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
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkSampleMeanShiftClusteringFilterTest.cxx,v $
Language: C++
Date: $Date: 2005-02-08 03:18:41 $
Version: $Revision: 1.5 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#include "itkImageFileReader.h"
#include "itkImageRegionIterator.h"
#include "itkScalarImageToListAdaptor.h"
#include "itkKdTree.h"
#include "itkKdTreeGenerator.h"
#include "itkMeanShiftModeCacheMethod.h"
#include "itkHypersphereKernelMeanShiftModeSeeker.h"
#include "itkSampleMeanShiftBlurringFilter.h"
#include "itkSampleMeanShiftClusteringFilter.h"
#include "itkImageFileWriter.h"
int itkSampleMeanShiftClusteringFilterTest(int argc, char* argv[] )
{
std::cout << "SampleMeanShiftClusteringFilter Test \n \n";
if (argc < 2)
{
std::cout << "ERROR: data file name argument missing."
<< std::endl ;
return EXIT_FAILURE;
}
bool saveClusteredImage = false ;
typedef unsigned char PixelType ;
typedef itk::Image< PixelType, 2 > ImageType ;
typedef itk::ImageFileReader< ImageType > ImageReaderType ;
ImageReaderType::Pointer imageReader = ImageReaderType::New() ;
imageReader->SetFileName( argv[1] ) ;
imageReader->Update() ;
ImageType::Pointer image = imageReader->GetOutput() ;
typedef itk::Statistics::ScalarImageToListAdaptor< ImageType >
ListSampleType ;
ListSampleType::Pointer listSample =
ListSampleType::New() ;
listSample->SetImage( image ) ;
typedef itk::Statistics::KdTreeGenerator< ListSampleType >
TreeGeneratorType ;
TreeGeneratorType::Pointer treeGenerator = TreeGeneratorType::New() ;
treeGenerator->SetSample( listSample ) ;
treeGenerator->SetBucketSize( 200 ) ;
treeGenerator->Update() ;
typedef TreeGeneratorType::KdTreeType TreeType ;
TreeType::Pointer tree = treeGenerator->GetOutput() ;
typedef itk::Statistics::HypersphereKernelMeanShiftModeSeeker<
TreeType > ModeSeekerType ;
ModeSeekerType::Pointer modeSeeker = ModeSeekerType::New() ;
modeSeeker->SetInputSample( tree ) ;
// modeSeeker->SetInputSample( listSample ) ;
modeSeeker->SetSearchRadius( 4.0 ) ;
typedef itk::Statistics::MeanShiftModeCacheMethod< TreeType::MeasurementVectorType > CacheMethodType ;
CacheMethodType::Pointer cacheMethod = CacheMethodType::New() ;
cacheMethod->SetMaximumEntries(255) ;
cacheMethod->SetMaximumConsecutiveFailures(100) ;
cacheMethod->SetHitRatioThreshold( 0.5 ) ;
modeSeeker->SetCacheMethod( cacheMethod.GetPointer() ) ;
typedef itk::Statistics::SampleMeanShiftBlurringFilter< TreeType >
FilterType ;
FilterType::Pointer filter = FilterType::New() ;
filter->SetInputSample( tree ) ;
filter->SetMeanShiftModeSeeker( modeSeeker ) ;
try
{
filter->Update() ;
}
catch ( ... )
{
std::cout << "Test failed. - blurring proces" << std::endl;
return EXIT_FAILURE;
}
std::cout << "Cache statistics: " << std::endl ;
cacheMethod->Print(std::cout) ;
typedef ImageType OutputImageType ;
OutputImageType::Pointer outputImage = OutputImageType::New() ;
outputImage->SetRegions( image->GetLargestPossibleRegion() ) ;
outputImage->Allocate() ;
typedef itk::ImageRegionIterator< OutputImageType > ImageIteratorType ;
ImageIteratorType io_iter( outputImage,
outputImage->GetLargestPossibleRegion() ) ;
io_iter.GoToBegin() ;
FilterType::OutputType::Pointer output = filter->GetOutput() ;
FilterType::OutputType::Iterator fo_iter = output->Begin() ;
FilterType::OutputType::Iterator fo_end = output->End() ;
while ( fo_iter != fo_end )
{
io_iter.Set( (PixelType) fo_iter.GetMeasurementVector()[0]) ;
++fo_iter ;
++io_iter ;
}
ListSampleType::Pointer listSample2 = ListSampleType::New() ;
listSample2->SetImage( outputImage ) ;
TreeGeneratorType::Pointer treeGenerator2 = TreeGeneratorType::New() ;
treeGenerator2->SetSample( listSample2 ) ;
treeGenerator2->SetBucketSize( 200 ) ;
treeGenerator2->Update() ;
typedef itk::Statistics::SampleMeanShiftClusteringFilter< TreeType >
ClusteringMethodType ;
ClusteringMethodType::Pointer clusteringMethod =
ClusteringMethodType::New() ;
clusteringMethod->SetInputSample( treeGenerator2->GetOutput() ) ;
clusteringMethod->SetThreshold( 0.5 ) ;
clusteringMethod->SetMinimumClusterSize( 16 ) ;
clusteringMethod->DebugOn() ;
try
{
clusteringMethod->Update() ;
}
catch ( ... )
{
std::cout << "Test failed. - clustering proces" << std::endl;
return EXIT_FAILURE;
}
if ( saveClusteredImage )
{
OutputImageType::Pointer clusterMap = OutputImageType::New() ;
clusterMap->SetRegions( image->GetLargestPossibleRegion() ) ;
clusterMap->Allocate() ;
ImageIteratorType m_iter( clusterMap,
clusterMap->GetLargestPossibleRegion() ) ;
m_iter.GoToBegin() ;
ClusteringMethodType::ClusterLabelsType clusterLabels =
clusteringMethod->GetOutput() ;
ClusteringMethodType::ClusterLabelsType::iterator co_iter =
clusterLabels.begin() ;
while ( co_iter != clusterLabels.end() )
{
m_iter.Set( (PixelType) *co_iter ) ;
++co_iter ;
++m_iter ;
}
typedef itk::ImageFileWriter< OutputImageType > ImageWriterType ;
ImageWriterType::Pointer map_writer = ImageWriterType::New() ;
map_writer->SetFileName("clustered_sf4.png") ;
map_writer->SetInput( clusterMap ) ;
map_writer->Update() ;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
|
