OpenCV C++, trouble understanding starter code for DFT - c++

Question

Not quite understanding why this code works:
cv::Mat img = cv::imread('pic.jpg', -1);
cv::Mat padded;
std::uint16_t m = cv::getOptimalDFTSize(img.rows); // This will be 256
std::uint16_t n = cv::getOptimalDFTSize(img.cols); // This will be 256
cv::copyMakeBorder(img, padded, 0, m - img.rows, 0, n - img.cols,
cv::BORDER_CONSTANT, cv::Scalar::all(0)); // With my inputs, this effectively just copies img into padded
cv::Mat planes[] = { cv::Mat_<float>(padded),cv:: Mat::zeros(padded.size(), CV_32F) };
cv::Mat dft_img;
cv::merge(planes, 2, dft_img);
cv::dft(dft_img, dft_img);
cv::split(dft_img, planes);
But this breaks with an exception in memory:
cv::Mat img = cv::imread('pic.jpg', -1); // I know this image is 256x256
cv::Mat dft_img = cv::Mat::zeros(256,256,CV_32F); // Hard coding for simplicity atm
cv::dft(img,dft_img);
I'm having trouble understanding the documentation for dft() https://docs.opencv.org/2.4/modules/core/doc/operations_on_arrays.html#dft,
and other functions and classes for that matter.
I think it has something to do with dft_img not being a multichannel array in the second segment, but I'm lost on how to initialize such an array short of copying the first segment of code.
Secondly, when trying to access either planes[0] or planes[1] and modify their values with:
planes[0].at<double>(indexi,indexj) = 0;
I get another exception in memory, though I also see a new page that says mat.inl.hpp not found. Using Visual Studio, OpenCV 3.4.3, a novice with C++ but intermediate with signal processing, any help is appreciated.

Answer 1

You did not specify what exception you got, but an important point is that input of the dft function must be a floating point number, either 32 bits or 64 bits floating point number. Another point is that try not to use raw arrays if you are not comfortable with c++. I would even suggest that if using c++ is not mandotary, prefer python for OpenCV. Here is a working example dft code:
// read your image
cv::Mat img = cv::imread("a2.jpg", CV_LOAD_IMAGE_GRAYSCALE); // I know this image is 256x256
// convert it to floating point
//normalization is optional(depends on library and you I guess?)
cv::Mat floatImage;
img.convertTo(floatImage, CV_32FC1, 1.0/255.0);
// create a placeholder Mat variable to hold output of dft
std::vector<cv::Mat> dftOutputs;
dftOutputs.push_back(floatImage);
dftOutputs.push_back(cv::Mat::zeros(floatImage.size(), CV_32F));
cv::Mat dftOutput;
cv::merge(dftOutputs, dftOutput);
// perform dft
cv::dft(dftOutput, dftOutput);
// separate real and complex outputs back
cv::split(dftOutput, dftOutputs);
I changed code from the tutorial a little to make it easier to understand. If you would like to obtain magnitude image and such, you can follow the tutorial after split function.