I'm trying to do object detection, training the SVM. The part of training is ok, he read the 2 images and create a file with the learned information. But when the code execute the predict function, he crash and below i post the error message (that i don't understand).

Do you have any idea why this happen?

include <opencv2 core="" core.hpp="">

include <opencv2 highgui="" highgui.hpp="">

include <opencv2 ml="" ml.hpp="">

include <io.h>

using namespace cv;

int main() {

if(access("learned.svm",0)){
// Set up training data
int width = 1920, height = 1080;

int num_files=2;
std::string files[2]={"tonno1.jpg",
    "tonno2.jpg"};;

int img_area=width*height;
Mat training_mat(num_files,img_area,CV_32FC1);

for(int z=0;z<num_files;z++){
    Mat img_mat = imread(files[z],CV_32FC1);
    int ii = 0; // Current column in training_mat
    for (int i = 0; i<img_mat.rows; i++) {
        for (int j = 0; j < img_mat.cols; j++) {
            training_mat.at<float>(z,ii++) = img_mat.at<uchar>(i,j);
        }
    }
}

Mat labels(num_files,1,CV_32FC1);
labels.at<float>(0,0)=1.0;
labels.at<float>(1,0)=0.0;

// Set up SVM's parameters
CvSVMParams params;
params.svm_type    = CvSVM::C_SVC;
params.kernel_type = CvSVM::POLY;
params.gamma = 3;
params.term_crit   = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
params.degree=10;

// Train the SVM
CvSVM svm;
svm.train(training_mat, labels, Mat(), Mat(), params);
svm.save("learned.svm");

return 1;

}

CvSVM svm;
svm.load("learned.svm");

Mat img;
img=imread("Sequenza 01.Immagine001.jpg",CV_32FC1);

float f=svm.predict(img);
std::cout<<f<<std::endl;

waitKey(0);

}

Here is the image:

I'm trying to do object detection, training the SVM. The part of training is ok, he read the 2 images and create a file with the learned information. But when the code execute the predict function, he crash and below i post the error message (that i don't understand).

Do you have any idea why this happen?

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/ml/ml.hpp>

#include <io.h>

using namespace cv;
 
cv;

int main()
{
 
{

    if(access("learned.svm",0)){
 // Set up training data
 int width = 1920, height = 1080;

 int num_files=2;
 std::string files[2]={"tonno1.jpg",
     "tonno2.jpg"};;

 int img_area=width*height;
 Mat training_mat(num_files,img_area,CV_32FC1);

 for(int z=0;z<num_files;z++){
     Mat img_mat = imread(files[z],CV_32FC1);
     int ii = 0; // Current column in training_mat
     for (int i = 0; i<img_mat.rows; i++) {
         for (int j = 0; j < img_mat.cols; j++) {
             training_mat.at<float>(z,ii++) = img_mat.at<uchar>(i,j);
         }
     }
 }

 Mat labels(num_files,1,CV_32FC1);
 labels.at<float>(0,0)=1.0;
 labels.at<float>(1,0)=0.0;

 // Set up SVM's parameters
 CvSVMParams params;
 params.svm_type    = CvSVM::C_SVC;
 params.kernel_type = CvSVM::POLY;
 params.gamma = 3;
 params.term_crit   = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
 params.degree=10;

 // Train the SVM
 CvSVM svm;
 svm.train(training_mat, labels, Mat(), Mat(), params);
 svm.save("learned.svm");

 return 1;

 }

 CvSVM svm;
 svm.load("learned.svm");

 Mat img;
 img=imread("Sequenza 01.Immagine001.jpg",CV_32FC1);

 float f=svm.predict(img);
 std::cout<<f<<std::endl;

 waitKey(0);

}
 
} 
Here is the image: