Question

我正在尝试运行冲浪代码：

我有以下问题。

1：我希望获得有限的关键点（例如1000），如SIFT实现。是否有任何内置函数或者必须编写自己的函数。

2：我画的很好。它工作正常，但我想绘制 与绿色匹配良好，与红线匹配（匹配 - 匹配） 在同一张图片上（'Match_SURF.jpg'）。

#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/line_descriptor.hpp"
#include "opencv2\features2d\features2d.hpp"
#include "opencv2/xfeatures2d.hpp"
#include "opencv2\xfeatures2d\nonfree.hpp"
#include "opencv2/imgproc.hpp"
    using namespace cv;
    void readme();

    /** @function main */
    int main(int argc, char** argv)
    {


        Mat img_object = imread("C:\\VC_examples\\IMG_0030.jpg", CV_LOAD_IMAGE_GRAYSCALE);
        Mat img_scene = imread("C:\\VC_examples\\IMG_0031.jpg", CV_LOAD_IMAGE_GRAYSCALE);

        if (!img_object.data || !img_scene.data)
        {
            std::cout << " --(!) Error reading images " << std::endl; return -1;
        }

        //-- Step 1: Detect the keypoints using SURF Detector
        int minHessian = 500;
        cv::Ptr<Feature2D> detector = xfeatures2d::SURF::create(minHessian);

        std::vector<KeyPoint> keypoints_object, keypoints_object;
        std::vector<KeyPoint> keypoints_scene, keypoints_scene;

        detector->detect(img_object, keypoints_object);
        detector->detect(img_scene, keypoints_scene);


    //-- Step 2: Calculate descriptors (feature vectors)    
    Mat descriptors_object, descriptors_scene;

    detector->compute(img_scene, keypoints_scene, descriptors_scene);
    detector->compute(img_object, keypoints_object, descriptors_object);

    //-- Step 3: Matching descriptor vectors using BFMatcher :
    BFMatcher matcher;
    std::vector< DMatch > matches;
    matcher.match(descriptors_object, descriptors_scene, matches);        

    double max_dist = 0; double min_dist = 100;

    //-- Quick calculation of max and min distances between keypoints
    for (int i = 0; i < descriptors_object.rows; i++)
    {
        double dist = matches[i].distance;
        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);

绘制“好”匹配和不匹配

    //-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
    std::vector< DMatch > good_matches;

    for (int i = 0; i < descriptors_object.rows; i++)
    {
        if (matches[i].distance < 3 * min_dist)
        {
            good_matches.push_back(matches[i]);
        }
    }

    Mat img_matches;
    drawMatches(img_object, keypoints_object, img_scene, keypoints_scene,
        good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
        std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);


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

保存图片

imwrite("Match_SURF.jpg", img_matches);**

    waitKey(0);
    return 0;
}

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

有什么想法吗？

SURF，用于限制关键点，绘图匹配的内置函数

0 个答案: