Commit d017faa0 authored by Vadim Pisarevsky's avatar Vadim Pisarevsky

now all the samples and opencv_contrib compile!

parent 5e667ee5
......@@ -197,6 +197,10 @@ public:
CV_WRAP virtual int detectAndLabel( InputArray image, OutputArray label,
OutputArray stats=noArray() ) = 0;
CV_WRAP virtual void detectAndStore( InputArray image,
std::vector<std::vector<Point> >& msers,
OutputArray stats=noArray() ) = 0;
};
//! detects corners using FAST algorithm by E. Rosten
......
......@@ -301,6 +301,9 @@ public:
};
int detectAndLabel( InputArray _src, OutputArray _labels, OutputArray _bboxes );
void detectAndStore( InputArray image,
std::vector<std::vector<Point> >& msers,
OutputArray stats );
void detect( InputArray _src, vector<KeyPoint>& keypoints, InputArray _mask );
void preprocess1( const Mat& img, int* level_size )
......@@ -955,6 +958,35 @@ int MSER_Impl::detectAndLabel( InputArray _src, OutputArray _labels, OutputArray
return (int)bboxvec.size();
}
void MSER_Impl::detectAndStore( InputArray image,
std::vector<std::vector<Point> >& msers,
OutputArray stats )
{
vector<Rect> bboxvec;
Mat labels;
int i, x, y, nregs = detectAndLabel(image, labels, bboxvec);
msers.resize(nregs);
for( i = 0; i < nregs; i++ )
{
Rect r = bboxvec[i];
vector<Point>& msers_i = msers[i];
msers_i.clear();
for( y = r.y; y < r.y + r.height; y++ )
{
const int* lptr = labels.ptr<int>(y);
for( x = r.x; x < r.x + r.width; x++ )
{
if( lptr[x] == i+1 )
msers_i.push_back(Point(x, y));
}
}
}
if( stats.needed() )
Mat(bboxvec).copyTo(stats);
}
void MSER_Impl::detect( InputArray _image, vector<KeyPoint>& keypoints, InputArray _mask )
{
vector<Rect> bboxes;
......
......@@ -48,8 +48,6 @@ using namespace cv::cuda;
#ifdef HAVE_OPENCV_XFEATURES2D
#include "opencv2/xfeatures2d.hpp"
static bool makeUseOfXfeatures2d = xfeatures2d::initModule_xfeatures2d();
#endif
namespace {
......
......@@ -19,23 +19,23 @@ public:
RobustMatcher() : ratio_(0.8f)
{
// ORB is the default feature
detector_ = new cv::OrbFeatureDetector();
extractor_ = new cv::OrbDescriptorExtractor();
detector_ = cv::ORB::create();
extractor_ = cv::ORB::create();
// BruteFroce matcher with Norm Hamming is the default matcher
matcher_ = new cv::BFMatcher(cv::NORM_HAMMING, false);
matcher_ = cv::makePtr<cv::BFMatcher>(cv::NORM_HAMMING, false);
}
virtual ~RobustMatcher();
// Set the feature detector
void setFeatureDetector(cv::FeatureDetector * detect) { detector_ = detect; }
void setFeatureDetector(const cv::Ptr<cv::FeatureDetector>& detect) { detector_ = detect; }
// Set the descriptor extractor
void setDescriptorExtractor(cv::DescriptorExtractor * desc) { extractor_ = desc; }
void setDescriptorExtractor(const cv::Ptr<cv::DescriptorExtractor>& desc) { extractor_ = desc; }
// Set the matcher
void setDescriptorMatcher(cv::DescriptorMatcher * match) { matcher_ = match; }
void setDescriptorMatcher(const cv::Ptr<cv::DescriptorMatcher>& match) { matcher_ = match; }
// Compute the keypoints of an image
void computeKeyPoints( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints);
......@@ -69,11 +69,11 @@ public:
private:
// pointer to the feature point detector object
cv::FeatureDetector * detector_;
cv::Ptr<cv::FeatureDetector> detector_;
// pointer to the feature descriptor extractor object
cv::DescriptorExtractor * extractor_;
cv::Ptr<cv::DescriptorExtractor> extractor_;
// pointer to the matcher object
cv::DescriptorMatcher * matcher_;
cv::Ptr<cv::DescriptorMatcher> matcher_;
// max ratio between 1st and 2nd NN
float ratio_;
};
......
......@@ -13,13 +13,16 @@
#include "ModelRegistration.h"
#include "Utils.h"
using namespace cv;
using namespace std;
/** GLOBAL VARIABLES **/
std::string tutorial_path = "../../samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/"; // path to tutorial
string tutorial_path = "../../samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/"; // path to tutorial
std::string img_path = tutorial_path + "Data/resized_IMG_3875.JPG"; // image to register
std::string ply_read_path = tutorial_path + "Data/box.ply"; // object mesh
std::string write_path = tutorial_path + "Data/cookies_ORB.yml"; // output file
string img_path = tutorial_path + "Data/resized_IMG_3875.JPG"; // image to register
string ply_read_path = tutorial_path + "Data/box.ply"; // object mesh
string write_path = tutorial_path + "Data/cookies_ORB.yml"; // output file
// Boolean the know if the registration it's done
bool end_registration = false;
......@@ -39,10 +42,10 @@ int n = 8;
int pts[] = {1, 2, 3, 4, 5, 6, 7, 8}; // 3 -> 4
// Some basic colors
cv::Scalar red(0, 0, 255);
cv::Scalar green(0,255,0);
cv::Scalar blue(255,0,0);
cv::Scalar yellow(0,255,255);
Scalar red(0, 0, 255);
Scalar green(0,255,0);
Scalar blue(255,0,0);
Scalar yellow(0,255,255);
/*
* CREATE MODEL REGISTRATION OBJECT
......@@ -61,13 +64,13 @@ void help();
// Mouse events for model registration
static void onMouseModelRegistration( int event, int x, int y, int, void* )
{
if ( event == cv::EVENT_LBUTTONUP )
if ( event == EVENT_LBUTTONUP )
{
int n_regist = registration.getNumRegist();
int n_vertex = pts[n_regist];
cv::Point2f point_2d = cv::Point2f((float)x,(float)y);
cv::Point3f point_3d = mesh.getVertex(n_vertex-1);
Point2f point_2d = Point2f((float)x,(float)y);
Point3f point_3d = mesh.getVertex(n_vertex-1);
bool is_registrable = registration.is_registrable();
if (is_registrable)
......@@ -92,23 +95,23 @@ int main()
//Instantiate robust matcher: detector, extractor, matcher
RobustMatcher rmatcher;
cv::FeatureDetector * detector = new cv::OrbFeatureDetector(numKeyPoints);
Ptr<FeatureDetector> detector = ORB::create(numKeyPoints);
rmatcher.setFeatureDetector(detector);
/** GROUND TRUTH OF THE FIRST IMAGE **/
// Create & Open Window
cv::namedWindow("MODEL REGISTRATION", cv::WINDOW_KEEPRATIO);
namedWindow("MODEL REGISTRATION", WINDOW_KEEPRATIO);
// Set up the mouse events
cv::setMouseCallback("MODEL REGISTRATION", onMouseModelRegistration, 0 );
setMouseCallback("MODEL REGISTRATION", onMouseModelRegistration, 0 );
// Open the image to register
cv::Mat img_in = cv::imread(img_path, cv::IMREAD_COLOR);
cv::Mat img_vis = img_in.clone();
Mat img_in = imread(img_path, IMREAD_COLOR);
Mat img_vis = img_in.clone();
if (!img_in.data) {
std::cout << "Could not open or find the image" << std::endl;
cout << "Could not open or find the image" << endl;
return -1;
}
......@@ -116,18 +119,18 @@ int main()
int num_registrations = n;
registration.setNumMax(num_registrations);
std::cout << "Click the box corners ..." << std::endl;
std::cout << "Waiting ..." << std::endl;
cout << "Click the box corners ..." << endl;
cout << "Waiting ..." << endl;
// Loop until all the points are registered
while ( cv::waitKey(30) < 0 )
while ( waitKey(30) < 0 )
{
// Refresh debug image
img_vis = img_in.clone();
// Current registered points
std::vector<cv::Point2f> list_points2d = registration.get_points2d();
std::vector<cv::Point3f> list_points3d = registration.get_points3d();
vector<Point2f> list_points2d = registration.get_points2d();
vector<Point3f> list_points3d = registration.get_points3d();
// Draw current registered points
drawPoints(img_vis, list_points2d, list_points3d, red);
......@@ -139,7 +142,7 @@ int main()
// Draw debug text
int n_regist = registration.getNumRegist();
int n_vertex = pts[n_regist];
cv::Point3f current_poin3d = mesh.getVertex(n_vertex-1);
Point3f current_poin3d = mesh.getVertex(n_vertex-1);
drawQuestion(img_vis, current_poin3d, green);
drawCounter(img_vis, registration.getNumRegist(), registration.getNumMax(), red);
......@@ -153,43 +156,43 @@ int main()
}
// Show the image
cv::imshow("MODEL REGISTRATION", img_vis);
imshow("MODEL REGISTRATION", img_vis);
}
/** COMPUTE CAMERA POSE **/
std::cout << "COMPUTING POSE ..." << std::endl;
cout << "COMPUTING POSE ..." << endl;
// The list of registered points
std::vector<cv::Point2f> list_points2d = registration.get_points2d();
std::vector<cv::Point3f> list_points3d = registration.get_points3d();
vector<Point2f> list_points2d = registration.get_points2d();
vector<Point3f> list_points3d = registration.get_points3d();
// Estimate pose given the registered points
bool is_correspondence = pnp_registration.estimatePose(list_points3d, list_points2d, cv::SOLVEPNP_ITERATIVE);
bool is_correspondence = pnp_registration.estimatePose(list_points3d, list_points2d, SOLVEPNP_ITERATIVE);
if ( is_correspondence )
{
std::cout << "Correspondence found" << std::endl;
cout << "Correspondence found" << endl;
// Compute all the 2D points of the mesh to verify the algorithm and draw it
std::vector<cv::Point2f> list_points2d_mesh = pnp_registration.verify_points(&mesh);
vector<Point2f> list_points2d_mesh = pnp_registration.verify_points(&mesh);
draw2DPoints(img_vis, list_points2d_mesh, green);
} else {
std::cout << "Correspondence not found" << std::endl << std::endl;
cout << "Correspondence not found" << endl << endl;
}
// Show the image
cv::imshow("MODEL REGISTRATION", img_vis);
imshow("MODEL REGISTRATION", img_vis);
// Show image until ESC pressed
cv::waitKey(0);
waitKey(0);
/** COMPUTE 3D of the image Keypoints **/
// Containers for keypoints and descriptors of the model
std::vector<cv::KeyPoint> keypoints_model;
cv::Mat descriptors;
vector<KeyPoint> keypoints_model;
Mat descriptors;
// Compute keypoints and descriptors
rmatcher.computeKeyPoints(img_in, keypoints_model);
......@@ -197,8 +200,8 @@ int main()
// Check if keypoints are on the surface of the registration image and add to the model
for (unsigned int i = 0; i < keypoints_model.size(); ++i) {
cv::Point2f point2d(keypoints_model[i].pt);
cv::Point3f point3d;
Point2f point2d(keypoints_model[i].pt);
Point3f point3d;
bool on_surface = pnp_registration.backproject2DPoint(&mesh, point2d, point3d);
if (on_surface)
{
......@@ -219,12 +222,12 @@ int main()
img_vis = img_in.clone();
// The list of the points2d of the model
std::vector<cv::Point2f> list_points_in = model.get_points2d_in();
std::vector<cv::Point2f> list_points_out = model.get_points2d_out();
vector<Point2f> list_points_in = model.get_points2d_in();
vector<Point2f> list_points_out = model.get_points2d_out();
// Draw some debug text
std::string num = IntToString((int)list_points_in.size());
std::string text = "There are " + num + " inliers";
string num = IntToString((int)list_points_in.size());
string text = "There are " + num + " inliers";
drawText(img_vis, text, green);
// Draw some debug text
......@@ -240,26 +243,26 @@ int main()
draw2DPoints(img_vis, list_points_out, red);
// Show the image
cv::imshow("MODEL REGISTRATION", img_vis);
imshow("MODEL REGISTRATION", img_vis);
// Wait until ESC pressed
cv::waitKey(0);
waitKey(0);
// Close and Destroy Window
cv::destroyWindow("MODEL REGISTRATION");
destroyWindow("MODEL REGISTRATION");
std::cout << "GOODBYE" << std::endl;
cout << "GOODBYE" << endl;
}
/**********************************************************************************************************/
void help()
{
std::cout
<< "--------------------------------------------------------------------------" << std::endl
<< "This program shows how to create your 3D textured model. " << std::endl
<< "Usage:" << std::endl
<< "./cpp-tutorial-pnp_registration" << std::endl
<< "--------------------------------------------------------------------------" << std::endl
<< std::endl;
cout
<< "--------------------------------------------------------------------------" << endl
<< "This program shows how to create your 3D textured model. " << endl
<< "Usage:" << endl
<< "./cpp-tutorial-pnp_registration" << endl
<< "--------------------------------------------------------------------------" << endl
<< endl;
}
......@@ -22,9 +22,9 @@ int main(void)
vector<KeyPoint> kpts1, kpts2;
Mat desc1, desc2;
AKAZE akaze;
akaze(img1, noArray(), kpts1, desc1);
akaze(img2, noArray(), kpts2, desc2);
Ptr<AKAZE> akaze = AKAZE::create();
akaze->detectAndCompute(img1, noArray(), kpts1, desc1);
akaze->detectAndCompute(img2, noArray(), kpts2, desc2);
BFMatcher matcher(NORM_HAMMING);
vector< vector<DMatch> > nn_matches;
......
......@@ -41,7 +41,7 @@ protected:
void Tracker::setFirstFrame(const Mat frame, vector<Point2f> bb, string title, Stats& stats)
{
first_frame = frame.clone();
(*detector)(first_frame, noArray(), first_kp, first_desc);
detector->detectAndCompute(first_frame, noArray(), first_kp, first_desc);
stats.keypoints = (int)first_kp.size();
drawBoundingBox(first_frame, bb);
putText(first_frame, title, Point(0, 60), FONT_HERSHEY_PLAIN, 5, Scalar::all(0), 4);
......@@ -52,7 +52,7 @@ Mat Tracker::process(const Mat frame, Stats& stats)
{
vector<KeyPoint> kp;
Mat desc;
(*detector)(frame, noArray(), kp, desc);
detector->detectAndCompute(frame, noArray(), kp, desc);
stats.keypoints = (int)kp.size();
vector< vector<DMatch> > matches;
......@@ -135,9 +135,9 @@ int main(int argc, char **argv)
return 1;
}
fs["bounding_box"] >> bb;
Ptr<Feature2D> akaze = Feature2D::create("AKAZE");
Ptr<Feature2D> akaze = AKAZE::create();
akaze->set("threshold", akaze_thresh);
Ptr<Feature2D> orb = Feature2D::create("ORB");
Ptr<Feature2D> orb = ORB::create();
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-Hamming");
Tracker akaze_tracker(akaze, matcher);
Tracker orb_tracker(orb, matcher);
......
......@@ -227,7 +227,7 @@ public:
#endif
Ptr<KeypointBasedMotionEstimator> kbest = makePtr<KeypointBasedMotionEstimator>(est);
kbest->setDetector(makePtr<GoodFeaturesToTrackDetector>(argi(prefix + "nkps")));
kbest->setDetector(GFTTDetector::create(argi(prefix + "nkps")));
kbest->setOutlierRejector(outlierRejector);
return kbest;
}
......@@ -268,7 +268,7 @@ public:
#endif
Ptr<KeypointBasedMotionEstimator> kbest = makePtr<KeypointBasedMotionEstimator>(est);
kbest->setDetector(makePtr<GoodFeaturesToTrackDetector>(argi(prefix + "nkps")));
kbest->setDetector(GFTTDetector::create(argi(prefix + "nkps")));
kbest->setOutlierRejector(outlierRejector);
return kbest;
}
......
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