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

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

example/main.cpp

@@ -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::SIFT();
-		// cv::DescriptorExtractor * extractor = new cv::SURF();
+		// cv::DescriptorExtractor * extractor = new cv::SURF(600.0);
-		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 results;
-		cv::Mat objectData;
+		cv::Mat dists;
-		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)
 		int k=2; // find the 2 nearest neighbors
-		cv::Mat results(objectData.rows, k, CV_32SC1); // Results index
+		if(objectDescriptors.type()==CV_8U)
-		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
+			// Binary descriptors detected (from ORB or Brief)
-		printf("Time nearest neighbor search = %d ms\n", time.restart());
+
+			// 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");
+		objWidget.setData(objectKeypoints, objectDescriptors, objectImg, "", "");
-		sceneWidget.setData(sceneKeypoints, sceneDescriptors, sceneImg, "SURF", "SURF");
+		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

src/Camera.cpp

@@ -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_++]);
 		}

src/MainWindow.cpp

@@ -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);
 					}