerr << "Error in minimum" << std::endl;
std::cerr << "Expected minimum = " << desiredMaximum << std::endl;
std::cerr << "Obtained minimum = " << obtainedMaximum << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
|
