How to convert tensor to image array? - c++

Question

I would like to convert a tensor to image array and use tensor.data() method.
But it doesn't work.
#include <torch/script.h> // One-stop header.
#include <iostream>
#include <memory>
#include <sstream>
#include <string>
#include <vector>
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkImageRegionIterator.h"
//////////////////////////////////////////////////////
//Goal: load jit script model and segment myocardium
//Step: 1. load jit script model
// 2. load input image
// 3. predict by model
// 4. save the result to file
//////////////////////////////////////////////////////
typedef short PixelType;
const unsigned int Dimension = 3;
typedef itk::Image<PixelType, Dimension> ImageType;
typedef itk::ImageFileReader<ImageType> ReaderType;
typedef itk::ImageRegionIterator<ImageType> IteratorType;
bool itk2tensor(ImageType::Pointer itk_img, torch::Tensor &tensor_img) {
typename ImageType::RegionType region = itk_img->GetLargestPossibleRegion();
const typename ImageType::SizeType size = region.GetSize();
std::cout << "Input size: " << size[0] << ", " << size[1]<< ", " << size[2] << std::endl;
int len = size[0] * size[1] * size[2];
short rowdata[len];
int count = 0;
IteratorType iter(itk_img, itk_img->GetRequestedRegion());
// convert itk to array
for (iter.GoToBegin(); !iter.IsAtEnd(); ++iter) {
rowdata[count] = iter.Get();
count++;
}
std::cout << "Convert itk to array DONE!" << std::endl;
// convert array to tensor
tensor_img = torch::from_blob(rowdata, {1, 1, (int)size[0], (int)size[1], (int)size[2]}, torch::kShort).clone();
tensor_img = tensor_img.toType(torch::kFloat);
tensor_img = tensor_img.to(torch::kCUDA);
tensor_img.set_requires_grad(0);
return true;
}
bool tensor2itk(torch::Tensor &t, ImageType::Pointer itk_img) {
std::cout << "tensor dtype = " << t.dtype() << std::endl;
std::cout << "tensor size = " << t.sizes() << std::endl;
t = t.toType(torch::kShort);
short * array = t.data<short>();
ImageType::IndexType start;
start[0] = 0; // first index on X
start[1] = 0; // first index on Y
start[2] = 0; // first index on Z
ImageType::SizeType size;
size[0] = t.size(2);
size[1] = t.size(3);
size[2] = t.size(4);
ImageType::RegionType region;
region.SetSize( size );
region.SetIndex( start );
itk_img->SetRegions( region );
itk_img->Allocate();
int len = size[0] * size[1] * size[2];
IteratorType iter(itk_img, itk_img->GetRequestedRegion());
int count = 0;
// convert array to itk
std::cout << "start!" << std::endl;
for (iter.GoToBegin(); !iter.IsAtEnd(); ++iter) {
short temp = *array++; // ERROR!
std::cout << temp << " ";
iter.Set(temp);
count++;
}
std::cout << "end!" << std::endl;
return true;
}
int main(int argc, const char* argv[]) {
int a, b, c;
if (argc != 4) {
std::cerr << "usage: automyo input jitmodel output\n";
return -1;
}
std::cout << "========= jit start =========\n";
// 1. load jit script model
std::cout << "Load script module: " << argv[2] << std::endl;
std::shared_ptr<torch::jit::script::Module> module = torch::jit::load(argv[2]);
module->to(at::kCUDA);
// assert(module != nullptr);
std::cout << "Load script module DONE" << std::endl;
// 2. load input image
const char* img_path = argv[1];
std::cout << "Load image: " << img_path << std::endl;
ReaderType::Pointer reader = ReaderType::New();
if (!img_path) {
std::cout << "Load input file error!" << std::endl;
return false;
}
reader->SetFileName(img_path);
reader->Update();
std::cout << "Load image DONE!" << std::endl;
ImageType::Pointer itk_img = reader->GetOutput();
torch::Tensor tensor_img;
if (!itk2tensor(itk_img, tensor_img)) {
std::cerr << "itk2tensor ERROR!" << std::endl;
}
else {
std::cout << "Convert array to tensor DONE!" << std::endl;
}
std::vector<torch::jit::IValue> inputs;
inputs.push_back(tensor_img);
// 3. predict by model
torch::Tensor y = module->forward(inputs).toTensor();
std::cout << "Inference DONE!" << std::endl;
// 4. save the result to file
torch::Tensor seg = y.gt(0.5);
// std::cout << seg << std::endl;
ImageType::Pointer out_itk_img = ImageType::New();
if (!tensor2itk(seg, out_itk_img)) {
std::cerr << "tensor2itk ERROR!" << std::endl;
}
else {
std::cout << "Convert tensor to itk DONE!" << std::endl;
}
std::cout << out_itk_img << std::endl;
return true;
}
The runtime log is showed below:
Load script module:model_myo_jit.pt
Load script module DONE Load
image: patch_6.nii.gz
Load image DONE!
Input size: 128, 128, 128
Convert itk to array DONE!
Convert array to tensor DONE!
Inference DONE!
tensor dtype = unsigned char
tensor size = [1, 1, 96, 96, 96]
start!
Segmentation fault (core dumped)
Why and how to convert?

Answer 1

I have found the solution. When I convert the y to kCPU, it works. Because it in CUDA before.