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#include <iostream>
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#include "opencv2/core.hpp"
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#ifdef HAVE_OPENCV_XFEATURES2D
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#include "opencv2/highgui.hpp"
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#include "opencv2/features2d.hpp"
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#include "opencv2/xfeatures2d.hpp"
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using namespace cv;
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using namespace cv::xfeatures2d;
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using std::cout;
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using std::endl;
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const char* keys =
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"{ help h | | Print help message. }"
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"{ input1 | box.png | Path to input image 1. }"
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"{ input2 | box_in_scene.png | Path to input image 2. }";
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int main( int argc, char* argv[] )
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{
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CommandLineParser parser( argc, argv, keys );
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Mat img1 = imread( samples::findFile( parser.get<String>("input1") ), IMREAD_GRAYSCALE );
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Mat img2 = imread( samples::findFile( parser.get<String>("input2") ), IMREAD_GRAYSCALE );
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if ( img1.empty() || img2.empty() )
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{
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cout << "Could not open or find the image!\n" << endl;
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parser.printMessage();
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return -1;
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}
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//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
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int minHessian = 400;
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Ptr<SURF> detector = SURF::create( minHessian );
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std::vector<KeyPoint> keypoints1, keypoints2;
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Mat descriptors1, descriptors2;
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detector->detectAndCompute( img1, noArray(), keypoints1, descriptors1 );
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detector->detectAndCompute( img2, noArray(), keypoints2, descriptors2 );
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//-- Step 2: Matching descriptor vectors with a brute force matcher
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// Since SURF is a floating-point descriptor NORM_L2 is used
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Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create(DescriptorMatcher::BRUTEFORCE);
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std::vector< DMatch > matches;
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matcher->match( descriptors1, descriptors2, matches );
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//-- Draw matches
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Mat img_matches;
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drawMatches( img1, keypoints1, img2, keypoints2, matches, img_matches );
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//-- Show detected matches
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imshow("Matches", img_matches );
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waitKey();
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return 0;
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}
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#else
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int main()
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{
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std::cout << "This tutorial code needs the xfeatures2d contrib module to be run." << std::endl;
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return 0;
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}
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#endif
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