openCV k-means调用断言失败

该断言告诉您：

1. 类型必须CV_32S在您的代码中似乎是这种情况，也许您的if语句为false，因为类型已自动更改为CV_32SC1？不知道...

2. 您可以将每个点放置在一行或一列中，因此is set to 1必须将行/列和另一维设置为data.rows，以指示data您要聚类的点以将每个点放置在行中的格式保存，从而导致#points行。因此，使该断言消失的错误似乎CvMat* labels = cvCreateMat(1, points->cols, CV_32S);应该CvMat* labels = cvCreateMat(1, points->rows, CV_32S);改为，但从points概念上来说，您的使用似乎是错误的。

您可能必须将您的观点（您想聚类）放在cvMatwithn rows和2 cols of type CV_32FC1or中1 col and type CV_32FC2（也许两个版本都可以使用，也许只有一个版本，或者在那儿我完全错了）。

编辑：我写了一个对我有用的简短代码段：

// here create the data array where your input points will be hold:
CvMat* points = cvCreateMat( numberOfPoints , 2 /* 2D points*/ , CV_32F);

// this is a float array of the 
float* pointsDataPtr = points->data.fl;
// fill the mat:
for(unsigned int r=0; r<samples.size(); ++r)
{
    pointsDataPtr[2*r] = samples.at(r).x; // this is the x coordinate of your r-th point
    pointsDataPtr[2*r+1] = samples.at(r).y; // this is the y coordinate of your r-th point
}


// this is the data array for the labels, which will be the output of the method.
CvMat* labels = cvCreateMat(1, points->rows, CV_32S);
// this is the quit criteria, which I did neither check nor modify, just used your version here.
CvTermCriteria criteria = cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 10, 1.0);

// call the method for 2 cluster
cvKMeans2(points, 2, labels, criteria);

// now labels holds numberOfPoints labels which have either value 0 or 1 since we searched for 2 cluster

int* labelData = labels->data.i; // array to the labels
for(unsigned int r=0; r<samples.size(); ++r)
{
    int labelOfPointR = labelData[r]; // this is the value of the label of point number r

    // here I use c++ API to draw the points, do whatever else you want to do with the label information (in C API). I choose different color for different labels.
    cv::Scalar outputColor;
    switch(labelOfPointR)
    {
        case 0: outputColor = cv::Scalar(0,255,0); break;
        case 1: outputColor = cv::Scalar(0,0,255); break;
        default: outputColor = cv::Scalar(255,0,255); break;    // this should never happen for 2 clusters...
    }
    cv::circle(outputMat, samples.at(r), 2, outputColor);
}

给我一些生成的点数据的结果：

也许您也需要这些中心，C API为您提供了返回它们的选项，但没有检查它的工作方式。