Open Source Computer Vision Library https://opencv.org/
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#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.empty() )
{
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;
}