calcCovarMatrix.cpp

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#include "mexopencv.hpp"
using namespace std;
using namespace cv;

void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
    // Check the number of arguments
    nargchk(nrhs>=1 && (nrhs%2)==1 && nlhs<=2);

    // Argument vector
    vector<MxArray> rhs(prhs, prhs+nrhs);

    // Option processing
    Mat mean;
    int flags = cv::COVAR_NORMAL | cv::COVAR_ROWS;
    int ctype = CV_64F;
    for (int i=1; i<nrhs; i+=2) {
        string key(rhs[i].toString());
        if (key == "Mean") {
            mean = rhs[i+1].toMat();
            flags |= cv::COVAR_USE_AVG;
        }
        else if (key == "Flags")
            flags = rhs[i+1].toInt();
        else if (key == "Scrambled") {
            //UPDATE_FLAG(flags, rhs[i+1].toBool(), cv::COVAR_SCRAMBLED);
            UPDATE_FLAG(flags, !rhs[i+1].toBool(), cv::COVAR_NORMAL);
        }
        else if (key == "Normal")
            UPDATE_FLAG(flags, rhs[i+1].toBool(), cv::COVAR_NORMAL);
        else if (key == "UseAvg")
            UPDATE_FLAG(flags, rhs[i+1].toBool(), cv::COVAR_USE_AVG);
        else if (key == "Scale")
            UPDATE_FLAG(flags, rhs[i+1].toBool(), cv::COVAR_SCALE);
        else if (key == "Rows") {
            UPDATE_FLAG(flags, rhs[i+1].toBool(), cv::COVAR_ROWS);
            UPDATE_FLAG(flags, !rhs[i+1].toBool(), cv::COVAR_COLS);
        }
        else if (key == "Cols") {
            UPDATE_FLAG(flags, rhs[i+1].toBool(), cv::COVAR_COLS);
            UPDATE_FLAG(flags, !rhs[i+1].toBool(), cv::COVAR_ROWS);
        }
        else if (key == "CType")
            ctype = (rhs[i+1].isChar()) ?
                ClassNameMap[rhs[i+1].toString()] : rhs[i+1].toInt();
        else
            mexErrMsgIdAndTxt("mexopencv:error",
                "Unrecognized option %s", key.c_str());
    }

    // Process
    Mat samples(rhs[0].toMat()), covar;
    calcCovarMatrix(samples, covar, mean, flags, ctype);
    plhs[0] = MxArray(covar);
    if (nlhs>1)
        plhs[1] = MxArray(mean);
}