Panorama with SIFT algorithm

Now, I work for a vision company. I should use OpenCV because this fantastic open-source library is dedicated to this field. But I am quite productive with Population, so I test it! Oke, it is not optimized as OpenCV (no platform primitive optimization). However, I get some very nice results. For I project, I have to create a panorama as in this article and from these images

photo2
photo3

photo4
I get this result:
panorama

#include"Population.h"//Single header
using namespace pop;//Population namespace
int main(){
        std::string path= "D:/Users/vtariel/Downloads/";
        Mat2RGBUI8 img3;
        img3.load(path+"Photo1.jpg");
        Mat2RGBUI8 img4;
        img4.load(path+"Photo2.jpg");
        Mat2RGBUI8 img5;
        img5.load(path+"Photo3.jpg");

        Mat2RGBUI8 img6;
        img6.load(path+"Photo4.jpg");
        Vec<Mat2RGBUI8> vv;

        vv.push_back(img4);
        vv.push_back(img5);
        vv.push_back(img6);

        Mat2RGBUI8 panoimg =Feature::panoramic(vv);
        panoimg.display();    
}
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