Question

我在循环中多次在OpenCV中运行EM算法。最初，EM使用默认初始参数运行。在随后的迭代中，我们基于先前迭代的输出将参数传递给EM算法。这是代码

Mat meansCombine;
Mat weightsCombine;
vector<Mat> covsCombine;
for(int k=maxComponents; k>=minComponents; k--){

    EM model(k,EM::COV_MAT_DIAGONAL,TermCriteria(TermCriteria::COUNT+TermCriteria::EPS,2,0.0001));

    Mat labels;
    Mat probs;
    Mat log_likelihoods;

    if( k==maxComponents )
    {
        model.train(samples,log_likelihoods, labels, probs);
    }
    else
    {
        model.trainE(samples, meansCombine, covsCombine, weightsCombine, log_likelihoods, labels, probs); //provide parameters as per previous iteration results
    }

    double total_likelihood = 0.0;

    for(int i=0;i<log_likelihoods.rows;i++){
        double t = log_likelihoods.at<double>(i,0);
        total_likelihood += t;

    }

    int dimension =3;
    double l = k*(1 + dimension + ((dimension+1)*dimension)/2)-1;
    double penalty = 0.5*l*log(samples.rows*dimension);
    double mdl = -total_likelihood + penalty;
    mdl_output << "********** No. of components=" << k << "***********" << endl;
    mdl_output << "Total log likelihood=" << total_likelihood << endl;
    mdl_output << "Penalty=" << penalty << endl;
    mdl_output << "MDL value=" << mdl << endl;

    if(mdl < minMdl)
    {   
        minMdl = mdl;
        minK = k;
    }

    int c1,c2;
    Mat means = model.get<Mat>("means");
    Mat weights = model.get<Mat>("weights");
    vector<Mat> covs = model.get<vector<Mat> >("covs");

    leastBhattacharyaDist(means,covs,c1,c2);
    mdl_output << "Merging components" << c1 <<" and " << c2 <<endl;

    meansCombine = Mat(means.rows-1,means.cols,means.type());
    weightsCombine = Mat(weights.rows,(weights.cols)-1,weights.type());
    covsCombine.clear();

    mergeComponents(means,covs,weights,c1,c2,meansCombine,covsCombine,weightsCombine);

}

运行此代码会给我以下断言失败消息。

Assertion failed (0 <= _rowRange.start && _rowRange.start <= _rowRange.end && _rowRange.end <= m.rows) in Mat, file /home/one_more_step/Documents/OpenCV/opencv-2.4.7/modules/core/src/matrix.cpp, line 284

无法追踪错误。提前致谢。

Answer 1

断言通常表明以下代码是在考虑某些假设的情况下编写的 - 并且您的参数不符合假设。（你能做的最蠢事就是删除断言 - 是的，代码可能会起作用，但是在所有的假设都没有得到满足之后，你将来会在某个地方射击自己。）

断言有时很复杂，因为它们可能由您无法控制的变量或代码流触发。

通常断言很容易调试。当断言发生时，只需在调试器中运行代码：查看回溯。

回溯将通过您上面显示的代码告诉您调用的位置。

通过沿着回溯的帧步进，您可以检查所有变量的值 - 这将告诉您断言为什么会消失。

Mat OpenCV中断言失败

1 个答案: