features

#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgcodecs/imgcodecs.hpp"
#include <opencv2/videoio/videoio.hpp>
#include <opencv2/video/video.hpp>
#include "opencv2/xfeatures2d/nonfree.hpp"
#include "opencv2/xfeatures2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/calib3d.hpp"
#include <stdlib.h>



using namespace cv;
using namespace std;
using namespace cv::xfeatures2d;
FlannBasedMatcher matcher;
Mat src;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

Mat img_prev, img_curr, result;

//void BoundingBox(Mat& img, vector<DMatch>& good_matches,double Dist);

/** @function main */
int main( int argc, char** argv )
{


	VideoCapture cap(0);
	  if (!cap.isOpened())
			  {
			       cout << "Cannot access camera" << endl;
			       return -1;
			   }

  for(;;)
  {

    cap >> img_curr;

    if(img_curr.empty()){
    	cout<<"no image"<<endl;
    	break;
    }

    //img_prev = cv::Mat::zeros(img_curr.size(), img_curr.type()); // prev frame as black


    img_curr.copyTo(img_prev);

   cv::imshow ("current frame",img_curr);

   cv::imshow("previous frame", img_prev);

   if( waitKey(10) == 27 ) break; // stop capturing by pressing ESC

   //cvtColor( img_curr, src_gray, CV_BGR2GRAY );

  //-- Step 1: Detect the keypoints using SURF Detector
  int minHessian = 2000;
  //Ptr<xfeatures2d::SURF> detector = xfeatures2d::SURF::create(minHessian);
  clock_t begin = clock();
  Ptr<SURF> detector = SURF::create(minHessian);
 // SurfFeatureDetector detector( minHessian );

  std::vector<KeyPoint> keypoints_object, keypoints_scene;

  detector->detect( img_curr, keypoints_scene);
  detector->detect( img_prev, keypoints_object);

		    //printf("-- Max dist : %f \n", max_dist );
		    //printf("-- Min dist : %f \n", min_dist );

		    //-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist,
		    //-- or a small arbitary value ( 0.02 ) in the event that min_dist is very
		    //-- small)
		    //-- PS.- radiusMatch can also be used here.y );

  //-- Step 2: Calculate descriptors (feature vectors)
  //SurfDescriptorExtractor extractor;
  Ptr<SURF> extractor = SURF::create();

  Mat descriptors_object, descriptors_scene;

  extractor->compute( img_curr, keypoints_scene, descriptors_scene);
  extractor->compute( img_prev, keypoints_object, descriptors_object);

  //-- Step 3: Matching descriptor vectors using FLANN matcher
  FlannBasedMatcher matcher;
  std::vector< DMatch > matches;
  matcher.match( descriptors_object, descriptors_scene, matches );

  double max_dist = 0; double min_dist = 100;

  //-- Quick calculation of max and min distances between keypoints
    for( int i = 0; i < descriptors_scene.rows; i++ )
    { double dist = matches[i].distance;
      if( dist < min_dist ) min_dist = dist;
      if( dist > max_dist ) max_dist = dist;
    }

    std::vector< DMatch > good_matches;

    for( int i = 0; i < descriptors_scene.rows; i++ )
    { if( matches[i].distance <= max(2*min_dist, 0.02) )
      { good_matches.push_back( matches[i]); }
    }

    //-- Draw only "good" matches
    Mat img_matches;
    drawMatches( img_curr, keypoints_scene, img_prev, keypoints_object,
                 good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                 vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );





     /// Detect edges using Threshold
    //cvtColor(img_matches,src,CV_BGR2GRAY,1);
    //-- Localize the object
     std::vector<Point2f> obj;
     std::vector<Point2f> scene;

     //int myradius=10;

    for( int i = 0; i < (int)good_matches.size(); i++ )
    {

    	//-- Get the keypoints from the good matches
    	    obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
    	    scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
    	   // circle(img_matches,cvPoint(scene[i].x,scene[i].y),myradius,CV_RGB(100,0,0),-1,8,0);


    	    // printf( "-- Good Match [%d] Keypoint scene: %d  -- Keypoint object: %d  \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }
    	  //Rect r = boundingRect(src);

    		//  Rect Min_Rect=boundingRect(src);
             // rectangle(src, pt1, pt2, CV_RGB(255,0,0), 1);
       	      //cout<<"channels"<<src.channels();
       	      //cout<<"type"<<src.type();
    	      //imshow( "Good Matches",src);

       	      //else

       	      //return -1;

      Mat H = findHomography(obj,scene, CV_RANSAC );
      std::vector<Point2f> obj_corners(4);
        obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( obj[i].x, 0 );
        obj_corners[2] = cvPoint( obj[i].x, obj[i].y ); obj_corners[3] = cvPoint( 0, obj[i].y );
        std::vector<Point2f> scene_corners(4);

        perspectiveTransform( obj_corners, scene_corners, H);

       line( img_matches, scene_corners[0] + Point2f( img_prev.cols, 0), scene_corners[1] + Point2f( img_prev.cols, 0), Scalar(0, 255, 0), 4 );
       line( img_matches, scene_corners[1] + Point2f( img_prev.cols, 0), scene_corners[2] + Point2f( img_prev.cols, 0), Scalar( 0, 255, 0), 4 );
       line( img_matches, scene_corners[2] + Point2f( img_prev.cols, 0), scene_corners[3] + Point2f( img_prev.cols, 0), Scalar( 0, 255, 0), 4 );
       line( img_matches, scene_corners[3] + Point2f( img_prev.cols, 0), scene_corners[0] + Point2f( img_prev.cols, 0), Scalar( 0, 255, 0), 4 );

        cout<<"here"<<endl;
        imshow( "Good Matches & Object detection", img_matches );
        cout<<"object"<<obj<<"scene"<<scene<<endl;
        clock_t end = clock();
        double elapsed_secs = double (end-begin)/CLOCKS_PER_SEC;
        cout<<"total time"<<elapsed_secs<<"s"<<endl;

    }


  }

	  return 0;
}
/*
	void BoundingBox(Mat& img, vector<DMatch>& good_matches,double Dist, const Scalar& color, int thickness=1, int lineType=8, int shift=0)
	{
		if(img.empty())
		{

			break;
		}
		else
		{
			cout<<"we are inside box"<<endl;
			for(int i = 0; i >= 20; i++)
			{
				Dist = good_matches[i].distance;

			}
		}
	}
*/