94 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			94 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
#include "opencv2/calib3d/calib3d.hpp"
 | 
						|
#include "opencv2/features2d/features2d.hpp"
 | 
						|
#include "opencv2/highgui/highgui.hpp"
 | 
						|
#include "opencv2/imgproc/imgproc.hpp"
 | 
						|
#include "opencv2/nonfree/nonfree.hpp"
 | 
						|
 | 
						|
#include <cstdio>
 | 
						|
 | 
						|
using namespace cv;
 | 
						|
 | 
						|
static void help()
 | 
						|
{
 | 
						|
    printf("Use the SURF descriptor for matching keypoints between 2 images\n");
 | 
						|
    printf("Format: \n./generic_descriptor_match <image1> <image2> <algorithm> <XML params>\n");
 | 
						|
    printf("For example: ./generic_descriptor_match ../c/scene_l.bmp ../c/scene_r.bmp FERN fern_params.xml\n");
 | 
						|
}
 | 
						|
 | 
						|
Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
 | 
						|
                        const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx);
 | 
						|
 | 
						|
int main(int argc, char** argv)
 | 
						|
{
 | 
						|
    if (argc != 5)
 | 
						|
    {
 | 
						|
        help();
 | 
						|
        return 0;
 | 
						|
    }
 | 
						|
 | 
						|
    std::string img1_name = std::string(argv[1]);
 | 
						|
    std::string img2_name = std::string(argv[2]);
 | 
						|
    std::string alg_name = std::string(argv[3]);
 | 
						|
    std::string params_filename = std::string(argv[4]);
 | 
						|
 | 
						|
    Ptr<GenericDescriptorMatcher> descriptorMatcher = GenericDescriptorMatcher::create(alg_name, params_filename);
 | 
						|
    if( descriptorMatcher == 0 )
 | 
						|
    {
 | 
						|
        printf ("Cannot create descriptor\n");
 | 
						|
        return 0;
 | 
						|
    }
 | 
						|
 | 
						|
    //printf("Reading the images...\n");
 | 
						|
    Mat img1 = imread(img1_name, CV_LOAD_IMAGE_GRAYSCALE);
 | 
						|
    Mat img2 = imread(img2_name, CV_LOAD_IMAGE_GRAYSCALE);
 | 
						|
 | 
						|
    // extract keypoints from the first image
 | 
						|
    SURF surf_extractor(5.0e3);
 | 
						|
    vector<KeyPoint> keypoints1;
 | 
						|
 | 
						|
    // printf("Extracting keypoints\n");
 | 
						|
    surf_extractor(img1, Mat(), keypoints1);
 | 
						|
 | 
						|
    printf("Extracted %d keypoints from the first image\n", (int)keypoints1.size());
 | 
						|
 | 
						|
    vector<KeyPoint> keypoints2;
 | 
						|
    surf_extractor(img2, Mat(), keypoints2);
 | 
						|
    printf("Extracted %d keypoints from the second image\n", (int)keypoints2.size());
 | 
						|
 | 
						|
    printf("Finding nearest neighbors... \n");
 | 
						|
    // find NN for each of keypoints2 in keypoints1
 | 
						|
    vector<DMatch> matches2to1;
 | 
						|
    descriptorMatcher->match( img2, keypoints2, img1, keypoints1, matches2to1 );
 | 
						|
    printf("Done\n");
 | 
						|
 | 
						|
    Mat img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, matches2to1);
 | 
						|
 | 
						|
    imshow("correspondences", img_corr);
 | 
						|
    waitKey(0);
 | 
						|
}
 | 
						|
 | 
						|
Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
 | 
						|
                        const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx)
 | 
						|
{
 | 
						|
    Mat part, img_corr(Size(img1.cols + img2.cols, MAX(img1.rows, img2.rows)), CV_8UC3);
 | 
						|
    img_corr = Scalar::all(0);
 | 
						|
    part = img_corr(Rect(0, 0, img1.cols, img1.rows));
 | 
						|
    cvtColor(img1, part, COLOR_GRAY2RGB);
 | 
						|
    part = img_corr(Rect(img1.cols, 0, img2.cols, img2.rows));
 | 
						|
    cvtColor(img1, part, COLOR_GRAY2RGB);
 | 
						|
 | 
						|
    for (size_t i = 0; i < features1.size(); i++)
 | 
						|
    {
 | 
						|
        circle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0));
 | 
						|
    }
 | 
						|
 | 
						|
    for (size_t i = 0; i < features2.size(); i++)
 | 
						|
    {
 | 
						|
        Point pt(cvRound(features2[i].pt.x + img1.cols), cvRound(features2[i].pt.y));
 | 
						|
        circle(img_corr, pt, 3, Scalar(0, 0, 255));
 | 
						|
        line(img_corr, features1[desc_idx[i].trainIdx].pt, pt, Scalar(0, 255, 0));
 | 
						|
    }
 | 
						|
 | 
						|
    return img_corr;
 | 
						|
}
 |