编写以下代码：C++，OpenCV4.6，显示两张图片特征点连线图

以下是基于OpenCV4.6的C++代码，可以显示两张图片的特征点连线图：

#include <opencv2/opencv.hpp>

using namespace cv;

int main()
{
    // 读取两张需要匹配的图片
    Mat img1 = imread("img1.jpg", IMREAD_GRAYSCALE);
    Mat img2 = imread("img2.jpg", IMREAD_GRAYSCALE);

    // 提取图片的特征点
    Ptr<FeatureDetector> detector = ORB::create();
    std::vector<KeyPoint> keypoints1, keypoints2;
    detector->detect(img1, keypoints1);
    detector->detect(img2, keypoints2);

    // 计算特征点的描述符
    Ptr<DescriptorExtractor> extractor = ORB::create();
    Mat descriptors1, descriptors2;
    extractor->compute(img1, keypoints1, descriptors1);
    extractor->compute(img2, keypoints2, descriptors2);

    // 匹配特征点
    Ptr<DescriptorMatcher> matcher = BFMatcher::create(NORM_HAMMING, true);
    std::vector<DMatch> matches;
    matcher->match(descriptors1, descriptors2, matches);

    // 选择最优的匹配
    double min_dist = 1000000;
    for (int i = 0; i < descriptors1.rows; i++)
    {
        double dist = matches[i].distance;
        if (dist < min_dist) min_dist = dist;
    }
    std::vector<DMatch> good_matches;
    for (int i = 0; i < descriptors1.rows; i++)
    {
        if (matches[i].distance < 3 * min_dist)
        {
            good_matches.push_back(matches[i]);
        }
    }

    // 绘制特征点连线图
    Mat img_matches;
    drawMatches(img1, keypoints1, img2, keypoints2, good_matches, img_matches);
    imshow("Matches", img_matches);
    waitKey(0);

    return 0;
}

注意，这段代码使用了ORB算法提取特征点，并使用了BFMatcher计算特征点之间的匹配关系。如果需要使用其他算法，可以将代码中的ORB::create()和BFMatcher::create()替换为其他算法的接口。