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I think this example in C++ should work. Unfortunately I don't know Python DistanceTranform but I think you can use this tutorial in C++ and this one in python to translate it in python. SparseMatrix is only for fun. you don't need it result (in Mat result) is saved in an yml file.

int main(int argc, char* argv[])
{
    Mat img=imread("14878460214049233.jpg",IMREAD_GRAYSCALE);
    imshow("test",img);
    threshold(img,img,200,255,CV_THRESH_BINARY); // to delete some noise
    imshow("test", img);

    Mat labels;
    connectedComponents(img,labels,8,CV_16U);
    Mat result(img.size(),CV_32FC1,Scalar::all(0));
    for (int i = 0; i <= 1; i++)
    {
        Mat mask1 = labels == 1+i;
        Mat mask2 = labels == 1+(1-i);
        Mat masknot;
        bitwise_not(mask1,masknot);
        imshow("masknot", masknot);
        Mat dist;
        distanceTransform(masknot,dist, DIST_L2,5,CV_8U);
        imshow("distance float", dist/255);
        dist.copyTo(result,mask2);

    }
    imshow("distance 1",result);
    FileStorage fs("distCtr.yml",FileStorage::WRITE);
    fs<<"Image"<<result;
    fs.release();
    waitKey();
    SparseMat ms(result);
    SparseMatConstIterator_<float> it = ms.begin<float>(),it_end = ms.end<float>();
    Mat lig(result.rows,1,CV_8U,Scalar::all(0));
    for (; it != it_end; it ++)
    {
        // print element indices and the element value
        const SparseMat::Node* n = it.node();
        if (lig.at<uchar>(n->idx[0])==0)
        {
            cout<< "("<<n->idx[0]<<","<<n->idx[1]<<") = " <<it.value<float>()<<"\t";
            lig.at<uchar>(n->idx[0])=1;
        }
    }
     return 0;
}