226 lines
6.9 KiB
C++
226 lines
6.9 KiB
C++
#include <iostream>
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#include <stdio.h>
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#include "opencv2/core.hpp"
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#include "opencv2/core/utility.hpp"
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#include "opencv2/core/ocl.hpp"
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/features2d.hpp"
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#include "opencv2/calib3d.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/xfeatures2d.hpp"
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using namespace cv;
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using namespace cv::xfeatures2d;
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const int LOOP_NUM = 10;
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const int GOOD_PTS_MAX = 50;
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const float GOOD_PORTION = 0.15f;
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int64 work_begin = 0;
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int64 work_end = 0;
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static void workBegin()
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{
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work_begin = getTickCount();
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}
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static void workEnd()
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{
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work_end = getTickCount() - work_begin;
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}
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static double getTime()
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{
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return work_end /((double)getTickFrequency() )* 1000.;
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}
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struct SURFDetector
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{
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Ptr<Feature2D> surf;
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SURFDetector(double hessian = 800.0)
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{
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surf = SURF::create(hessian);
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}
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template<class T>
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void operator()(const T& in, const T& mask, std::vector<cv::KeyPoint>& pts, T& descriptors, bool useProvided = false)
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{
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surf->detectAndCompute(in, mask, pts, descriptors, useProvided);
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}
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};
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template<class KPMatcher>
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struct SURFMatcher
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{
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KPMatcher matcher;
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template<class T>
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void match(const T& in1, const T& in2, std::vector<cv::DMatch>& matches)
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{
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matcher.match(in1, in2, matches);
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}
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};
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static Mat drawGoodMatches(
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const Mat& img1,
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const Mat& img2,
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const std::vector<KeyPoint>& keypoints1,
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const std::vector<KeyPoint>& keypoints2,
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std::vector<DMatch>& matches,
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std::vector<Point2f>& scene_corners_
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)
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{
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//-- Sort matches and preserve top 10% matches
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std::sort(matches.begin(), matches.end());
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std::vector< DMatch > good_matches;
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double minDist = matches.front().distance;
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double maxDist = matches.back().distance;
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const int ptsPairs = std::min(GOOD_PTS_MAX, (int)(matches.size() * GOOD_PORTION));
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for( int i = 0; i < ptsPairs; i++ )
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{
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good_matches.push_back( matches[i] );
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}
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std::cout << "\nMax distance: " << maxDist << std::endl;
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std::cout << "Min distance: " << minDist << std::endl;
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std::cout << "Calculating homography using " << ptsPairs << " point pairs." << std::endl;
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// drawing the results
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Mat img_matches;
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drawMatches( img1, keypoints1, img2, keypoints2,
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good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
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std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
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//-- Localize the object
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std::vector<Point2f> obj;
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std::vector<Point2f> scene;
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for( size_t i = 0; i < good_matches.size(); i++ )
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{
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//-- Get the keypoints from the good matches
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obj.push_back( keypoints1[ good_matches[i].queryIdx ].pt );
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scene.push_back( keypoints2[ good_matches[i].trainIdx ].pt );
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}
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//-- Get the corners from the image_1 ( the object to be "detected" )
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std::vector<Point2f> obj_corners(4);
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obj_corners[0] = Point(0,0);
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obj_corners[1] = Point( img1.cols, 0 );
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obj_corners[2] = Point( img1.cols, img1.rows );
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obj_corners[3] = Point( 0, img1.rows );
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std::vector<Point2f> scene_corners(4);
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Mat H = findHomography( obj, scene, RANSAC );
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perspectiveTransform( obj_corners, scene_corners, H);
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scene_corners_ = scene_corners;
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//-- Draw lines between the corners (the mapped object in the scene - image_2 )
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line( img_matches,
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scene_corners[0] + Point2f( (float)img1.cols, 0), scene_corners[1] + Point2f( (float)img1.cols, 0),
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Scalar( 0, 255, 0), 2, LINE_AA );
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line( img_matches,
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scene_corners[1] + Point2f( (float)img1.cols, 0), scene_corners[2] + Point2f( (float)img1.cols, 0),
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Scalar( 0, 255, 0), 2, LINE_AA );
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line( img_matches,
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scene_corners[2] + Point2f( (float)img1.cols, 0), scene_corners[3] + Point2f( (float)img1.cols, 0),
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Scalar( 0, 255, 0), 2, LINE_AA );
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line( img_matches,
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scene_corners[3] + Point2f( (float)img1.cols, 0), scene_corners[0] + Point2f( (float)img1.cols, 0),
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Scalar( 0, 255, 0), 2, LINE_AA );
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return img_matches;
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}
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////////////////////////////////////////////////////
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// This program demonstrates the usage of SURF_OCL.
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// use cpu findHomography interface to calculate the transformation matrix
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int main(int argc, char* argv[])
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{
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const char* keys =
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"{ h help | | print help message }"
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"{ l left | box.png | specify left image }"
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"{ r right | box_in_scene.png | specify right image }"
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"{ o output | SURF_output.jpg | specify output save path }"
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"{ m cpu_mode | | run without OpenCL }";
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CommandLineParser cmd(argc, argv, keys);
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if (cmd.has("help"))
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{
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std::cout << "Usage: surf_matcher [options]" << std::endl;
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std::cout << "Available options:" << std::endl;
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cmd.printMessage();
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return EXIT_SUCCESS;
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}
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if (cmd.has("cpu_mode"))
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{
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ocl::setUseOpenCL(false);
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std::cout << "OpenCL was disabled" << std::endl;
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}
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UMat img1, img2;
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std::string outpath = cmd.get<std::string>("o");
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std::string leftName = cmd.get<std::string>("l");
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imread(leftName, IMREAD_GRAYSCALE).copyTo(img1);
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if(img1.empty())
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{
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std::cout << "Couldn't load " << leftName << std::endl;
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cmd.printMessage();
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return EXIT_FAILURE;
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}
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std::string rightName = cmd.get<std::string>("r");
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imread(rightName, IMREAD_GRAYSCALE).copyTo(img2);
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if(img2.empty())
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{
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std::cout << "Couldn't load " << rightName << std::endl;
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cmd.printMessage();
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return EXIT_FAILURE;
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}
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double surf_time = 0.;
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//declare input/output
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std::vector<KeyPoint> keypoints1, keypoints2;
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std::vector<DMatch> matches;
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UMat _descriptors1, _descriptors2;
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Mat descriptors1 = _descriptors1.getMat(ACCESS_RW),
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descriptors2 = _descriptors2.getMat(ACCESS_RW);
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//instantiate detectors/matchers
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SURFDetector surf;
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SURFMatcher<BFMatcher> matcher;
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//-- start of timing section
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for (int i = 0; i <= LOOP_NUM; i++)
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{
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if(i == 1) workBegin();
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surf(img1.getMat(ACCESS_READ), Mat(), keypoints1, descriptors1);
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surf(img2.getMat(ACCESS_READ), Mat(), keypoints2, descriptors2);
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matcher.match(descriptors1, descriptors2, matches);
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}
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workEnd();
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std::cout << "FOUND " << keypoints1.size() << " keypoints on first image" << std::endl;
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std::cout << "FOUND " << keypoints2.size() << " keypoints on second image" << std::endl;
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surf_time = getTime();
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std::cout << "SURF run time: " << surf_time / LOOP_NUM << " ms" << std::endl<<"\n";
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std::vector<Point2f> corner;
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Mat img_matches = drawGoodMatches(img1.getMat(ACCESS_READ), img2.getMat(ACCESS_READ), keypoints1, keypoints2, matches, corner);
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//-- Show detected matches
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namedWindow("surf matches", 0);
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imshow("surf matches", img_matches);
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imwrite(outpath, img_matches);
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waitKey(0);
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return EXIT_SUCCESS;
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}
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