在opencv中为图像训练svm

Question

I have already reffered to the following links: Link 1 and Link 2

From the above i have to managed to write the following :

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

using namespace cv;
using namespace std;

int main(){
    int num_files = 2;
    int width = 128, height = 128;

    Mat image[2];
    image[0] = imread("Tomato.jpg");
    image[1] = imread("Melon.jpg");

    Mat new_image(2,height*width,CV_32FC1); //Training sample from input images

    int ii = 0;
    for (int i = 0; i < num_files; i++){
        Mat temp = image[i];
        ii = 0;
        for (int j = 0; j < temp.rows; j++){
            for (int k = 0; k < temp.cols; k++){
                new_image.at<float>(i, ii++) = temp.at<uchar>(j, k);
            }
        }
    }
    //new_image.push_back(image[0].reshape(0, 1));
    //new_image.push_back(image[1].reshape(0, 1));
    Mat labels(num_files, 1, CV_32FC1);
    labels.at<float>(0, 0) = 1.0;//tomato
    labels.at<float>(1, 0) = -1.0;//melon

    imshow("New image", new_image);
    printf("%f %f", labels.at<float>(0, 0), labels.at<float>(1, 0));

    CvSVMParams params;
    params.svm_type = CvSVM::C_SVC;
    params.kernel_type = CvSVM::LINEAR;
    params.gamma = 3;
    params.degree = 3;
    params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
    CvSVM svm;
    svm.train(new_image, labels, Mat(), Mat(), params);

    svm.save("svm.xml"); // saving
    svm.load("svm.xml"); // loading

    Mat test_img = imread("Tomato.jpg");
    test_img=test_img.reshape(0, 1);
    imshow("shit_image", test_img);
    test_img.convertTo(test_img, CV_32FC1);
    svm.predict(test_img);

    waitKey(0);
}

I get the following error:

unsupported format or combination of formats, input sample must have 32FC1 type in cvPreparePredictData ...

I followed all steps in the second link. All matrices are 32FC1 type. What am I missing? Is there something wrong with the svm parameters ? The error is caused when i try to predict a result.

Answer 1

check

1) Tomato.jpg and Melon.jpg size is 128*128 ?
2) both images are grayscale?

if not. try this code:
I just add resize(), cvtColor() and print result

 #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/ml/ml.hpp> #include <opencv2\\imgproc\\imgproc.hpp> using namespace cv; using namespace std; int main(){ int num_files = 2; int width = 128, height = 128; Mat image[2]; image[0] = imread("Tomato.jpg", 0); image[1] = imread("Melon.jpg", 0); resize(image[0], image[0], Size(width, height)); resize(image[1], image[1], Size(width, height)); Mat new_image(2, height*width, CV_32FC1); //Training sample from input images int ii = 0; for (int i = 0; i < num_files; i++){ Mat temp = image[i]; ii = 0; for (int j = 0; j < temp.rows; j++){ for (int k = 0; k < temp.cols; k++){ new_image.at<float>(i, ii++) = temp.at<uchar>(j, k); } } } //new_image.push_back(image[0].reshape(0, 1)); //new_image.push_back(image[1].reshape(0, 1)); Mat labels(num_files, 1, CV_32FC1); labels.at<float>(0, 0) = 1.0;//tomato labels.at<float>(1, 0) = -1.0;//melon imshow("New image", new_image); printf("%f %f", labels.at<float>(0, 0), labels.at<float>(1, 0)); CvSVMParams params; params.svm_type = CvSVM::C_SVC; params.kernel_type = CvSVM::LINEAR; params.gamma = 3; params.degree = 3; params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6); CvSVM svm; svm.train(new_image, labels, Mat(), Mat(), params); svm.save("svm.xml"); // saving svm.load("svm.xml"); // loading Mat test_img = imread("Tomato.jpg", 0); resize(test_img, test_img, Size(width, height)); test_img = test_img.reshape(0, 1); imshow("shit_image", test_img); test_img.convertTo(test_img, CV_32FC1); float res = svm.predict(test_img); if (res > 0) cout << endl << "Tomato"; else cout << endl << "Melon"; waitKey(0); }