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/*=========================================================================
*
* 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 "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkGPUImage.h"
#include "itkGPUKernelManager.h"
#include "itkGPUContextManager.h"
#include "itkGPUImageToImageFilter.h"
#include "itkGPUNeighborhoodOperatorImageFilter.h"
#include "itkTimeProbe.h"
#include "itkGaussianOperator.h"
#include "itkDiscreteGaussianImageFilter.h"
#include "itkGPUDiscreteGaussianImageFilter.h"
/**
* Testing GPU Discrete Gaussian Image Filter
*/
template <unsigned int VImageDimension>
int
runGPUDiscreteGaussianImageFilterTest(const std::string & inFile, const std::string & outFile)
{
using InputPixelType = float;
using OutputPixelType = float;
using InputImageType = itk::GPUImage<InputPixelType, VImageDimension>;
using OutputImageType = itk::GPUImage<OutputPixelType, VImageDimension>;
using CPUFilterType = itk::DiscreteGaussianImageFilter<InputImageType, OutputImageType>;
using GPUFilterType = itk::GPUDiscreteGaussianImageFilter<InputImageType, OutputImageType>;
using ReaderType = itk::ImageFileReader<InputImageType>;
using WriterType = itk::ImageFileWriter<OutputImageType>;
auto reader = ReaderType::New();
auto writer = WriterType::New();
reader->SetFileName(inFile);
writer->SetFileName(outFile);
float variance = 4.0;
// test 1~8 threads for CPU
for (int numberOfWorkUnits = 1; numberOfWorkUnits <= 8; ++numberOfWorkUnits)
{
auto CPUFilter = CPUFilterType::New();
itk::TimeProbe cputimer;
cputimer.Start();
CPUFilter->SetNumberOfWorkUnits(numberOfWorkUnits);
CPUFilter->SetInput(reader->GetOutput());
CPUFilter->SetVariance(variance);
CPUFilter->Update();
cputimer.Stop();
std::cout << "CPU Gaussian Filter took " << cputimer.GetMean() << " seconds with "
<< CPUFilter->GetNumberOfWorkUnits() << " work units.\n"
<< std::endl;
// -------
if (numberOfWorkUnits == 8)
{
auto GPUFilter = GPUFilterType::New();
itk::TimeProbe gputimer;
gputimer.Start();
GPUFilter->SetInput(reader->GetOutput());
GPUFilter->SetVariance(variance);
GPUFilter->Update();
GPUFilter->GetOutput()->UpdateBuffers(); // synchronization point (GPU->CPU memcpy)
gputimer.Stop();
std::cout << "GPU Gaussian Filter took " << gputimer.GetMean() << " seconds.\n" << std::endl;
// ---------------
// RMS Error check
// ---------------
double diff = 0;
unsigned int nPix = 0;
itk::ImageRegionIterator<OutputImageType> cit(CPUFilter->GetOutput(),
CPUFilter->GetOutput()->GetLargestPossibleRegion());
itk::ImageRegionIterator<OutputImageType> git(GPUFilter->GetOutput(),
GPUFilter->GetOutput()->GetLargestPossibleRegion());
for (cit.GoToBegin(), git.GoToBegin(); !cit.IsAtEnd(); ++cit, ++git)
{
double err = static_cast<double>(cit.Get()) - static_cast<double>(git.Get());
// if(err > 0.1 || static_cast<double>(cit.Get()) < 0.1) std::cout << "CPU : " <<
// static_cast<double>(cit.Get()) <<
// ", GPU : "
// << static_cast<double>(git.Get()) << std::endl;
diff += err * err;
nPix++;
}
writer->SetInput(GPUFilter->GetOutput());
writer->Update();
if (nPix > 0)
{
double RMSError = sqrt(diff / static_cast<double>(nPix));
std::cout << "RMS Error : " << RMSError << std::endl;
// the CPU filter operator has type double
// but the double precision is not well-supported on most GPUs
// and by most drivers at this time. Therefore, the GPU filter
// operator has type float
// relax the RMS threshold here to allow for errors due to
// differences in precision
// NOTE:
// a threshold of 1.2e-5 worked on linux and Mac, but not Windows
// why?
double RMSThreshold = 1.7e-5;
if (itk::Math::isnan(RMSError))
{
std::cout << "RMS Error is NaN! nPix: " << nPix << std::endl;
return EXIT_FAILURE;
}
if (RMSError > RMSThreshold)
{
std::cout << "RMS Error exceeds threshold (" << RMSThreshold << ')' << std::endl;
return EXIT_FAILURE;
}
}
else
{
std::cout << "No pixels in output!" << std::endl;
return EXIT_FAILURE;
}
}
}
return EXIT_SUCCESS;
}
int
itkGPUDiscreteGaussianImageFilterTest(int argc, char * argv[])
{
if (!itk::IsGPUAvailable())
{
std::cerr << "OpenCL-enabled GPU is not present." << std::endl;
return EXIT_FAILURE;
}
if (argc < 3)
{
std::cerr << "Error: missing arguments" << std::endl;
std::cerr << "inputfile outputfile [num_dimensions]" << std::endl;
return EXIT_FAILURE;
}
std::string inFile(argv[1]);
std::string outFile(argv[2]);
unsigned int dim = 3;
if (argc >= 4)
{
dim = std::stoi(argv[3]);
}
if (dim == 2)
{
return runGPUDiscreteGaussianImageFilterTest<2>(inFile, outFile);
}
else if (dim == 3)
{
return runGPUDiscreteGaussianImageFilterTest<3>(inFile, outFile);
}
else
{
std::cerr << "Error: only 2 or 3 dimensions allowed, " << dim << " selected." << std::endl;
return EXIT_FAILURE;
}
}
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