0810

#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/calib3d.hpp>
#include <iostream>
#include <iomanip>

using namespace std;
using namespace cv;


static double timer()
{
    return getTickCount() / getTickFrequency();
}

int main(int argc, char** argv)
{

    Mat img1 = imread("object.jpg", IMREAD_GRAYSCALE);
    Mat img2 = imread("scene.jpg", IMREAD_GRAYSCALE);
    if (img1.empty())
    {
        cerr << "Image " << "scene.jpg" << " is empty or cannot be found" << endl;
        return 1;
    }
    if (img2.empty())
    {
        cerr << "Image " << "object.jpg" << " is empty or cannot be found" << endl;
        return 1;
    }

    Ptr<Feature2D> backend;
    Ptr<DescriptorMatcher> matcher;

    matcher = DescriptorMatcher::create("FlannBased");
    int maxlines = 50;//매칭된 키포인트를 그려줄 최대 직선 개수 
 

    cout << "extracting with " << "SIFT" << "..." << endl;
    Ptr<SIFT> ext = SIFT::create();
    vector<KeyPoint> kp1, kp2;
    Mat desc1, desc2;

    ext->detectAndCompute(img1, Mat(), kp1, desc1);
    ext->detectAndCompute(img2, Mat(), kp2, desc2);
    cout << "img1 - " << kp1.size() << " features, "
        << "img2 - " << kp2.size() << " features"
        << endl;

    cout << "matching with " << "flann" << "..." << endl;
    double start = timer();

    // match and draw
    vector< vector<DMatch> > rawMatches;
    vector<Point2f> p1, p2;
    vector<float> distances;
    matcher->knnMatch(desc1, desc2, rawMatches, 2);

    // filter_matches
    for (size_t i = 0; i < rawMatches.size(); i++)
    {
        const vector<DMatch>& m = rawMatches[i];
        if (m.size() == 2 && m[0].distance < m[1].distance * 0.75)
        {
            p1.push_back(kp1[m[0].queryIdx].pt);
            p2.push_back(kp2[m[0].trainIdx].pt);
            distances.push_back(m[0].distance);
        }
    }
    vector<uchar> status;
    vector< pair<Point2f, Point2f> > pointPairs;
    Mat H = findHomography(p1, p2, status, RANSAC);
    int inliers = 0;
    for (size_t i = 0; i < status.size(); i++)
    {
        if (status[i])
        {
            pointPairs.push_back(make_pair(p1[i], p2[i]));
            distances[inliers] = distances[i];
            // CV_Assert(inliers <= (int)i);
            inliers++;
        }
    }
    distances.resize(inliers);

    cout << "execution time: " << fixed << setprecision(2) << (timer() - start) * 1000 << " ms" << endl;
    cout << inliers << " / " << status.size() << " inliers/matched" << endl;

    cout << "visualizing..." << endl;
    vector<int> indices(inliers);
    cv::sortIdx(distances, indices, SORT_EVERY_ROW + SORT_ASCENDING);

    // explore_match
    int h1 = img1.size().height;
    int w1 = img1.size().width;
    int h2 = img2.size().height;
    int w2 = img2.size().width;
    Mat vis = Mat::zeros(max(h1, h2), w1 + w2, CV_8U);
    img1.copyTo(Mat(vis, Rect(0, 0, w1, h1)));
    img2.copyTo(Mat(vis, Rect(w1, 0, w2, h2)));
    cvtColor(vis, vis, COLOR_GRAY2BGR);

    vector<Point2f> corners(4);
    corners[0] = Point2f(0, 0);
    corners[1] = Point2f((float)w1, 0);
    corners[2] = Point2f((float)w1, (float)h1);
    corners[3] = Point2f(0, (float)h1);
    vector<Point2i> icorners;
    perspectiveTransform(corners, corners, H);
    transform(corners, corners, Matx23f(1, 0, (float)w1, 0, 1, 0));
    Mat(corners).convertTo(icorners, CV_32S);
    polylines(vis, icorners, true, Scalar(255, 255, 255));

    for (int i = 0; i < min(inliers, maxlines); i++)
    {
        int idx = indices[i];
        const Point2f& pi1 = pointPairs[idx].first;
        const Point2f& pi2 = pointPairs[idx].second;
        circle(vis, pi1, 2, Scalar(0, 255, 0), -1);
        circle(vis, pi2 + Point2f((float)w1, 0), 2, Scalar(0, 255, 0), -1);
        line(vis, pi1, pi2 + Point2f((float)w1, 0), Scalar(0, 255, 0));
    }
    if (inliers > maxlines)
        cout << "only " << maxlines << " inliers are visualized" << endl;
    imshow("affine find_obj", vis);
    waitKey();

    cout << "done" << endl;
    return 0;
}