Open Source Computer Vision Library https://opencv.org/
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#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/3d.hpp>
#include <iostream>
#include <iomanip>
using namespace std;
using namespace cv;
static void help(char** argv)
{
cout
<< "This is a sample usage of AffineFeature detector/extractor.\n"
<< "And this is a C++ version of samples/python/asift.py\n"
<< "Usage: " << argv[0] << "\n"
<< " [ --feature=<sift|orb|brisk> ] # Feature to use.\n"
<< " [ --flann ] # use Flann-based matcher instead of bruteforce.\n"
<< " [ --maxlines=<number(50 as default)> ] # The maximum number of lines in visualizing the matching result.\n"
<< " [ --image1=<image1(aero1.jpg as default)> ]\n"
<< " [ --image2=<image2(aero3.jpg as default)> ] # Path to images to compare."
<< endl;
}
static double timer()
{
return getTickCount() / getTickFrequency();
}
int main(int argc, char** argv)
{
vector<String> fileName;
cv::CommandLineParser parser(argc, argv,
"{help h ||}"
"{feature|brisk|}"
"{flann||}"
"{maxlines|50|}"
"{image1|aero1.jpg|}{image2|aero3.jpg|}");
if (parser.has("help"))
{
help(argv);
return 0;
}
string feature = parser.get<string>("feature");
bool useFlann = parser.has("flann");
int maxlines = parser.get<int>("maxlines");
fileName.push_back(samples::findFile(parser.get<string>("image1")));
fileName.push_back(samples::findFile(parser.get<string>("image2")));
if (!parser.check())
{
parser.printErrors();
cout << "See --help (or missing '=' between argument name and value?)" << endl;
return 1;
}
Mat img1 = imread(fileName[0], IMREAD_GRAYSCALE);
Mat img2 = imread(fileName[1], IMREAD_GRAYSCALE);
if (img1.empty())
{
cerr << "Image " << fileName[0] << " is empty or cannot be found" << endl;
return 1;
}
if (img2.empty())
{
cerr << "Image " << fileName[1] << " is empty or cannot be found" << endl;
return 1;
}
Ptr<Feature2D> backend;
Ptr<DescriptorMatcher> matcher;
if (feature == "sift")
{
backend = SIFT::create();
if (useFlann)
matcher = DescriptorMatcher::create("FlannBased");
else
matcher = DescriptorMatcher::create("BruteForce");
}
else if (feature == "orb")
{
backend = ORB::create();
if (useFlann)
matcher = makePtr<FlannBasedMatcher>(makePtr<flann::LshIndexParams>(6, 12, 1));
else
matcher = DescriptorMatcher::create("BruteForce-Hamming");
}
else if (feature == "brisk")
{
backend = BRISK::create();
if (useFlann)
matcher = makePtr<FlannBasedMatcher>(makePtr<flann::LshIndexParams>(6, 12, 1));
else
matcher = DescriptorMatcher::create("BruteForce-Hamming");
}
else
{
cerr << feature << " is not supported. See --help" << endl;
return 1;
}
cout << "extracting with " << feature << "..." << endl;
Ptr<AffineFeature> ext = AffineFeature::create(backend);
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 " << (useFlann ? "flann" : "bruteforce") << "..." << 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);
// Mat vis2 = Mat::zeros(max(h1, h2), w1+w2, CV_8U);
// Mat warp1;
// warpPerspective(img1, warp1, H, Size(w1, h1));
// warp1.copyTo(Mat(vis2, Rect(0, 0, w1, h1)));
// img2.copyTo(Mat(vis2, Rect(w1, 0, w2, h2)));
// imshow("warped", vis2);
waitKey();
cout << "done" << endl;
return 0;
}