写一个改进后的orb算法c++代码，要求：1 在orb算法中加入shi-tomasi算法

以下是一个改进后的ORB算法代码，它包括了Shi-Tomasi算法：

#include <opencv2/opencv.hpp>
#include <vector>
#include <iostream>

using namespace cv;
using namespace std;

void cornerSubPix_wrapper(const Mat& gray, vector<Point2f>& corners, Size winSize, Size zeroZone, TermCriteria criteria)
{
    cornerSubPix(gray, corners, winSize, zeroZone, criteria);
}

vector<KeyPoint> myORB(const Mat& img, int nfeatures = 500, float scaleFactor = 1.2f, int nlevels = 8,
                       int edgeThreshold = 31, int firstLevel = 0, int WTA_K = 2, int scoreType = ORB::HARRIS_SCORE,
                       int patchSize = 31, int fastThreshold = 20, double minDistance = 10.0, bool useShiTomasi = true)
{
    // 灰度图
    Mat gray;
    cvtColor(img, gray, COLOR_BGR2GRAY);

    // 角点检测
    vector<Point2f> corners;
    if (useShiTomasi)
    {
        // Shi-Tomasi角点检测
        goodFeaturesToTrack(gray, corners, nfeatures, 0.01, minDistance);
        // 亚像素级别的精度
        cornerSubPix_wrapper(gray, corners, Size(3, 3), Size(-1, -1), TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 30, 0.1));
    }
    else
    {
        // Harris角点检测
        cornerHarris(gray, gray, 2, 3, 0.04);
        // 非极大值抑制
        Mat dst_norm, dst_norm_scaled;
        normalize(gray, dst_norm, 0, 255, NORM_MINMAX, CV_32FC1, Mat());
        convertScaleAbs(dst_norm, dst_norm_scaled);
        for (int i = 0; i < dst_norm.rows; i++)
        {
            for (int j = 0; j < dst_norm.cols; j++)
            {
                if (dst_norm.at<float>(i, j) > edgeThreshold)
                {
                    corners.push_back(Point2f(j, i));
                }
            }
        }
    }

    // ORB描述子
    vector<KeyPoint> keypoints;
    for (const auto& pt : corners)
    {
        keypoints.emplace_back(pt, patchSize);
    }
    Ptr<ORB> orb = ORB::create(nfeatures, scaleFactor, nlevels, edgeThreshold, firstLevel, WTA_K, scoreType, patchSize);
    Mat descriptors;
    orb->compute(img, keypoints, descriptors);

    // 绘制角点
    Mat img_with_corners;
    drawKeypoints(img, keypoints, img_with_corners);
    imshow("ORB with Shi-Tomasi", img_with_corners);
    waitKey(0);

    return keypoints;
}

int main()
{
    Mat img = imread("test.png");
    vector<KeyPoint> keypoints = myORB(img);

    return 0;
}

这个改进的ORB算法代码中，我们在角点检测部分加入了Shi-Tomasi算法。如果`useShiTomasi`参数为`true`，则使用Shi-Tomasi算法进行角点检测；如果为`false`，则使用Harris角点检测。在使用Shi-Tomasi算法时，我们还使用了`cornerSubPix`函数对检测到的角点进行了亚像素级别的精度提升。