How to convert 4 dimensional matrix to NHWC format in OpenCV - c++

Question

So I'm in the middle of implementing SIFT and the thing is that I don't know how to deal with channel in OpenCV. Here is what I've done so far.
#ifndef QUANTIZATION_DATABASE_DATA_READ_H
#define QUANTIZATION_DATABASE_DATA_READ_H
// C HEADERS
#include <stdlib.h>
#include <fcntl.h>
// C++ HEADERS
#include <iostream>
#include <string>
// OPENCV HEADERS
#include <opencv2/opencv.hpp>
namespace cv
{
class DataReader
{
public:
explicit DataReader(int _flags) : flags(_flags)
{
}
void read(std::string filename, const char *key, Mat &res)
{
try
{
FileStorage fs(filename, FileStorage::Mode::FORMAT_XML | FileStorage::Mode::READ);
fs[key] >> res;
fs.release();
}
catch (Exception e)
{
std::cerr << e.msg << std::endl;
}
}
private:
int flags;
};
}
The algorithm that I want to implement is as follow.
Read the 4 dimensional matrix(NHWC) from a xml file.
Store it in a matrix
Convert it into NHWC
The thing is that I don't have to do step 3 when I do some stuffs using Tensorflow. It just automatically knows the last dimension is channel. So, what should I do?

Answer 1

It seems like there is no way whatsoever to make 4 dimensional buffer to a batch of images. So I decided to change the format of the xml file and it worked like a charm.
Below is temporarily workaround for this problem.
#ifndef QUANTIZATION_DATABASE_DATA_READ_H
#define QUANTIZATION_DATABASE_DATA_READ_H
// C HEADERS
#include <stdlib.h>
#include <fcntl.h>
// C++ HEADERS
#include <iostream>
#include <string>
// OPENCV HEADERS
#include <opencv2/opencv.hpp>
namespace cv
{
class DataReader
{
public:
explicit DataReader(int _flags) : flags(_flags)
{
}
void read(std::string filename, Mat &res)
{
try
{
float length = 0;
FileStorage fs(filename, FileStorage::Mode::FORMAT_XML | FileStorage::Mode::READ);
fs["size"] >> length;
for (int i = 0; i < (int)length; ++i) {
std::string key("image");
std::string index = std::to_string(i);
Mat image;
key = key + index;
fs[key.c_str()] >> image;
std::cout << image.channels() << std::endl;
res.push_back(image);
}
fs.release();
}
catch (Exception e)
{
std::cerr << e.msg << std::endl;
}
}
private:
int flags;
};
}