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Fixed a warning (int and unsigned int comparison) in Camera.cpp

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Updated example to switch between LSH and KDTree depending on descriptors type detected. Also use SIFT as it gives better results than SURF.

git-svn-id: http://find-object.googlecode.com/svn/trunk/find_object@163 620bd6b2-0a58-f614-fd9a-1bd335dccda9
This commit is contained in:
matlabbe 2012-08-31 14:09:25 +00:00
parent 3930d71b2f
commit 4fb42d4889
3 changed files with 42 additions and 37 deletions
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75
example/main.cpp
View File

@ -66,10 +66,9 @@ int main(int argc, char * argv[])
// cv::FeatureDetector * detector = new cv::GFTTDetector();
// cv::FeatureDetector * detector = new cv::MSER();
// cv::FeatureDetector * detector = new cv::ORB();
// cv::FeatureDetector * detector = new cv::SIFT();
cv::FeatureDetector * detector = new cv::SIFT();
// cv::FeatureDetector * detector = new cv::StarFeatureDetector();
// cv::FeatureDetector * detector = new cv::SURF();
cv::FeatureDetector * detector = new cv::SURF(600.0);
// cv::FeatureDetector * detector = new cv::SURF(600.0);
detector->detect(objectImg, objectKeypoints);
printf("Object: %d keypoints detected in %d ms\n", (int)objectKeypoints.size(), time.restart());
detector->detect(sceneImg, sceneKeypoints);
@ -81,9 +80,8 @@ int main(int argc, char * argv[])
// The extractor can be any of (see OpenCV features2d.hpp):
// cv::DescriptorExtractor * extractor = new cv::BriefDescriptorExtractor();
// cv::DescriptorExtractor * extractor = new cv::ORB();
// cv::DescriptorExtractor * extractor = new cv::SIFT();
// cv::DescriptorExtractor * extractor = new cv::SURF();
cv::DescriptorExtractor * extractor = new cv::SURF(600.0);
cv::DescriptorExtractor * extractor = new cv::SIFT();
// cv::DescriptorExtractor * extractor = new cv::SURF(600.0);
extractor->compute(objectImg, objectKeypoints, objectDescriptors);
printf("Object: %d descriptors extracted in %d ms\n", objectDescriptors.rows, time.restart());
extractor->compute(sceneImg, sceneKeypoints, sceneDescriptors);
@ -92,46 +90,55 @@ int main(int argc, char * argv[])
////////////////////////////
// NEAREST NEIGHBOR MATCHING USING FLANN LIBRARY (included in OpenCV)
////////////////////////////
// Format descriptors for Flann
cv::Mat objectData;
cv::Mat sceneData;
if(objectDescriptors.type()!=CV_32F) {
objectDescriptors.convertTo(objectData, CV_32F); // make sure it's CV_32F
}
else {
objectData = objectDescriptors;
}
if(sceneDescriptors.type()!=CV_32F) {
sceneDescriptors.convertTo(sceneData, CV_32F); // make sure it's CV_32F
}
else {
sceneData = sceneDescriptors;
}
// Create Flann index
cv::flann::Index treeFlannIndex(sceneData, cv::flann::KDTreeIndexParams());
printf("Time creating FLANN index = %d ms\n", time.restart());
// search (nearest neighbor)
cv::Mat results;
cv::Mat dists;
int k=2; // find the 2 nearest neighbors
cv::Mat results(objectData.rows, k, CV_32SC1); // Results index
cv::Mat dists(objectData.rows, k, CV_32FC1); // Distance results are CV_32FC1
treeFlannIndex.knnSearch(objectData, results, dists, k, cv::flann::SearchParams() ); // maximum number of leafs checked
printf("Time nearest neighbor search = %d ms\n", time.restart());
if(objectDescriptors.type()==CV_8U)
{
// Binary descriptors detected (from ORB or Brief)
// Create Flann LSH index
cv::flann::Index flannIndex(sceneDescriptors, cv::flann::LshIndexParams(20, 10, 2));
printf("Time creating FLANN 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)
flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
printf("Time nearest neighbor search = %d ms\n", time.restart());
}
else
{
// assume it is CV_32F
// Create Flann KDTree index
cv::flann::Index flannIndex(sceneDescriptors, cv::flann::KDTreeIndexParams());
printf("Time creating FLANN 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)
flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
printf("Time nearest neighbor search = %d ms\n", time.restart());
}
////////////////////////////
// PROCESS NEAREST NEIGHBOR RESULTS
////////////////////////////
// Set gui data
objWidget.setData(objectKeypoints, objectDescriptors, objectImg, "SURF", "SURF");
sceneWidget.setData(sceneKeypoints, sceneDescriptors, sceneImg, "SURF", "SURF");
objWidget.setData(objectKeypoints, objectDescriptors, objectImg, "", "");
sceneWidget.setData(sceneKeypoints, sceneDescriptors, sceneImg, "", "");
// Find correspondences by NNDR (Nearest Neighbor Distance Ratio)
float nndrRatio = 0.6;
std::vector<cv::Point2f> mpts_1, mpts_2; // Used for homography
std::vector<int> indexes_1, indexes_2; // Used for homography
std::vector<uchar> outlier_mask; // Used for homography
for(int i=0; i<objectData.rows; ++i)
for(int i=0; i<objectDescriptors.rows; ++i)
{
// Check if this descriptor matches with those of the objects
// Apply NNDR

2
src/Camera.cpp
View File

@ -83,7 +83,7 @@ void Camera::takeImage()
}
else if(!images_.empty())
{
if(currentImageIndex_ < images_.size())
if(currentImageIndex_ < (unsigned int)images_.size())
{
img = cv::imread(images_[currentImageIndex_++]);
}

2
src/MainWindow.cpp
View File

@ -1048,8 +1048,6 @@ void MainWindow::update(const cv::Mat & image)
QColor color((Qt::GlobalColor)(nColor==Qt::yellow?Qt::gray:nColor));
for(QMultiMap<int, int>::iterator iter = matches[i].begin(); iter!=matches[i].end(); ++iter)
{
printf("iter.key()=%d, iter.value()=%d\n", iter.key(), iter.value());
printf("objects_[%d].keypoints=%d\n", i, (int)objects_[i]->keypoints().size());
objects_[i]->setKptColor(iter.key(), color);
ui_->imageView_source->setKptColor(iter.value(), color);
}