ITK/Examples/Broken/Statistics/ImageKmeansModelEstimator: Difference between revisions
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int main(int, char* [] ) | int main(int, char* [] ) | ||
{ | { | ||
// Create a demo image | |||
ColorImageType::Pointer image = ColorImageType::New(); | ColorImageType::Pointer image = ColorImageType::New(); | ||
CreateImage(image); | CreateImage(image); | ||
// Compute pixel clusters using KMeans | |||
typedef itk::Statistics::DistanceToCentroidMembershipFunction< itk::Vector<unsigned char,3> > MembershipFunctionType ; | typedef itk::Statistics::DistanceToCentroidMembershipFunction< itk::Vector<unsigned char,3> > MembershipFunctionType ; | ||
typedef MembershipFunctionType::Pointer MembershipFunctionPointer ; | typedef MembershipFunctionType::Pointer MembershipFunctionPointer ; | ||
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kmeansEstimator->SetMaxSplitAttempts( 10 ); | kmeansEstimator->SetMaxSplitAttempts( 10 ); | ||
kmeansEstimator->Update(); | kmeansEstimator->Update(); | ||
// Classify each pixel | |||
typedef itk::Statistics::ListSample< MeasurementVectorType > SampleType ; | typedef itk::Statistics::ListSample< MeasurementVectorType > SampleType ; | ||
typedef itk::Statistics::SampleClassifierFilter< SampleType > ClassifierType; | typedef itk::Statistics::SampleClassifierFilter< SampleType > ClassifierType; | ||
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MembershipFunctionVectorType & membershipFunctionsVector = membershipFunctionsVectorObject->Get(); | MembershipFunctionVectorType & membershipFunctionsVector = membershipFunctionsVectorObject->Get(); | ||
for(unsigned int i = 0; i < kmeansMembershipFunctions.size(); i++) | for(unsigned int i = 0; i < kmeansMembershipFunctions.size(); i++) | ||
{ | { | ||
membershipFunctionsVector.push_back(kmeansMembershipFunctions[i].GetPointer()); | membershipFunctionsVector.push_back(kmeansMembershipFunctions[i].GetPointer()); | ||
} | } | ||
// Setup class labels | // Setup class labels |
Revision as of 15:12, 12 November 2010
KmeansModelEstimator.cxx
<source lang="cpp">
- include "itkImage.h"
- include "itkListSample.h"
- include "itkVector.h"
- include "itkImageKmeansModelEstimator.h"
- include "itkImageRegionIteratorWithIndex.h"
- include "itkImageToListSampleAdaptor.h"
- include "itkDistanceToCentroidMembershipFunction.h"
- include "itkSampleClassifierFilter.h"
- include "itkMinimumDecisionRule2.h"
- include "vtkSmartPointer.h"
- include "vtkImageActor.h"
- include "vtkImageData.h"
- include "vtkInteractorStyleImage.h"
- include "vtkRenderer.h"
- include "vtkRenderWindow.h"
- include "vtkRenderWindowInteractor.h"
typedef itk::Vector<unsigned char,3> MeasurementVectorType; typedef itk::Image<MeasurementVectorType,2> ColorImageType; typedef itk::Image<unsigned char,2> GrayscaleImageType;
void CreateImage(ColorImageType::Pointer image); void ITKImagetoVTKImageColor(ColorImageType::Pointer image, vtkImageData* outputImage); void ITKImagetoVTKImageGrayscale(GrayscaleImageType::Pointer image, vtkImageData* outputImage); void CreateBlankImage(GrayscaleImageType::Pointer image, ColorImageType::Pointer inputImage);
int main(int, char* [] ) {
// Create a demo image ColorImageType::Pointer image = ColorImageType::New(); CreateImage(image);
// Compute pixel clusters using KMeans typedef itk::Statistics::DistanceToCentroidMembershipFunction< itk::Vector<unsigned char,3> > MembershipFunctionType ; typedef MembershipFunctionType::Pointer MembershipFunctionPointer ; typedef std::vector< MembershipFunctionPointer > MembershipFunctionPointerVector;
typedef itk::ImageKmeansModelEstimator<ColorImageType, MembershipFunctionType> ImageKmeansModelEstimatorType;
ImageKmeansModelEstimatorType::Pointer kmeansEstimator = ImageKmeansModelEstimatorType::New(); kmeansEstimator->SetInputImage(image); kmeansEstimator->SetNumberOfModels(3); kmeansEstimator->SetThreshold(0.01 ); kmeansEstimator->SetOffsetAdd( 0.01 ); kmeansEstimator->SetOffsetMultiply( 0.01 ); kmeansEstimator->SetMaxSplitAttempts( 10 ); kmeansEstimator->Update();
// Classify each pixel typedef itk::Statistics::ListSample< MeasurementVectorType > SampleType ; typedef itk::Statistics::SampleClassifierFilter< SampleType > ClassifierType; ClassifierType::Pointer classifier = ClassifierType::New();
typedef itk::Statistics::MinimumDecisionRule2 DecisionRuleType; DecisionRuleType::Pointer decisionRule = DecisionRuleType::New(); classifier->SetDecisionRule(decisionRule); classifier->SetNumberOfClasses(3);
typedef ClassifierType::ClassLabelVectorObjectType ClassLabelVectorObjectType; typedef ClassifierType::ClassLabelVectorType ClassLabelVectorType; typedef ClassifierType::MembershipFunctionVectorObjectType MembershipFunctionVectorObjectType; typedef ClassifierType::MembershipFunctionVectorType MembershipFunctionVectorType;
// Setup membership functions MembershipFunctionPointerVector kmeansMembershipFunctions = kmeansEstimator->GetMembershipFunctions();
MembershipFunctionVectorObjectType::Pointer membershipFunctionsVectorObject = MembershipFunctionVectorObjectType::New(); classifier->SetMembershipFunctions(membershipFunctionsVectorObject);
MembershipFunctionVectorType & membershipFunctionsVector = membershipFunctionsVectorObject->Get();
for(unsigned int i = 0; i < kmeansMembershipFunctions.size(); i++) { membershipFunctionsVector.push_back(kmeansMembershipFunctions[i].GetPointer()); }
// Setup class labels ClassLabelVectorObjectType::Pointer classLabelsObject = ClassLabelVectorObjectType::New(); classifier->SetClassLabels( classLabelsObject );
ClassLabelVectorType & classLabelsVector = classLabelsObject->Get(); classLabelsVector.push_back( 50 ); classLabelsVector.push_back( 150 ); classLabelsVector.push_back( 250 );
// Perform the classification typedef itk::Statistics::ImageToListSampleAdaptor< ColorImageType > SampleAdaptorType; SampleAdaptorType::Pointer sample = SampleAdaptorType::New(); sample->SetImage(image);
classifier->SetInput(sample); classifier->Update(); // Prepare the output image GrayscaleImageType::Pointer outputImage = GrayscaleImageType::New(); CreateBlankImage(outputImage, image);
// Setup the membership iterator const ClassifierType::MembershipSampleType* membershipSample = classifier->GetOutput(); ClassifierType::MembershipSampleType::ConstIterator membershipIterator = membershipSample->Begin();
// Setup the output image iterator - this is automatically synchronized with the membership iterator since the sample is an adaptor itk::ImageRegionIteratorWithIndex<GrayscaleImageType> outputIterator(outputImage,outputImage->GetLargestPossibleRegion()); outputIterator.GoToBegin(); while(membershipIterator != membershipSample->End()) { int classLabel = membershipIterator.GetClassLabel(); std::cout << "Class label: " << classLabel << std::endl; outputIterator.Set(static_cast<unsigned char>(classLabel)); ++membershipIterator; ++outputIterator; }
// Visualize // Original image vtkSmartPointer<vtkImageData> originalVTKImage = vtkSmartPointer<vtkImageData>::New(); ITKImagetoVTKImageColor(image, originalVTKImage);
vtkSmartPointer<vtkImageActor> originalActor = vtkSmartPointer<vtkImageActor>::New(); originalActor->SetInput(originalVTKImage);
// Kmeans image vtkSmartPointer<vtkImageData> kmeansVTKImage = vtkSmartPointer<vtkImageData>::New(); ITKImagetoVTKImageGrayscale(outputImage, kmeansVTKImage);
vtkSmartPointer<vtkImageActor> kmeansActor = vtkSmartPointer<vtkImageActor>::New(); kmeansActor->SetInput(kmeansVTKImage); // There will be one render window vtkSmartPointer<vtkRenderWindow> renderWindow = vtkSmartPointer<vtkRenderWindow>::New(); renderWindow->SetSize(600, 300);
// Define viewport ranges // (xmin, ymin, xmax, ymax) double leftViewport[4] = {0.0, 0.0, 0.5, 1.0}; double rightViewport[4] = {0.5, 0.0, 1.0, 1.0}; vtkSmartPointer<vtkRenderWindowInteractor> interactor = vtkSmartPointer<vtkRenderWindowInteractor>::New(); interactor->SetRenderWindow(renderWindow);
vtkSmartPointer<vtkRenderer> leftRenderer = vtkSmartPointer<vtkRenderer>::New(); renderWindow->AddRenderer(leftRenderer); leftRenderer->SetViewport(leftViewport); leftRenderer->SetBackground(.6, .5, .4);
leftRenderer->AddActor(originalActor); leftRenderer->ResetCamera();
vtkSmartPointer<vtkRenderer> rightRenderer = vtkSmartPointer<vtkRenderer>::New(); renderWindow->AddRenderer(rightRenderer); rightRenderer->SetViewport(rightViewport); rightRenderer->SetBackground(.7, .4, .4);
rightRenderer->AddActor(kmeansActor); rightRenderer->ResetCamera();
renderWindow->Render();
vtkSmartPointer<vtkInteractorStyleImage> style = vtkSmartPointer<vtkInteractorStyleImage>::New(); interactor->SetInteractorStyle(style);
interactor->Start();
return EXIT_SUCCESS;
}
void CreateImage(ColorImageType::Pointer image) {
// Create a black image with a red square and a green square ColorImageType::RegionType region; ColorImageType::IndexType start; start[0] = 0; start[1] = 0;
ColorImageType::SizeType size; size[0] = 200; size[1] = 300;
region.SetSize(size); region.SetIndex(start);
image->SetRegions(region); image->Allocate();
itk::ImageRegionIterator<ColorImageType> imageIterator(image,region);
itk::Vector<unsigned char, 3> redPixel; redPixel[0] = 255; redPixel[1] = 0; redPixel[2] = 0;
itk::Vector<unsigned char, 3> greenPixel; greenPixel[0] = 0; greenPixel[1] = 255; greenPixel[2] = 0; itk::Vector<unsigned char, 3> blackPixel; blackPixel[0] = 0; blackPixel[1] = 0; blackPixel[2] = 0; while(!imageIterator.IsAtEnd()) { if(imageIterator.GetIndex()[0] > 100 && imageIterator.GetIndex()[0] < 150 && imageIterator.GetIndex()[1] > 100 && imageIterator.GetIndex()[1] < 150) { imageIterator.Set(redPixel); } else if(imageIterator.GetIndex()[0] > 50 && imageIterator.GetIndex()[0] < 70 && imageIterator.GetIndex()[1] > 50 && imageIterator.GetIndex()[1] < 70) { imageIterator.Set(greenPixel); } else { imageIterator.Set(blackPixel); }
++imageIterator; }
}
void ITKImagetoVTKImageColor(ColorImageType::Pointer image, vtkImageData* outputImage)
{
outputImage->SetNumberOfScalarComponents(3); outputImage->SetScalarTypeToUnsignedChar();
outputImage->SetDimensions(image->GetLargestPossibleRegion().GetSize()[0], image->GetLargestPossibleRegion().GetSize()[1], 1);
outputImage->AllocateScalars();
int* dims = outputImage->GetDimensions();
for (int y = 0; y < dims[1]; y++) { for (int x = 0; x < dims[0]; x++) { unsigned char* pixel = static_cast<unsigned char*>(outputImage->GetScalarPointer(x,y,0)); ColorImageType::IndexType index;
index[0] = x; index[1] = y; pixel[0] = image->GetPixel(index)[0]; pixel[1] = image->GetPixel(index)[1]; pixel[2] = image->GetPixel(index)[2]; } }
}
void ITKImagetoVTKImageGrayscale(GrayscaleImageType::Pointer image, vtkImageData* outputImage)
{
outputImage->SetNumberOfScalarComponents(1); outputImage->SetScalarTypeToUnsignedChar();
outputImage->SetDimensions(image->GetLargestPossibleRegion().GetSize()[0], image->GetLargestPossibleRegion().GetSize()[1], 1);
outputImage->AllocateScalars();
int* dims = outputImage->GetDimensions();
for (int y = 0; y < dims[1]; y++) { for (int x = 0; x < dims[0]; x++) { unsigned char* pixel = static_cast<unsigned char*>(outputImage->GetScalarPointer(x,y,0)); GrayscaleImageType::IndexType index;
index[0] = x; index[1] = y; pixel[0] = image->GetPixel(index); } }
}
void CreateBlankImage(GrayscaleImageType::Pointer image, ColorImageType::Pointer inputImage) {
image->SetRegions(inputImage->GetLargestPossibleRegion()); image->Allocate();
itk::ImageRegionIterator<GrayscaleImageType> imageIterator(image,image->GetLargestPossibleRegion());
while(!imageIterator.IsAtEnd()) {
imageIterator.Set(0);
++imageIterator; }
} </source>
CMakeLists.txt
<source lang="cmake"> cmake_minimum_required(VERSION 2.6)
PROJECT(ImageKmeansModelEstimator)
FIND_PACKAGE(VTK REQUIRED) INCLUDE(${VTK_USE_FILE})
FIND_PACKAGE(ITK REQUIRED) INCLUDE(${ITK_USE_FILE})
ADD_EXECUTABLE(ImageKmeansModelEstimator ImageKmeansModelEstimator.cxx) TARGET_LINK_LIBRARIES(ImageKmeansModelEstimator ITKIO ITKStatistics vtkHybrid)
</source>