// -----------------------------------------------------------------------------
//
// -----------------------------------------------------------------------------
void Threshold::execute()
{
std::stringstream ss;
int err = 0;
setErrorCondition(err);
VoxelDataContainer* m = getVoxelDataContainer();
if(NULL == m)
{
setErrorCondition(-999);
notifyErrorMessage("The DataContainer Object was NULL", getErrorCondition());
return;
}
setErrorCondition(0);
int64_t totalPoints = m->getTotalPoints();
size_t totalFields = m->getNumFieldTuples();
size_t totalEnsembles = m->getNumEnsembleTuples();
dataCheck(false, totalPoints, totalFields, totalEnsembles);
if(m_OverwriteArray)
{
CREATE_NON_PREREQ_DATA(m, DREAM3D, CellData, ProcessedImageData, ss, ImageProcessing::DefaultPixelType, ImageProcessing::DefaultArrayType, 0, totalPoints, 1)
}
if (getErrorCondition() < 0)
{
return;
}
//get dims
size_t udims[3] = {0,0,0};
m->getDimensions(udims);
#if (CMP_SIZEOF_SIZE_T == 4)
typedef int32_t DimType;
#else
typedef int64_t DimType;
#endif
DimType dims[3] = {
static_cast<DimType>(udims[0]),
static_cast<DimType>(udims[1]),
static_cast<DimType>(udims[2]),
};
//wrap input as itk image
ImageProcessing::DefaultImageType::Pointer inputImage=ITKUtilities::Dream3DtoITK(m, m_RawImageData);
//define threshold filters
typedef itk::BinaryThresholdImageFilter <ImageProcessing::DefaultImageType, ImageProcessing::DefaultImageType> BinaryThresholdImageFilterType;
typedef itk::BinaryThresholdImageFilter <ImageProcessing::DefaultSliceType, ImageProcessing::DefaultSliceType> BinaryThresholdImageFilterType2D;
if(m_Method>=0 && m_Method<=11)
{
//define hitogram generator (will make the same kind of histogram for 2 and 3d images
typedef itk::Statistics::ImageToHistogramFilter<ImageProcessing::DefaultImageType> HistogramGenerator;
//find threshold value w/ histogram
itk::HistogramThresholdCalculator< HistogramGenerator::HistogramType, uint8_t >::Pointer calculator;
typedef itk::HuangThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > HuangCalculatorType;
typedef itk::IntermodesThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > IntermodesCalculatorType;
typedef itk::IsoDataThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > IsoDataCalculatorType;
typedef itk::KittlerIllingworthThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > KittlerIllingowrthCalculatorType;
typedef itk::LiThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > LiCalculatorType;
typedef itk::MaximumEntropyThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > MaximumEntropyCalculatorType;
typedef itk::MomentsThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > MomentsCalculatorType;
typedef itk::OtsuThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > OtsuCalculatorType;
typedef itk::RenyiEntropyThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > RenyiEntropyCalculatorType;
typedef itk::ShanbhagThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > ShanbhagCalculatorType;
typedef itk::TriangleThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > TriangleCalculatorType;
typedef itk::YenThresholdCalculator< HistogramGenerator::HistogramType, uint8_t > YenCalculatorType;
switch(m_Method)
{
case 0:
{
calculator = HuangCalculatorType::New();
}
break;
case 1:
{
calculator = IntermodesCalculatorType::New();
}
break;
case 2:
{
calculator = IsoDataCalculatorType::New();
}
break;
case 3:
{
calculator = KittlerIllingowrthCalculatorType::New();
}
break;
case 4:
{
calculator = LiCalculatorType::New();
}
break;
case 5:
{
calculator = MaximumEntropyCalculatorType::New();
}
break;
case 6:
{
calculator = MomentsCalculatorType::New();
}
break;
case 7:
{
calculator = OtsuCalculatorType::New();
}
break;
case 8:
{
calculator = RenyiEntropyCalculatorType::New();
}
break;
case 9:
{
calculator = ShanbhagCalculatorType::New();
}
break;
case 10:
{
calculator = TriangleCalculatorType::New();
}
break;
case 11:
{
calculator = YenCalculatorType::New();
}
break;
}
if(m_Slice)
{
//define 2d histogram generator
typedef itk::Statistics::ImageToHistogramFilter<ImageProcessing::DefaultSliceType> HistogramGenerator2D;
HistogramGenerator2D::Pointer histogramFilter2D = HistogramGenerator2D::New();
//specify number of bins / bounds
typedef HistogramGenerator2D::HistogramSizeType SizeType;
SizeType size( 1 );
size[0] = 255;
histogramFilter2D->SetHistogramSize( size );
histogramFilter2D->SetMarginalScale( 10.0 );
HistogramGenerator2D::HistogramMeasurementVectorType lowerBound( 1 );
HistogramGenerator2D::HistogramMeasurementVectorType upperBound( 1 );
lowerBound[0] = 0;
upperBound[0] = 256;
histogramFilter2D->SetHistogramBinMinimum( lowerBound );
histogramFilter2D->SetHistogramBinMaximum( upperBound );
//wrap output buffer as image
ImageProcessing::DefaultImageType::Pointer outputImage=ITKUtilities::Dream3DtoITK(m, m_ProcessedImageData);
//loop over slices
for(int i=0; i<dims[2]; i++)
{
//get slice
ImageProcessing::DefaultSliceType::Pointer slice = ITKUtilities::ExtractSlice<ImageProcessing::DefaultPixelType>(inputImage, ImageProcessing::ZSlice, i);
//find histogram
histogramFilter2D->SetInput( slice );
histogramFilter2D->Update();
const HistogramGenerator::HistogramType * histogram = histogramFilter2D->GetOutput();
//calculate threshold level
calculator->SetInput(histogram);
calculator->Update();
const uint8_t thresholdValue = calculator->GetThreshold();
//threshold
BinaryThresholdImageFilterType2D::Pointer thresholdFilter = BinaryThresholdImageFilterType2D::New();
thresholdFilter->SetInput(slice);
thresholdFilter->SetLowerThreshold(thresholdValue);
thresholdFilter->SetUpperThreshold(255);
thresholdFilter->SetInsideValue(255);
thresholdFilter->SetOutsideValue(0);
thresholdFilter->Update();
//copy back into volume
ITKUtilities::SetSlice<ImageProcessing::DefaultPixelType>(outputImage, thresholdFilter->GetOutput(), ImageProcessing::ZSlice, i);
}
}
else
{
//specify number of bins / bounds
HistogramGenerator::Pointer histogramFilter = HistogramGenerator::New();
typedef HistogramGenerator::HistogramSizeType SizeType;
SizeType size( 1 );
size[0] = 255;
histogramFilter->SetHistogramSize( size );
histogramFilter->SetMarginalScale( 10.0 );
HistogramGenerator::HistogramMeasurementVectorType lowerBound( 1 );
HistogramGenerator::HistogramMeasurementVectorType upperBound( 1 );
lowerBound[0] = 0;
upperBound[0] = 256;
histogramFilter->SetHistogramBinMinimum( lowerBound );
histogramFilter->SetHistogramBinMaximum( upperBound );
//find histogram
histogramFilter->SetInput( inputImage );
histogramFilter->Update();
const HistogramGenerator::HistogramType * histogram = histogramFilter->GetOutput();
//calculate threshold level
calculator->SetInput(histogram);
calculator->Update();
const uint8_t thresholdValue = calculator->GetThreshold();
//threshold
BinaryThresholdImageFilterType::Pointer thresholdFilter = BinaryThresholdImageFilterType::New();
thresholdFilter->SetInput(inputImage);
thresholdFilter->SetLowerThreshold(thresholdValue);
thresholdFilter->SetUpperThreshold(255);
thresholdFilter->SetInsideValue(255);
thresholdFilter->SetOutsideValue(0);
thresholdFilter->GetOutput()->GetPixelContainer()->SetImportPointer(m_ProcessedImageData, totalPoints, false);
thresholdFilter->Update();
}
}
else if(m_Method==12)//manual
{
//threshold
BinaryThresholdImageFilterType::Pointer thresholdFilter = BinaryThresholdImageFilterType::New();
thresholdFilter->SetInput(inputImage);
thresholdFilter->SetLowerThreshold(m_ManualParameter);
thresholdFilter->SetUpperThreshold(255);
thresholdFilter->SetInsideValue(255);
thresholdFilter->SetOutsideValue(0);
thresholdFilter->GetOutput()->GetPixelContainer()->SetImportPointer(m_ProcessedImageData, totalPoints, false);
thresholdFilter->Update();
}
/*
else if(m_Method==13)//robust automatic
{
typedef itk::GradientMagnitudeImageFilter<ImageProcessing::DefaultImageType, ImageProcessing::DefaultImageType> GradientMagnitudeType;
typedef itk::GradientMagnitudeImageFilter<ImageProcessing::DefaultSliceType, ImageProcessing::DefaultSliceType> GradientMagnitudeType2D;
typedef itk::itkRobustAutomaticThresholdCalculator<ImageProcessing::DefaultImageType,ImageProcessing::DefaultImageType> SelectionType;
typedef itk::itkRobustAutomaticThresholdCalculator<ImageProcessing::DefaultSliceType,ImageProcessing::DefaultSliceType> SelectionType2D;
if(m_slice)
{
//wrap output buffer as image
ImageProcessing::DefaultImageType::Pointer outputImage=ITKUtilities::Dream3DtoITK(m, m_ProcessedImageData);
//loop over slices
for(int i=0; i<dims[2]; i++)
{
//get slice
ImageProcessing::DefaultSliceType::Pointer slice = ITKUtilities::ExtractSlice<ImageProcessing::DefaultPixelType>(inputImage, ImageProcessing::ZSlice, i);
//find gradient
GradientMagnitudeType2D::Pointer gradientFilter = GradientMagnitudeType2D::New();
gradientFilter->setInput(slice);
gradientFilter->Update();
//calculate thershold
SelectionType2D::Pointer calculatorFilter = SelectionType2D::New();
calculatorFilter->SetInput(slice);
calculatorFilter->SetGradientImage(gradientFilter->GetOutput());
calculatorFilter->SetPow(m_ManualParameter);
calculatorFilter->Update();
const uint8_t thresholdValue = calculatorFilter->GetOutput();
//threshold
BinaryThresholdImageFilterType::Pointer thresholdFilter = BinaryThresholdImageFilterType::New();
thresholdFilter->SetInput(inputImage);
thresholdFilter->SetLowerThreshold(thresholdValue);
thresholdFilter->SetUpperThreshold(255);
thresholdFilter->SetInsideValue(255);
thresholdFilter->SetOutsideValue(0);
thresholdFilter->Update();
//copy back into volume
ITKUtilities::SetSlice<ImageProcessing::DefaultPixelType>(outputImage, thresholdFilter->GetOutput(), ImageProcessing::ZSlice, i);
}
}
else
{
//find gradient
GradientMagnitudeType::Pointer gradientFilter = GradientMagnitudeType::New();
gradientFilter->setInput(inputImage);
gradientFilter->Update();
//calculate threshold
SelectionType::Pointer calculatorFilter = SelectionType::New();
calculatorFilter->SetInput(inputImage);
calculatorFilter->SetGradientImage(gradientFilter->GetOutput());
calculatorFilter->SetPow(m_ManualParameter);
calculatorFilter->Update();
const uint8_t thresholdValue = calculatorFilter->GetOutput();
//threshold
BinaryThresholdImageFilterType::Pointer thresholdFilter = BinaryThresholdImageFilterType::New();
thresholdFilter->SetInput(inputImage);
thresholdFilter->SetLowerThreshold(thresholdValue);
thresholdFilter->SetUpperThreshold(255);
thresholdFilter->SetInsideValue(255);
thresholdFilter->SetOutsideValue(0);
thresholdFilter->GetOutput()->GetPixelContainer()->SetImportPointer(m_ProcessedImageData, totalPoints, false);
thresholdFilter->Update();
}
}
*/
//array name changing/cleanup
if(m_OverwriteArray)
{
m->removeCellData(m_SelectedCellArrayName);
bool check = m->renameCellData(m_ProcessedImageDataArrayName, m_SelectedCellArrayName);
}
/* Let the GUI know we are done with this filter */
notifyStatusMessage("Complete");
}
int main( int argc, char* argv[] )
{
if( argc != 3 )
{
std::cerr << "Usage: "<< std::endl;
std::cerr << argv[0];
std::cerr << " <InputFileName> n";
std::cerr << std::endl;
return EXIT_FAILURE;
}
int operations = atoi(argv[2]);
//sscanf(&operations,"%d",argv[2]);
//printf("%d\n", operations);
itk::TimeProbe itkClock;
double t0 = 0.0;
double tf = 0.0;
itk::MultiThreader::SetGlobalDefaultNumberOfThreads(1);
// Loading file
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
reader->Update();
ImageType::Pointer image = reader->GetOutput();
#ifdef GPU
GPUReaderType::Pointer gpureader = GPUReaderType::New();
gpureader->SetFileName( argv[1] );
gpureader->Update();
GPUImageType::Pointer gpuImage = gpureader->GetOutput();
#endif
saveFile((char*) "/tmp/itk_input.dcm", image);
// Allocate output image
ImageType::Pointer output = ImageType::New();
ImageType::RegionType region = image->GetBufferedRegion();
output->SetRegions( region );
output->SetOrigin( image->GetOrigin() );
output->SetSpacing( image->GetSpacing() );
output->Allocate();
// Negative
typedef itk::UnaryFunctorImageFilter<ImageType,ImageType,
Negate<ImageType::PixelType,ImageType::PixelType> > NegateImageFilterType;
NegateImageFilterType::Pointer negateFilter = NegateImageFilterType::New();
negateFilter = NegateImageFilterType::New();
negateFilter->SetInput(image);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
negateFilter->Modified();
negateFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d negative: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
#endif
// Saving Not result
saveFile((char*) "/tmp/itk_not.dcm", negateFilter->GetOutput());
#ifdef GPU
// GPU Negative
typedef itk::GPUUnaryFunctorImageFilter<ImageType,ImageType,
Negate<ImageType::PixelType,ImageType::PixelType> > GPUNegateImageFilterType;
GPUNegateImageFilterType::Pointer gpuNegateFilter = GPUNegateImageFilterType::New();
gpuNegateFilter->SetInput(gpureader->GetOutput());
gpuNegateFilter->Update();
// Saving Not result
//saveFile("/tmp/itk_gpu_not.dcm", gpuNegateFilter->GetOutput());
#endif
// Common Threshold
int lowerThreshold = 100;
int upperThreshold = 200;
// Threshold
typedef itk::BinaryThresholdImageFilter <ImageType, ImageType>
BinaryThresholdImageFilterType;
BinaryThresholdImageFilterType::Pointer thresholdFilter
= BinaryThresholdImageFilterType::New();
thresholdFilter = BinaryThresholdImageFilterType::New();
thresholdFilter->SetInput(reader->GetOutput());
thresholdFilter->SetLowerThreshold(lowerThreshold);
thresholdFilter->SetUpperThreshold(upperThreshold);
thresholdFilter->SetInsideValue(255);
thresholdFilter->SetOutsideValue(0);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
thresholdFilter->Modified();
thresholdFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d threshold: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Threshold result
saveFile((char*) "/tmp/itk_thresh.dcm", thresholdFilter->GetOutput());
#endif
#ifdef GPU
// GPU Threshold
typedef itk::GPUBinaryThresholdImageFilter <GPUImageType, GPUImageType>
GPUBinaryThresholdImageFilterType;
GPUBinaryThresholdImageFilterType::Pointer gpuThresholdFilter
= GPUBinaryThresholdImageFilterType::New();
gpuThresholdFilter->SetInput(gpureader->GetOutput());
gpuThresholdFilter->SetLowerThreshold(lowerThreshold);
gpuThresholdFilter->SetUpperThreshold(upperThreshold);
gpuThresholdFilter->SetInsideValue(255);
gpuThresholdFilter->SetOutsideValue(0);
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
gpuThresholdFilter->Modified();
gpuThresholdFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d GPU threshold: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving GPU Threshold result
gpuThresholdFilter->GetOutput()->UpdateBuffers();
saveFile((char*) "/tmp/itk_gpu_thresh.dcm", gpuThresholdFilter->GetOutput());
#endif
// Mean
typedef itk::MeanImageFilter< ImageType, ImageType > MeanFilterType;
MeanFilterType::Pointer meanFilter = MeanFilterType::New();
meanFilter = MeanFilterType::New();
meanFilter->SetInput( image );
meanFilter->SetRadius( 1 );
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
meanFilter->Modified();
meanFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d mean blur: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Convolution result
saveFile((char*) "/tmp/itk_mean3x3.dcm", meanFilter->GetOutput());
#endif
// Binomial Blur (aproximation of gaussian blur)
typedef itk::BinomialBlurImageFilter<ImageType, ImageType> BinomialBlurImageFilterType;
int repetitions = 1;
BinomialBlurImageFilterType::Pointer blurFilter = BinomialBlurImageFilterType::New();
blurFilter = BinomialBlurImageFilterType::New();
blurFilter->SetInput( reader->GetOutput() );
blurFilter->SetRepetitions( repetitions );
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
blurFilter->Modified();
blurFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d blur: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Blur result
saveFile((char*) "/tmp/itk_blur.dcm", blurFilter->GetOutput());
#endif
#ifdef GPU
// GPU Blur
typedef itk::BoxImageFilter< GPUImageType, GPUImageType > BoxImageFilterType;
typedef itk::GPUBoxImageFilter< GPUImageType, GPUImageType, BoxImageFilterType > GPUBoxImageFilterType;
GPUBoxImageFilterType::Pointer GPUBlurFilter = GPUBoxImageFilterType::New();
//ImageType::SizeType indexRadius;
//indexRadius[0] = 2;
//indexRadius[1] = 2;
//indexRadius[2] = 2;
GPUBlurFilter->SetInput(gpureader->GetOutput());
//GPUBlurFilter->SetRadius(indexRadius);
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
GPUBlurFilter->Update();
GPUBlurFilter->Modified();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d gpu blur: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
GPUBlurFilter->GetOutput()->UpdateBuffers();
// Saving GPU Blur result
saveFile((char*) "/tmp/itk_gpu_blur.dcm", GPUBlurFilter->GetOutput());
#endif
//Erosion Common
typedef itk::BinaryBallStructuringElement<
ImageType::PixelType, 3> StructuringElementType;
typedef itk::GrayscaleErodeImageFilter <ImageType, ImageType, StructuringElementType>
GrayscaleErodeImageFilterType;
unsigned int radius;
// Erosion 3x3
StructuringElementType structuringElement3x3;
radius = 1;
structuringElement3x3.SetRadius(radius);
structuringElement3x3.CreateStructuringElement();
GrayscaleErodeImageFilterType::Pointer erodeFilter3x3;
erodeFilter3x3= GrayscaleErodeImageFilterType::New();
erodeFilter3x3->SetInput(reader->GetOutput());
erodeFilter3x3->SetKernel(structuringElement3x3);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
erodeFilter3x3->Modified();
erodeFilter3x3->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d erosion 3x3: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Erosion result
saveFile((char*) "/tmp/itk_erode3x3.dcm", erodeFilter3x3->GetOutput());
#endif
// Erosion 5x5
StructuringElementType structuringElement5x5;
radius = 2;
structuringElement5x5.SetRadius(radius);
structuringElement5x5.CreateStructuringElement();
GrayscaleErodeImageFilterType::Pointer erodeFilter5x5;
erodeFilter5x5 = GrayscaleErodeImageFilterType::New();
erodeFilter5x5->SetInput(reader->GetOutput());
erodeFilter5x5->SetKernel(structuringElement5x5);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
erodeFilter5x5->Modified();
erodeFilter5x5->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d erosion 5x5: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Erosion result
saveFile((char*) "/tmp/itk_erode5x5.dcm", erodeFilter5x5->GetOutput());
#endif
// Copy
typedef itk::ImageDuplicator< ImageType > DuplicatorType;
DuplicatorType::Pointer duplicator;
duplicator = DuplicatorType::New();
duplicator->SetInputImage(image);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
duplicator->Modified();
duplicator->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d copias cpu: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Copy result
saveFile((char*) "/tmp/itk_copy.dcm", duplicator->GetOutput());
#endif
// Convolution common
typedef itk::ConvolutionImageFilter<ImageType> ConvolutionImageFilterType;
ConvolutionImageFilterType::Pointer convolutionFilter;
convolutionFilter = ConvolutionImageFilterType::New();
convolutionFilter->SetInput(reader->GetOutput());
int convWidth;
// Convolution 3x3
ImageType::Pointer kernel3x3 = ImageType::New();
convWidth = 3;
CreateKernel(kernel3x3, convWidth);
convolutionFilter->SetKernelImage(kernel3x3);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
convolutionFilter->Modified();
convolutionFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d convolucoes 3x3 cpu: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Convolution result
saveFile((char*) "/tmp/itk_convolution3x3.dcm", convolutionFilter->GetOutput());
#endif
// Convolution 5x5
ImageType::Pointer kernel5x5 = ImageType::New();
convWidth = 5;
CreateKernel(kernel5x5, convWidth);
convolutionFilter->SetKernelImage(kernel5x5);
#ifndef GPU_only
itkClock.Start();
TimerStart();
for(int n = 0; n < operations; n++)
{
convolutionFilter->Modified();
convolutionFilter->Update();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d convolucoes 5x5 cpu: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
// Saving Convolution result
saveFile((char*) "/tmp/itk_convolution5x5.dcm", convolutionFilter->GetOutput());
#endif
#ifdef GPU
// GPU Mean
typedef itk::GPUMeanImageFilter<GPUImageType, GPUImageType> GPUMeanFilterType;
GPUMeanFilterType::Pointer GPUMean = GPUMeanFilterType::New();
GPUMean->SetInput(gpureader->GetOutput());
GPUMean->SetRadius( 1 );
TimerStart();
for(int n = 0; n < operations; n++)
{
GPUMean->Update();
GPUMean->Modified();
}
itkClock.Stop();
printf("Tempo gasto para fazer %d GPU mean blur: %s\n",operations, getTimeElapsedInSeconds());
tf = itkClock.GetTotal();
std::cout << "My: " << (tf - t0) << std::endl;
t0 = tf;
GPUMean->GetOutput()->UpdateBuffers();
saveFile((char*) "/tmp/itk_gpu_blurmean.dcm", GPUMean->GetOutput());
#endif
// Visualize
/*
QuickView viewer;
viewer.AddImage<ImageType>(
image,true,
itksys::SystemTools::GetFilenameName(argv[1]));
std::stringstream desc;
desc << "ITK QuickView: "
<< argv[1];
viewer.Visualize();
*/
// Saving input image as is
saveFile((char*) "/tmp/itk_input.dcm", image);
return EXIT_SUCCESS;
}
