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updated example with proper distance results in CV_32F when binary is detected

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git-svn-id: http://find-object.googlecode.com/svn/trunk/find_object@275 620bd6b2-0a58-f614-fd9a-1bd335dccda9
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matlabbe 2014-05-14 18:58:15 +00:00
parent 6d2705846a
commit 96462e0ec8
1 changed files with 12 additions and 14 deletions
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26
example/main.cpp
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@ -96,17 +96,15 @@ int main(int argc, char * argv[])
cv::Mat results; cv::Mat results;
cv::Mat dists; cv::Mat dists;
std::vector<std::vector<cv::DMatch> > matches; std::vector<std::vector<cv::DMatch> > matches;
bool isBinaryDescriptors;
int k=2; // find the 2 nearest neighbors int k=2; // find the 2 nearest neighbors
bool useBFMatcher = false; // SET TO TRUE TO USE BRUTE FORCE MATCHER (may give better results with binary descriptors) bool useBFMatcher = false; // SET TO TRUE TO USE BRUTE FORCE MATCHER
if(objectDescriptors.type()==CV_8U) if(objectDescriptors.type()==CV_8U)
{ {
// Binary descriptors detected (from ORB, Brief, BRISK, FREAK) // Binary descriptors detected (from ORB, Brief, BRISK, FREAK)
printf("Binary descriptors detected...\n"); printf("Binary descriptors detected...\n");
isBinaryDescriptors = true;
if(useBFMatcher) if(useBFMatcher)
{ {
cv::BFMatcher matcher(cv::NORM_HAMMING); cv::BFMatcher matcher(cv::NORM_HAMMING); // use cv::NORM_HAMMING2 for ORB descriptor with WTA_K == 3 or 4 (see ORB constructor)
matcher.knnMatch(objectDescriptors, sceneDescriptors, matches, k); matcher.knnMatch(objectDescriptors, sceneDescriptors, matches, k);
} }
else else
@ -114,8 +112,6 @@ int main(int argc, char * argv[])
// Create Flann LSH index // Create Flann LSH index
cv::flann::Index flannIndex(sceneDescriptors, cv::flann::LshIndexParams(12, 20, 2), cvflann::FLANN_DIST_HAMMING); cv::flann::Index flannIndex(sceneDescriptors, cv::flann::LshIndexParams(12, 20, 2), cvflann::FLANN_DIST_HAMMING);
printf("Time creating FLANN LSH index = %d ms\n", time.restart()); printf("Time creating FLANN LSH index = %d ms\n", time.restart());
results = cv::Mat(objectDescriptors.rows, k, CV_32SC1); // Results index
dists = cv::Mat(objectDescriptors.rows, k, CV_32FC1); // Distance results are CV_32FC1 ?!?!? NOTE OpenCV doc is not clear about that...
// search (nearest neighbor) // search (nearest neighbor)
flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() ); flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
@ -125,7 +121,6 @@ int main(int argc, char * argv[])
{ {
// assume it is CV_32F // assume it is CV_32F
printf("Float descriptors detected...\n"); printf("Float descriptors detected...\n");
isBinaryDescriptors = false;
if(useBFMatcher) if(useBFMatcher)
{ {
cv::BFMatcher matcher(cv::NORM_L2); cv::BFMatcher matcher(cv::NORM_L2);
@ -136,8 +131,6 @@ int main(int argc, char * argv[])
// Create Flann KDTree index // Create Flann KDTree index
cv::flann::Index flannIndex(sceneDescriptors, cv::flann::KDTreeIndexParams(), cvflann::FLANN_DIST_EUCLIDEAN); cv::flann::Index flannIndex(sceneDescriptors, cv::flann::KDTreeIndexParams(), cvflann::FLANN_DIST_EUCLIDEAN);
printf("Time creating FLANN KDTree index = %d ms\n", time.restart()); printf("Time creating FLANN KDTree index = %d ms\n", time.restart());
results = cv::Mat(objectDescriptors.rows, k, CV_32SC1); // Results index
dists = cv::Mat(objectDescriptors.rows, k, CV_32FC1); // Distance results are CV_32FC1
// search (nearest neighbor) // search (nearest neighbor)
flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() ); flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
@ -145,8 +138,13 @@ int main(int argc, char * argv[])
} }
printf("Time nearest neighbor search = %d ms\n", time.restart()); printf("Time nearest neighbor search = %d ms\n", time.restart());
// Conversion to CV_32F if needed
if(dists.type() == CV_32S)
{
cv::Mat temp;
dists.convertTo(temp, CV_32F);
dists = temp;
}
//////////////////////////// ////////////////////////////
@ -157,7 +155,7 @@ int main(int argc, char * argv[])
sceneWidget.setData(sceneKeypoints, sceneDescriptors, sceneImg, "", ""); sceneWidget.setData(sceneKeypoints, sceneDescriptors, sceneImg, "", "");
// Find correspondences by NNDR (Nearest Neighbor Distance Ratio) // Find correspondences by NNDR (Nearest Neighbor Distance Ratio)
float nndrRatio = 0.6; float nndrRatio = 0.8;
std::vector<cv::Point2f> mpts_1, mpts_2; // Used for homography std::vector<cv::Point2f> mpts_1, mpts_2; // Used for homography
std::vector<int> indexes_1, indexes_2; // Used for homography std::vector<int> indexes_1, indexes_2; // Used for homography
std::vector<uchar> outlier_mask; // Used for homography std::vector<uchar> outlier_mask; // Used for homography
@ -168,7 +166,7 @@ int main(int argc, char * argv[])
{ {
// Apply NNDR // Apply NNDR
//printf("q=%d dist1=%f dist2=%f\n", i, dists.at<float>(i,0), dists.at<float>(i,1)); //printf("q=%d dist1=%f dist2=%f\n", i, dists.at<float>(i,0), dists.at<float>(i,1));
if(isBinaryDescriptors || //Binary, just take the nearest if(results.at<int>(i,0) >= 0 && results.at<int>(i,1) >= 0 &&
dists.at<float>(i,0) <= nndrRatio * dists.at<float>(i,1)) dists.at<float>(i,0) <= nndrRatio * dists.at<float>(i,1))
{ {
mpts_1.push_back(objectKeypoints.at(i).pt); mpts_1.push_back(objectKeypoints.at(i).pt);
@ -185,7 +183,7 @@ int main(int argc, char * argv[])
{ {
// Apply NNDR // Apply NNDR
//printf("q=%d dist1=%f dist2=%f\n", matches.at(i).at(0).queryIdx, matches.at(i).at(0).distance, matches.at(i).at(1).distance); //printf("q=%d dist1=%f dist2=%f\n", matches.at(i).at(0).queryIdx, matches.at(i).at(0).distance, matches.at(i).at(1).distance);
if(isBinaryDescriptors || //Binary, just take the nearest if(matches.at(i).size() == 2 &&
matches.at(i).at(0).distance <= nndrRatio * matches.at(i).at(1).distance) matches.at(i).at(0).distance <= nndrRatio * matches.at(i).at(1).distance)
{ {
mpts_1.push_back(objectKeypoints.at(matches.at(i).at(0).queryIdx).pt); mpts_1.push_back(objectKeypoints.at(matches.at(i).at(0).queryIdx).pt);