【问题标题】：Training an SVM using hu moments使用 hu 矩训练 SVM
【发布时间】：2016-03-29 06:50:54
【问题描述】：

我正在学习 SVM，因此我制作了一个示例程序来训练 SVM 以检测符号是否在图像中。所有图像都是黑白的（符号为黑色，背景为白色）。我有 12 个训练图像，6 个正面（带有符号）和 6 个负面（没有它）。我使用hu moments 来获取每个图像的描述符，然后用这些描述符构建训练矩阵。我还有一个Labels 矩阵，其中包含每个图像的标签：如果是正则为 1，如果为负则为 0。但是我在训练 SVM 的那一行出现错误（类似于分段错误）。这是我的代码：

using namespace cv;
using namespace std;

int main(int argc, char* argv[])
{
    //arrays where the labels and the features will be stored
    float labels[12] ;
    float trainingData[12][7] ;

    Moments moment;
    double hu[7];

  //===============extracting the descriptos for each positive image=========
    for ( int i = 0; i <= 5; i++){

        //the images are called t0.png ... t5.png and are in the folder train
        std::string path("train/t");
        path += std::to_string(i);
        path += ".png";

        Mat input = imread(path, 0); //read the images
        bitwise_not(input, input); //invert black and white
        Mat BinaryInput;
        threshold(input, BinaryInput, 100, 255, cv::THRESH_BINARY); //apply theshold

        moment = moments(BinaryInput, true); //calculate the moments of the current image
        HuMoments(moment, hu); //calculate the hu moments (this will be our descriptor)

        //setting the row i of the training data as the hu moments
        for (int j = 0; j <= 6; j++){
            trainingData[i][j] = (float)hu[j];
        }

        labels[i] = 1; //label=1 because is a positive image
    }

  //===============extracting the descriptos for each negative image=========
    for (int i = 0; i <= 5; i++){

        //the images are called tn0.png ... tn5.png and are in the folder train
        std::string path("train/tn");
        path += std::to_string(i);
        path += ".png";

        Mat input = imread(path, 0); //read the images
        bitwise_not(input, input); //invert black and white
        Mat BinaryInput;
        threshold(input, BinaryInput, 100, 255, cv::THRESH_BINARY); //apply theshold

        moment = moments(BinaryInput, true); //calculate the moments of the current image
        HuMoments(moment, hu); //calculate the hu moments (this will be our descriptor)

        for (int j = 0; j <= 6; j++){
            trainingData[i + 6][j] = (float)hu[j];
        }

         labels[i + 6] = 0;  //label=0 because is a negative image

    }
    
//===========================training the SVM================
    //we convert the labels and trainingData matrixes to Mat objects
    Mat labelsMat(12, 1, CV_32FC1, labels);
    Mat trainingDataMat(12, 7, CV_32FC1, trainingData);

    //create the SVM
    Ptr<ml::SVM> svm = ml::SVM::create();
    
    //set the parameters of the SVM
    svm->setType(ml::SVM::C_SVC);
    svm->setKernel(ml::SVM::LINEAR);
    CvTermCriteria criteria = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
    svm->setTermCriteria(criteria);

     //Train the SVM !!!!!HERE OCCURS THE ERROR!!!!!!
     svm->train(trainingDataMat, ml::ROW_SAMPLE, labelsMat);


    //Testing the SVM...
    Mat test = imread("train/t1.png", 0); //this should be a positive test
    bitwise_not(test, test);
    Mat testBin;
    threshold(test, testBin, 100, 255, cv::THRESH_BINARY);

    Moments momentP = moments(testBin, true); //calculate the moments of the test image

    double huP[7];
    HuMoments(momentP, huP);

    Mat testMat(1, 7, CV_32FC1, huP); //setting the hu moments to the test matrix

    double resp = svm->predict(testMat); //pretiction of the SVM
    printf("%f", resp); //Response

    getchar();

}

我知道该程序在该行之前运行良好，因为我打印了 labelsMat 和 trainingDataMat 并且其中的值正常。即使在控制台中，我也可以看到程序运行良好，直到执行该确切的行。控制台然后显示此消息：

OpenCV error: Bad argument (in the case of classification problem the responses must be categorical;  either specify varType when creating TrainDatam or pass integer responses)

我真的不知道这意味着什么。知道什么可能导致问题吗？如果您需要任何其他详细信息，请告诉我。