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BFMatcher knnMatch

I try to implement knnMatch on BFMatcher as follows:

BFMatcher matcher(NORM_L2, true);
vector<DMatch> matches;
//matcher.match(descriptors1, descriptors2, matches);
matcher.knnMatch(descriptors1, descriptors2, matches, 2);

And receive the following error:

fiducialMain.cpp: In function ‘void fiducialCalc(cv::Mat, cv::Mat, cv::Mat&, cv::Mat&, int&)’:
fiducialMain.cpp:98:56: error: no matching function for call to ‘cv::BFMatcher::knnMatch(cv::Mat&, cv::Mat&, std::vector<cv::DMatch>&, int)’
  matcher.knnMatch(descriptors1, descriptors2, matches,2);
                                                        ^
fiducialMain.cpp:98:56: note: candidates are:
In file included from fiducialMain.cpp:15:0:
/usr/local/include/opencv2/features2d/features2d.hpp:1116:18: note: void cv::DescriptorMatcher::knnMatch(const cv::Mat&, const cv::Mat&, std::vector<std::vector<cv::DMatch> >&, int, const cv::Mat&, bool) const
     CV_WRAP void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
                  ^
/usr/local/include/opencv2/features2d/features2d.hpp:1116:18: note:   no known conversion for argument 3 from ‘std::vector<cv::DMatch>’ to ‘std::vector<std::vector<cv::DMatch> >&’
/usr/local/include/opencv2/features2d/features2d.hpp:1130:18: note: void cv::DescriptorMatcher::knnMatch(const cv::Mat&, std::vector<std::vector<cv::DMatch> >&, int, const std::vector<cv::Mat>&, bool)
     CV_WRAP void knnMatch( const Mat& queryDescriptors, CV_OUT vector<vector<DMatch> >& matches, int k,
                  ^
/usr/local/include/opencv2/features2d/features2d.hpp:1130:18: note:   no known conversion for argument 2 from ‘cv::Mat’ to ‘std::vector<std::vector<cv::DMatch> >&’

Can anybody explain this error?

like image 965
P3d0r Avatar asked Dec 12 '22 00:12

P3d0r


1 Answers

please have another look at the docs

while the ordinary match function has a vector<DMatch> as result,

knnMatch (say loud : k-nearest-neighbours !) results in several(k) vectors, thus you need a :

vector< vector< DMatch > > matches

for the result

like image 101
berak Avatar answered Dec 31 '22 00:12

berak