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#include "antsUtilities.h"
#include <algorithm>
#include <algorithm>
#include "stdio.h"
#include "itkImage.h"
#include "itkImageRegionIteratorWithIndex.h"
#include "ReadWriteData.h"
#include "TensorFunctions.h"
namespace ants
{
template <unsigned int ImageDimension>
int
AverageTensorImages(unsigned int argc, char * argv[])
{
// typedef itk::Vector<float,6> TensorType;
using TensorType = itk::SymmetricSecondRankTensor<float, 3>;
using ImageType = itk::Image<TensorType, ImageDimension>;
using IteratorType = itk::ImageRegionIteratorWithIndex<ImageType>;
char * outputName = argv[2];
int mathtype = std::stoi(argv[3]);
float numberofimages = static_cast<float>(argc) - 4.0f;
std::cout << "Averaging " << numberofimages << " images " << std::endl;
typename ImageType::Pointer averageimage = nullptr;
typename ImageType::Pointer image2 = nullptr;
typename ImageType::SizeType size;
size.Fill(0);
unsigned int bigimage = 0;
for (unsigned int j = 4; j < argc; j++)
{
// Get the image dimension
std::string fn = std::string(argv[j]);
std::cout << " fn " << fn << std::endl;
typename itk::ImageIOBase::Pointer imageIO =
itk::ImageIOFactory::CreateImageIO(fn.c_str(), itk::IOFileModeEnum::ReadMode);
imageIO->SetFileName(fn.c_str());
imageIO->ReadImageInformation();
for (unsigned int i = 0; i < imageIO->GetNumberOfDimensions(); i++)
{
if (imageIO->GetDimensions(i) > size[i])
{
size[i] = imageIO->GetDimensions(i);
bigimage = j;
std::cout << " bigimage " << j << " size " << size << std::endl;
}
}
}
std::cout << " largest image " << size << std::endl;
bool logeuc = true;
if (mathtype == 1)
{
logeuc = false;
}
TensorType nullTensor;
nullTensor[0] = nullTensor[1] = nullTensor[2] = nullTensor[3] = nullTensor[4] = nullTensor[5] = 0;
ReadTensorImage<ImageType>(averageimage, argv[bigimage], logeuc);
averageimage->FillBuffer(nullTensor);
for (unsigned int j = 4; j < argc; j++)
{
std::string fn = std::string(argv[j]);
ReadTensorImage<ImageType>(image2, fn.c_str(), logeuc);
IteratorType vfIter(image2, image2->GetLargestPossibleRegion());
for (vfIter.GoToBegin(); !vfIter.IsAtEnd(); ++vfIter)
{
TensorType val = vfIter.Get() / numberofimages;
averageimage->SetPixel(vfIter.GetIndex(), val + averageimage->GetPixel(vfIter.GetIndex()));
}
}
WriteTensorImage<ImageType>(averageimage, outputName, logeuc);
return EXIT_SUCCESS;
}
// Main Program
// entry point for the library; parameter 'args' is equivalent to 'argv' in (argc,argv) of commandline parameters to
// 'main()'
int
AverageTensorImages(std::vector<std::string> args, std::ostream * /*out_stream = nullptr */)
{
// put the arguments coming in as 'args' into standard (argc,argv) format;
// 'args' doesn't have the command name as first, argument, so add it manually;
// 'args' may have adjacent arguments concatenated into one argument,
// which the parser should handle
args.insert(args.begin(), "AverageTensorImages");
int argc = args.size();
char ** argv = new char *[args.size() + 1];
for (unsigned int i = 0; i < args.size(); ++i)
{
// allocate space for the string plus a null character
argv[i] = new char[args[i].length() + 1];
std::strncpy(argv[i], args[i].c_str(), args[i].length());
// place the null character in the end
argv[i][args[i].length()] = '\0';
}
argv[argc] = nullptr;
// class to automatically cleanup argv upon destruction
class Cleanup_argv
{
public:
Cleanup_argv(char ** argv_, int argc_plus_one_)
: argv(argv_)
, argc_plus_one(argc_plus_one_)
{}
~Cleanup_argv()
{
for (unsigned int i = 0; i < argc_plus_one; ++i)
{
delete[] argv[i];
}
delete[] argv;
}
private:
char ** argv;
unsigned int argc_plus_one;
};
Cleanup_argv cleanup_argv(argv, argc + 1);
// antscout->set_stream( out_stream );
try
{
if (argc - 4 < 1)
{
std::cerr << "Basic useage ex: " << std::endl;
std::cerr << argv[0] << " ImageDimension average.nii mathtype list-of-files-via-wildcard " << std::endl;
std::cerr << " e.g. \n AverageTensorImages 3 average.nii 1 *registered.nii " << std::endl;
std::cerr << " mathtype=[0=log-euclidean, 1=euclidean] " << std::endl;
if (argc >= 2 && (std::string(argv[1]) == std::string("--help") || std::string(argv[1]) == std::string("-h")))
{
return EXIT_SUCCESS;
}
return EXIT_FAILURE;
}
int dim = std::stoi(argv[1]);
// char * outputName = argv[2];
// int mathtype = std::stoi(argv[3]);
// int numberofimages = argc - 4;
// Get the image dimension
switch (dim)
{
case 2:
{
return AverageTensorImages<2>(argc, argv);
}
break;
case 3:
{
return AverageTensorImages<3>(argc, argv);
}
break;
default:
std::cerr << "Unsupported dimension" << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
catch (const itk::ExceptionObject & err)
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
}
} // namespace ants
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