Code
====
-This tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp>`_
+This tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp>`_
- .. code-block:: cpp
-
- #include <stdio.h>
- #include <iostream>
- #include "opencv2/core/core.hpp"
- #include "opencv2/features2d/features2d.hpp"
- #include "opencv2/highgui/highgui.hpp"
- #include "opencv2/nonfree/nonfree.hpp"
-
- using namespace cv;
-
- void readme();
-
- /** @function main */
- int main( int argc, char** argv )
- {
- if( argc != 3 )
- { readme(); return -1; }
-
- Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
- Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
-
- 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)
- SurfDescriptorExtractor extractor;
-
- 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 = 100;
-
- //-- 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 );
-
- 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);
-
- return 0;
- }
-
- /** @function readme */
- void readme()
- { std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }
+ .. literalinclude:: ../../../../samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp
+ :language: cpp
Explanation
============