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/*
* matching_test.cpp
*
* Created on: Oct 17, 2010
* Author: ethan
*/
#include "opencv2/core/core.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <vector>
#include <iostream>
using namespace cv;
using namespace std;
//Copy (x,y) location of descriptor matches found from KeyPoint data structures into Point2f vectors
static void matches2points(const vector<DMatch>& matches, const vector<KeyPoint>& kpts_train,
const vector<KeyPoint>& kpts_query, vector<Point2f>& pts_train, vector<Point2f>& pts_query)
{
pts_train.clear();
pts_query.clear();
pts_train.reserve(matches.size());
pts_query.reserve(matches.size());
for (size_t i = 0; i < matches.size(); i++)
{
const DMatch& match = matches[i];
pts_query.push_back(kpts_query[match.queryIdx].pt);
pts_train.push_back(kpts_train[match.trainIdx].pt);
}
}
static double match(const vector<KeyPoint>& /*kpts_train*/, const vector<KeyPoint>& /*kpts_query*/, DescriptorMatcher& matcher,
const Mat& train, const Mat& query, vector<DMatch>& matches)
{
double t = (double)getTickCount();
matcher.match(query, train, matches); //Using features2d
return ((double)getTickCount() - t) / getTickFrequency();
}
static void help()
{
cout << "This program shows how to use BRIEF descriptor to match points in features2d" << endl <<
"It takes in two images, finds keypoints and matches them displaying matches and final homography warped results" << endl <<
"Usage: " << endl <<
"image1 image2 " << endl <<
"Example: " << endl <<
"box.png box_in_scene.png " << endl;
}
const char* keys =
{
"{1| |box.png |the first image}"
"{2| |box_in_scene.png|the second image}"
};
int main(int argc, const char ** argv)
{
help();
CommandLineParser parser(argc, argv, keys);
string im1_name = parser.get<string>("1");
string im2_name = parser.get<string>("2");
Mat im1 = imread(im1_name, CV_LOAD_IMAGE_GRAYSCALE);
Mat im2 = imread(im2_name, CV_LOAD_IMAGE_GRAYSCALE);
if (im1.empty() || im2.empty())
{
cout << "could not open one of the images..." << endl;
cout << "the cmd parameters have next current value: " << endl;
parser.printParams();
return 1;
}
double t = (double)getTickCount();
FastFeatureDetector detector(50);
BriefDescriptorExtractor extractor(32); //this is really 32 x 8 matches since they are binary matches packed into bytes
vector<KeyPoint> kpts_1, kpts_2;
detector.detect(im1, kpts_1);
detector.detect(im2, kpts_2);
t = ((double)getTickCount() - t) / getTickFrequency();
cout << "found " << kpts_1.size() << " keypoints in " << im1_name << endl << "fount " << kpts_2.size()
<< " keypoints in " << im2_name << endl << "took " << t << " seconds." << endl;
Mat desc_1, desc_2;
cout << "computing descriptors..." << endl;
t = (double)getTickCount();
extractor.compute(im1, kpts_1, desc_1);
extractor.compute(im2, kpts_2, desc_2);
t = ((double)getTickCount() - t) / getTickFrequency();
cout << "done computing descriptors... took " << t << " seconds" << endl;
//Do matching using features2d
cout << "matching with BruteForceMatcher<Hamming>" << endl;
BFMatcher matcher_popcount(NORM_HAMMING);
vector<DMatch> matches_popcount;
double pop_time = match(kpts_1, kpts_2, matcher_popcount, desc_1, desc_2, matches_popcount);
cout << "done BruteForceMatcher<Hamming> matching. took " << pop_time << " seconds" << endl;
vector<Point2f> mpts_1, mpts_2;
matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2); //Extract a list of the (x,y) location of the matches
vector<char> outlier_mask;
Mat H = findHomography(mpts_2, mpts_1, RANSAC, 1, outlier_mask);
Mat outimg;
drawMatches(im2, kpts_2, im1, kpts_1, matches_popcount, outimg, Scalar::all(-1), Scalar::all(-1), outlier_mask);
imshow("matches - popcount - outliers removed", outimg);
Mat warped;
Mat diff;
warpPerspective(im2, warped, H, im1.size());
imshow("warped", warped);
absdiff(im1,warped,diff);
imshow("diff", diff);
waitKey();
return 0;
}
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