opencv sift match

#include "opencvlib.h"
using namespace cv;

int main()
{
Mat img_1 = cv::imread("1.png");
Mat img_2 = cv::imread("2.png");

imshow("img1", img_1);
imshow("img2", img_2);

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)
SiftDescriptorExtractor extractor;
//SurfDescriptorExtractor
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 = 1000;

//-- Quick calculation of max and min distances between keypoints
for (int i = 0; i < descriptors_1.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);

//-- 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);
imwrite("matchs.jpg", 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);

system("pause");

return 0;
}