use Keras Model in C plus plus

kerasModelInCpp.cpp

#include <iostream>
#include <fdeep/fdeep.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <filesystem>
#include <exception>
using namespace stdext;
namespace fs = std::filesystem;
int main()
{
    

        std::string test_image_folder_path = "d:/catdog/"; // path to folder containing test images
        const auto mymodel = fdeep::load_model("D:/CatDogNew.json"); // load the converted model
        for (const auto& entry : fs::directory_iterator(test_image_folder_path)) {
           try
             { 
                    std::string image_path = entry.path().string(); // get images path one by one
                    const cv::Mat image = cv::imread(image_path, cv::IMREAD_GRAYSCALE);  // read the image in single channel grayscale mode 
                   
                    cv::Mat resizedImg;
                    cv::resize(image, resizedImg, cv::Size(128, 128)); // resize image to the 128x128 (Model input dimension)
                    imshow("Display Window", resizedImg); // just show the image

                    // convert cv::MAT to fdeep::tensor
                    const auto input = fdeep::tensor_from_bytes(resizedImg.ptr(),
                        static_cast<std::size_t>(resizedImg.rows),
                        static_cast<std::size_t>(resizedImg.cols),
                        static_cast<std::size_t>(resizedImg.channels()),
                        0.0f, 1.0f); 

                    auto result = mymodel.predict({ input }); // predict the image's label and ouput a 1x2 tensor containing each class probability
                    std::cout << fdeep::show_tensors(result) << std::endl; // print the tensor
                    cv::waitKey();
        }
        catch (const std::exception& e)
        {
            std::cout << e.what() << '\n';
        }
    }
    

}

is it possible to use this example with image output?

is it possible to use this example with image output?

visit https://mshaeri.com/blog/tensorflow-keras-train-in-python-predict-use-in-c-plus/

please

yes, I checked it but I have still always had the same issue.