Question

我有vector<vector<float> >大小 1800 * 160 的功能现在我需要火车svm，我尝试使用OPENCV SVM但是在调试模式下svm-＆gt;火车返回false并且在释放模式这个例子提出：

Exception thrown at 0x00007FFF587AC387 (vcruntime140.dll):Access violation reading location 0x00000048B7FED000.

我的代码：

void Classifier::trainSVM(vector<vector<float> > data,cv::Mat Lable)
{
    // Train the SVM
    cv::Ptr<cv::ml::SVM> svm = cv::ml::SVM::create();
    svm->setType(cv::ml::SVM::C_SVC);
    svm->setKernel(cv::ml::SVM::LINEAR);
    svm->setTermCriteria(cv::TermCriteria(cv::TermCriteria::MAX_ITER, 50000, 1e-6));
    cv::Mat trainingData = cv::Mat(data.size(), 160, CV_32FC1, data.data());
    std::cout << "\nBegan Training Svm in vector faces.";
    bool trained = svm->train(trainingData, cv::ml::ROW_SAMPLE, Lable);
    if (trained)
        svm->save("svm_data.xml");
    std::cout << "\nEnd Training Svm in vector faces.";

}

Answer 1

感谢berak的solution

你的vector<vector<float>>是罪魁祸首，opencv的机器学习期望单个Mat具有连续数据。

你需要将它复制到Mat中，每个向量都在一行上，可能是这样的：

vector<vector<float>> vf {{1,2,3},{4,5,6},{7,8,9}}; // demo data

Mat data;
for ( auto v : vf ) {
    Mat row = Mat(v, true).reshape(1,1); // deep copy, reshape to row
    data.push_back(row);
}

cerr << data << endl;

[1, 2, 3;
 4, 5, 6;
 7, 8, 9]

svm-＆gt;用火车训练异常

1 个答案: