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
|
/*=========================================================================
*
* 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 "itkLabelStatisticsImageFilter.h"
#include "itkImageFileReader.h"
#include "itkSimpleFilterWatcher.h"
#include "itkTestingMacros.h"
int
itkLabelStatisticsImageFilterTest(int argc, char * argv[])
{
std::cout << "itkLabelStatisticsImageFilterTest Start" << std::endl;
if (argc < 4)
{
std::cerr << "Missing Arguments" << std::endl;
std::cerr << "Usage: " << std::endl;
std::cerr << itkNameOfTestExecutableMacro(argv) << " inputImage labeledImage useHistograms [numberOfStreamDivision]"
<< std::endl;
return EXIT_FAILURE;
}
using ImageType = itk::Image<unsigned char, 2>;
using ReaderType = itk::ImageFileReader<ImageType>;
auto reader1 = ReaderType::New();
auto reader2 = ReaderType::New();
reader1->SetFileName(argv[1]);
reader2->SetFileName(argv[2]);
unsigned int numberOfStreamDivisions = 1;
if (argc > 4)
{
numberOfStreamDivisions = std::max(std::stoi(argv[4]), 1);
}
using FilterType = itk::LabelStatisticsImageFilter<ImageType, ImageType>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, LabelStatisticsImageFilter, ImageSink);
itk::SimpleFilterWatcher filterWatch(filter);
auto useHistograms = static_cast<bool>(std::stoi(argv[3]));
ITK_TEST_SET_GET_BOOLEAN(filter, UseHistograms, useHistograms);
filter->SetNumberOfStreamDivisions(numberOfStreamDivisions);
ITK_TEST_SET_GET_VALUE(numberOfStreamDivisions, filter->GetNumberOfStreamDivisions());
filter->SetInput(reader1->GetOutput());
filter->SetLabelInput(reader2->GetOutput());
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught ! " << std::endl;
std::cerr << excp << std::endl;
return EXIT_FAILURE;
}
const unsigned int numberOfObjects = filter->GetNumberOfObjects();
const unsigned int numberOfLabels = filter->GetNumberOfLabels();
using RealType = FilterType::RealType;
using BoundingBoxType = FilterType::BoundingBoxType;
using RegionType = FilterType::RegionType;
using LabelPixelType = FilterType::LabelPixelType;
LabelPixelType labelValue;
std::cout << "There are " << numberOfLabels << " labels" << std::endl;
std::cout << "There are " << numberOfObjects << " objects" << std::endl;
unsigned int labelCount = 0;
// Try to validate that the numberOfLabels in the ValidLabelList is
// equal to the number of labels reported
for (auto vIt = filter->GetValidLabelValues().begin(); vIt != filter->GetValidLabelValues().end(); ++vIt)
{
if (filter->HasLabel(*vIt))
{
++labelCount;
}
}
if (labelCount != numberOfLabels)
{
std::cerr << "Valid Labels Mismatch found!" << std::endl;
std::cerr << labelCount << " != " << numberOfLabels << std::endl;
return EXIT_FAILURE;
}
// Try two labels: one that exists and one that does not
for (int i = 0; i < 2; ++i)
{
// Find an existing label
if (i == 0)
{
labelValue = 0;
while (!filter->HasLabel(labelValue))
{
labelValue++;
}
std::cout << "Label Statistics for label "
<< static_cast<itk::NumericTraits<LabelPixelType>::PrintType>(labelValue) << " which exists"
<< std::endl;
}
// Find a non existent label
if (i != 0)
{
labelValue = 0;
while (filter->HasLabel(labelValue))
{
labelValue++;
}
std::cout << "Label Statistics for label "
<< static_cast<itk::NumericTraits<LabelPixelType>::PrintType>(labelValue) << " which does not exist"
<< std::endl;
}
const RealType min = filter->GetMinimum(labelValue);
const RealType max = filter->GetMaximum(labelValue);
const RealType median = filter->GetMedian(labelValue);
const RealType mean = filter->GetMean(labelValue);
const RealType sigma = filter->GetSigma(labelValue);
const RealType variance = filter->GetVariance(labelValue);
const RealType sum = filter->GetSum(labelValue);
const BoundingBoxType box = filter->GetBoundingBox(labelValue);
const RegionType region = filter->GetRegion(labelValue);
std::cout << "Minimum = " << min << std::endl;
std::cout << "Maximum = " << max << std::endl;
std::cout << "Median = " << median << std::endl;
std::cout << "Mean = " << mean << std::endl;
std::cout << "Sigma = " << sigma << std::endl;
std::cout << "Variance = " << variance << std::endl;
std::cout << "Sum = " << sum << std::endl;
std::cout << "Region = " << region << std::endl;
auto itr = box.begin();
while (itr != box.end())
{
std::cout << "Index = " << *itr << std::endl;
++itr;
}
}
return EXIT_SUCCESS;
}
|
