C++ 如何访问OpenCV Matcher上的点位置？

我使用这个FLANN matcher算法来匹配2张图片中的兴趣点（代码如下所示）

有时代码会找到匹配点的列表：

std::vector<DMatch> good_matches;

std:：向量良好匹配；

我想得到两张图片中的点定位（x，y）。创建置换贴图的步骤我如何访问这些点？

干杯

#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"

using namespace cv;

void readme();

/** @function main */
int main(int argc, char** argv) {
    if (argc != 3) {
        readme();
        return -1;
    }

    // Transform in GrayScale
    Mat img_1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
    Mat img_2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE);

    // Checks if the image could be loaded
    if (!img_1.data || !img_2.data) {
        std::cout << " --(!) Error reading images " << std::endl;
        return -1;
    }

    //-- Step 1: Detect the keypoints using SURF Detector
    int minHessian = 400;

    SurfFeatureDetector detector(minHessian);

    std::vector<KeyPoint> keypoints_1, keypoints_2;

    detector.detect(img_1, keypoints_1);
    detector.detect(img_2, keypoints_2);

    //-- Step 2: Calculate descriptors (feature vectors)
    SurfDescriptorExtractor extractor;

    Mat descriptors_1, descriptors_2;

    extractor.compute(img_1, keypoints_1, descriptors_1);
    extractor.compute(img_2, keypoints_2, descriptors_2);

    //-- Step 3: Matching descriptor vectors using FLANN matcher
    FlannBasedMatcher matcher;
    std::vector<DMatch> matches;
    matcher.match(descriptors_1, descriptors_2, matches);

    double max_dist = 0;
    double min_dist = 100;

    //-- Quick calculation of max and min distances between keypoints
    for (int i = 0; i < descriptors_1.rows; i++) {
        double dist = matches[i].distance;
//      printf("-- DISTANCE =  [%f]\n", dist);
        if (dist < min_dist)
            min_dist = dist;
        if (dist > max_dist)
            max_dist = dist;
    }

    printf("-- Max dist : %f \n", max_dist);
    printf("-- Min dist : %f \n", min_dist);

    //-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist )
    //-- PS.- radiusMatch can also be used here.
    std::vector<DMatch> good_matches;

    for (int i = 0; i < descriptors_1.rows; i++) {
        if (matches[i].distance < 2 * min_dist) {
            good_matches.push_back(matches[i]);
        }
    }

    //-- Draw only "good" matches
    Mat img_matches;
    drawMatches(img_1, keypoints_1, img_2, keypoints_2, good_matches,
            img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(),
            DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

    //-- Show detected matches
    imshow("Good Matches", img_matches);

    for (int i = 0; i < good_matches.size(); i++) {
        printf("-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  \n", i,
                good_matches[i].queryIdx, good_matches[i].trainIdx);
    }

    waitKey(0);

    return 0;
}

/** @function readme */
void readme() {
    std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl;
}

#包括
#包括
#包括“opencv2/core/core.hpp”
#包括“opencv2/nonfree/features2d.hpp”
#包括“opencv2/highgui/highgui.hpp”
使用名称空间cv；
无效自述（）；
/**@主功能*/
int main（int argc，字符**argv）{
如果（argc！=3）{
自述文件（）；
返回-1；
}
//灰度变换
Mat img_1=imread（argv[1]，CV_LOAD_IMAGE_GRAYSCALE）；
Mat img_2=imread（argv[2]，CV_LOAD_IMAGE_GRAYSCALE）；
//检查是否可以加载图像
如果（！img_1.data | |！img_2.data）{
std:：cout匹配的_点1和2将是左右图像中的对应点。然后，您可以找到好的_匹配的索引，idx1=好的_匹配[i]。trainIdx用于左图像，idx2=好的_匹配[i].queryIdx获取正确的图像。然后只需将相应的点添加到匹配的_点向量中，即可获得匹配的x、y点向量

long num_matches = good_matches.size();
vector<Point2f> matched_points1;
vector<Point2f> matched_points2;

for (int i=0;i<num_matches;i++)
{
    int idx1=good_matches[i].trainIdx;
    int idx2=good_matches[i].queryIdx;
    matched_points1.push_back(points1[idx1]);
    matched_points2.push_back(points2[idx2]);
}

long num_matches=good_matches.size（）；
向量匹配_点1；
向量匹配_点2；
对于（inti=0；iHi我有一个朋友有同样的问题…只是好奇…问题解决了吗？点不是二维的。它们是一维的。一个“点”二维数组的索引是二维的。与算法检测到的关键点相对应的一维数字是原始图像中的任意二维点。必须有某种方法从描述符中获取二维点。否则，opencv如何绘制描述。这可能是OP所寻找的吗？