Added code example for descriptors extraction
git-svn-id: http://find-object.googlecode.com/svn/trunk/find_object@20 620bd6b2-0a58-f614-fd9a-1bd335dccda9
This commit is contained in:
matlabbe
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### Qt Gui stuff ###
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SET(headers_ui
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../src/ObjWidget.h
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../src/Camera.h
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)
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#This will generate moc_* for Qt
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QT4_WRAP_CPP(moc_srcs ${headers_ui})
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### Qt Gui stuff end###
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SET(SRC_FILES
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main.cpp
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../src/ObjWidget.cpp
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../src/KeypointItem.cpp
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../src/qtipl.cpp
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../src/Settings.cpp
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../src/Camera.cpp
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${moc_srcs}
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)
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SET(INCLUDE_DIRS
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${CMAKE_CURRENT_SOURCE_DIR}
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${OpenCV_INCLUDE_DIRS}
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${CMAKE_CURRENT_SOURCE_DIR}/../src
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)
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INCLUDE(${QT_USE_FILE})
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SET(LIBRARIES
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${OpenCV_LIBS}
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${QT_LIBRARIES}
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)
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# Make sure the compiler can find include files from our library.
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INCLUDE_DIRECTORIES(${INCLUDE_DIRS})
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# Add binary called "example" that is built from the source file "main.cpp".
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# The extension is automatically found.
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ADD_EXECUTABLE(example ${SRC_FILES})
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TARGET_LINK_LIBRARIES(example ${LIBRARIES})
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SET_TARGET_PROPERTIES( example
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PROPERTIES OUTPUT_NAME ${PROJECT_PREFIX}-example)
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@@ -0,0 +1,236 @@
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/*
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* main.cpp
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*
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* Created on: 2011-11-15
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* Author: matlab
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*/
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#include <stdio.h>
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// Qt stuff
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#include <QtCore/QTime>
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#include <QtCore/QTimer>
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#include <QtGui/QApplication>
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#include <QtGui/QGraphicsRectItem>
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#include <QtGui/QPen>
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#include <QtGui/QColor>
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// OpenCV stuff
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#include <opencv2/core/core.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <opencv2/features2d/features2d.hpp>
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#include <opencv2/calib3d/calib3d.hpp> // for homography
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// From this project (see src folder)
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#include "ObjWidget.h"
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void showUsage()
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{
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printf("\n");
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printf("Usage :\n");
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printf(" ./example object.png scene.png\n");
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exit(1);
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}
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int main(int argc, char * argv[])
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{
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if(argc<3)
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{
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showUsage();
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}
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QTime time;
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time.start();
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// GUI stuff
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QApplication app(argc, argv);
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ObjWidget objWidget;
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ObjWidget sceneWidget;
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//Load as grayscale
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IplImage * objectImg = cvLoadImage(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
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IplImage * sceneImg = cvLoadImage(argv[2], CV_LOAD_IMAGE_GRAYSCALE);
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if(objectImg && sceneImg)
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{
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std::vector<cv::KeyPoint> objectKeypoints;
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std::vector<cv::KeyPoint> sceneKeypoints;
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cv::Mat objectDescriptors;
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cv::Mat sceneDescriptors;
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////////////////////////////
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// EXTRACT KEYPOINTS
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////////////////////////////
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// The detector can be any of (see OpenCV features2d.hpp):
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// cv::FeatureDetector * detector = new cv::FastFeatureDetector();
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// cv::FeatureDetector * detector = new cv::SiftFeatureDetector();
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// cv::FeatureDetector * detector = new cv::SurfFeatureDetector();
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// cv::FeatureDetector * detector = new cv::StarFeatureDetector();
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cv::FeatureDetector * detector = new cv::SurfFeatureDetector();
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detector->detect(objectImg, objectKeypoints);
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printf("Object: %d keypoints detected in %d ms\n", (int)objectKeypoints.size(), time.restart());
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detector->detect(sceneImg, sceneKeypoints);
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printf("Scene: %d keypoints detected in %d ms\n", (int)sceneKeypoints.size(), time.restart());
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////////////////////////////
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// EXTRACT DESCRIPTORS
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////////////////////////////
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// The extractor can be any of (see OpenCV features2d.hpp):
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// cv::DescriptorExtractor * detector = new cv::BriefDescriptorExtractor();
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// cv::DescriptorExtractor * detector = new cv::SiftFeatureDetector();
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// cv::DescriptorExtractor * detector = new cv::SurfFeatureDetector();
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cv::DescriptorExtractor * extractor = new cv::SurfDescriptorExtractor();
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extractor->compute(objectImg, objectKeypoints, objectDescriptors);
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printf("Object: %d descriptors extracted in %d ms\n", objectDescriptors.rows, time.restart());
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extractor->compute(sceneImg, sceneKeypoints, sceneDescriptors);
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printf("Scene: %d descriptors extracted in %d ms\n", sceneDescriptors.rows, time.restart());
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////////////////////////////
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// NEAREST NEIGHBOR MATCHING USING FLANN LIBRARY (included in OpenCV)
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////////////////////////////
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// Format descriptors for Flann
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cv::Mat objectData;
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cv::Mat sceneData;
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if(objectDescriptors.type()!=CV_32F) {
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objectDescriptors.convertTo(objectData, CV_32F); // make sure it's CV_32F
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}
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else {
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objectData = objectDescriptors;
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}
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if(sceneDescriptors.type()!=CV_32F) {
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sceneDescriptors.convertTo(sceneData, CV_32F); // make sure it's CV_32F
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}
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else {
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sceneData = sceneDescriptors;
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}
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// Create Flann index
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cv::flann::Index treeFlannIndex(sceneData, cv::flann::KDTreeIndexParams());
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printf("Time creating FLANN index = %d ms\n", time.restart());
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// search (nearest neighbor)
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int k=2; // find the 2 nearest neighbors
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cv::Mat results(objectData.rows, k, CV_32SC1); // Results index
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cv::Mat dists(objectData.rows, k, CV_32FC1); // Distance results are CV_32FC1
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treeFlannIndex.knnSearch(objectData, results, dists, k, cv::flann::SearchParams() ); // maximum number of leafs checked
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printf("Time nearest neighbor search = %d ms\n", time.restart());
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////////////////////////////
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// PROCESS NEAREST NEIGHBOR RESULTS
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////////////////////////////
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// Set gui data
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objWidget.setData(objectKeypoints, objectDescriptors, objectImg);
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sceneWidget.setData(sceneKeypoints, sceneDescriptors, sceneImg);
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// Find correspondences by NNDR (Nearest Neighbor Distance Ratio)
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float nndrRatio = 0.6;
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std::vector<cv::Point2f> mpts_1, mpts_2; // Used for homography
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std::vector<int> indexes_1, indexes_2; // Used for homography
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std::vector<uchar> outlier_mask; // Used for homography
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for(unsigned int i=0; i<objectData.rows; ++i)
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{
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// Check if this descriptor matches with those of the objects
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// Apply NNDR
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if(dists.at<float>(i,0) <= nndrRatio * dists.at<float>(i,1))
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{
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mpts_1.push_back(objectKeypoints.at(i).pt);
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indexes_1.push_back(i);
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mpts_2.push_back(sceneKeypoints.at(results.at<int>(i,0)).pt);
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indexes_2.push_back(results.at<int>(i,0));
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}
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}
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// FIND HOMOGRAPHY
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int minInliers = 8;
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if(mpts_1.size() >= minInliers)
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{
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cv::Mat H = findHomography(mpts_1,
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mpts_2,
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cv::RANSAC,
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1.0,
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outlier_mask);
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int inliers=0, outliers=0;
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for(int k=0; k<mpts_1.size();++k)
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{
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if(outlier_mask.at(k))
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{
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++inliers;
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}
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else
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{
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++outliers;
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}
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}
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QTransform hTransform(
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H.at<double>(0,0), H.at<double>(1,0), H.at<double>(2,0),
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H.at<double>(0,1), H.at<double>(1,1), H.at<double>(2,1),
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H.at<double>(0,2), H.at<double>(1,2), H.at<double>(2,2));
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// GUI : Change color and add homography rectangle
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QColor color(Qt::red);
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int alpha = 130;
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color.setAlpha(alpha);
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for(int k=0; k<mpts_1.size();++k)
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{
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if(outlier_mask.at(k))
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{
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objWidget.setKptColor(indexes_1.at(k), color);
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sceneWidget.setKptColor(indexes_2.at(k), color);
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}
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else
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{
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objWidget.setKptColor(indexes_1.at(k), QColor(0,0,0,alpha));
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}
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}
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QPen rectPen(color);
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rectPen.setWidth(4);
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QGraphicsRectItem * rectItem = new QGraphicsRectItem(objWidget.image().rect());
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rectItem->setPen(rectPen);
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rectItem->setTransform(hTransform);
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sceneWidget.addRect(rectItem);
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printf("Inliers=%d Outliers=%d\n", inliers, outliers);
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}
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else
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{
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printf("Not enough matches (%d) for homography...\n", (int)mpts_1.size());
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}
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// Wait for gui
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objWidget.setGraphicsViewMode(false);
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objWidget.setWindowTitle("Object");
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objWidget.show();
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sceneWidget.setGraphicsViewMode(false);
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sceneWidget.setWindowTitle("Scene");
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sceneWidget.show();
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int r = app.exec();
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////////////////////////////
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//Cleanup
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////////////////////////////
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delete detector;
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delete extractor;
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if(objectImg) {
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cvReleaseImage(&objectImg);
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}
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if(sceneImg) {
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cvReleaseImage(&sceneImg);
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}
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return r;
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}
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else
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{
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if(objectImg) {
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cvReleaseImage(&objectImg);
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}
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if(sceneImg) {
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cvReleaseImage(&sceneImg);
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}
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printf("Images are not valid!\n");
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showUsage();
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}
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return 1;
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}
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