OpenCv C++: Image Not Warping Correctly

Question

I am learning how to stitch two images together using the below link but whatever I do to calculate the homography and warpPerspective, two images won't stitch together.

https://learnopencv.com/feature-based-image-alignment-using-opencv-c-python/

Below is the source code for image stitching

Include Section

#include <opencv2/features2d.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/core/types.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <vector>
#include <iostream>

Global Variables

using namespace std;
using namespace cv;

const float inlier_threshold = 2.5f; // Distance threshold to identify inliers
const float nn_match_ratio = 0.8f;   // Nearest neighbor matching ratio

Main Function

int main(void)
{
    puts("opening");
    Mat img1 = imread("uttower_right.jpg", IMREAD_GRAYSCALE);   // To be Aligned
    Mat img2 = imread("large2_uttower_left.jpg", IMREAD_GRAYSCALE); // Reference
    Mat img3 = Mat(img2.rows, img2.cols, CV_8UC1);
    //img2.copyTo(img3);

    Mat homography;

    vector<KeyPoint> kpts1, kpts2;
    Mat desc1, desc2;
    puts("Have opened");

    Ptr<AKAZE> akaze = AKAZE::create();
    akaze->detectAndCompute(img1, noArray(), kpts1, desc1);
    akaze->detectAndCompute(img2, noArray(), kpts2, desc2);

    puts("have commputed akaze");

    BFMatcher matcher(NORM_HAMMING);
    vector< vector<DMatch> > nn_matches;
    matcher.knnMatch(desc1, desc2, nn_matches, 2);
    puts("Have done match");

    vector<KeyPoint> matched1, matched2;
    vector<Point2f> inliers1, inliers2;

    for (size_t i = 0; i < nn_matches.size(); i++) {
        DMatch first = nn_matches[i][0];
        float dist1 = nn_matches[i][0].distance;
        float dist2 = nn_matches[i][1].distance;

        if (dist1 < nn_match_ratio * dist2) {
            matched1.push_back(kpts1[first.queryIdx]);
            matched2.push_back(kpts2[first.trainIdx]);

            inliers1.push_back(kpts1[first.queryIdx].pt);
            inliers2.push_back(kpts1[first.trainIdx].pt);
        }

    }
    printf("Matches %d %d\n", matched1.size(), matched2.size());

    homography = findHomography(inliers1, inliers2, RANSAC);
    warpPerspective(img1, img3, homography, img2.size());

    //Display input and output
    imshow("Input1", img1);
    imshow("Input2", img2);
    imshow("Input3", img3);
    waitKey(0);

    return 0;
}

Images used