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922108060d
* Implement ASIFT in C++ * '>>' should be '> >' within a nested template * add a sample for asift usage * bugfix empty keypoints cause crash * simpler initialization for mask * suppress the number of lines * correct tex document * type casting * add descriptorsize for asift * smaller testdata for asift * more smaller test data * add OpenCV short license header
200 lines
6.4 KiB
C++
200 lines
6.4 KiB
C++
#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/features2d.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/calib3d.hpp>
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#include <iostream>
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#include <iomanip>
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using namespace std;
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using namespace cv;
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static void help(char** argv)
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{
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cout
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<< "This is a sample usage of AffineFeature detector/extractor.\n"
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<< "And this is a C++ version of samples/python/asift.py\n"
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<< "Usage: " << argv[0] << "\n"
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<< " [ --feature=<sift|orb|brisk> ] # Feature to use.\n"
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<< " [ --flann ] # use Flann-based matcher instead of bruteforce.\n"
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<< " [ --maxlines=<number(50 as default)> ] # The maximum number of lines in visualizing the matching result.\n"
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<< " [ --image1=<image1(aero1.jpg as default)> ]\n"
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<< " [ --image2=<image2(aero3.jpg as default)> ] # Path to images to compare."
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<< endl;
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}
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static double timer()
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{
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return getTickCount() / getTickFrequency();
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}
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int main(int argc, char** argv)
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{
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vector<String> fileName;
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cv::CommandLineParser parser(argc, argv,
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"{help h ||}"
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"{feature|brisk|}"
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"{flann||}"
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"{maxlines|50|}"
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"{image1|aero1.jpg|}{image2|aero3.jpg|}");
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if (parser.has("help"))
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{
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help(argv);
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return 0;
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}
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string feature = parser.get<string>("feature");
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bool useFlann = parser.has("flann");
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int maxlines = parser.get<int>("maxlines");
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fileName.push_back(samples::findFile(parser.get<string>("image1")));
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fileName.push_back(samples::findFile(parser.get<string>("image2")));
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if (!parser.check())
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{
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parser.printErrors();
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cout << "See --help (or missing '=' between argument name and value?)" << endl;
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return 1;
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}
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Mat img1 = imread(fileName[0], IMREAD_GRAYSCALE);
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Mat img2 = imread(fileName[1], IMREAD_GRAYSCALE);
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if (img1.empty())
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{
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cerr << "Image " << fileName[0] << " is empty or cannot be found" << endl;
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return 1;
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}
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if (img2.empty())
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{
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cerr << "Image " << fileName[1] << " is empty or cannot be found" << endl;
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return 1;
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}
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Ptr<Feature2D> backend;
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Ptr<DescriptorMatcher> matcher;
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if (feature == "sift")
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{
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backend = SIFT::create();
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if (useFlann)
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matcher = DescriptorMatcher::create("FlannBased");
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else
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matcher = DescriptorMatcher::create("BruteForce");
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}
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else if (feature == "orb")
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{
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backend = ORB::create();
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if (useFlann)
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matcher = makePtr<FlannBasedMatcher>(makePtr<flann::LshIndexParams>(6, 12, 1));
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else
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matcher = DescriptorMatcher::create("BruteForce-Hamming");
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}
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else if (feature == "brisk")
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{
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backend = BRISK::create();
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if (useFlann)
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matcher = makePtr<FlannBasedMatcher>(makePtr<flann::LshIndexParams>(6, 12, 1));
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else
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matcher = DescriptorMatcher::create("BruteForce-Hamming");
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}
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else
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{
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cerr << feature << " is not supported. See --help" << endl;
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return 1;
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}
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cout << "extracting with " << feature << "..." << endl;
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Ptr<AffineFeature> ext = AffineFeature::create(backend);
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vector<KeyPoint> kp1, kp2;
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Mat desc1, desc2;
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ext->detectAndCompute(img1, Mat(), kp1, desc1);
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ext->detectAndCompute(img2, Mat(), kp2, desc2);
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cout << "img1 - " << kp1.size() << " features, "
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<< "img2 - " << kp2.size() << " features"
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<< endl;
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cout << "matching with " << (useFlann ? "flann" : "bruteforce") << "..." << endl;
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double start = timer();
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// match and draw
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vector< vector<DMatch> > rawMatches;
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vector<Point2f> p1, p2;
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vector<float> distances;
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matcher->knnMatch(desc1, desc2, rawMatches, 2);
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// filter_matches
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for (size_t i = 0; i < rawMatches.size(); i++)
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{
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const vector<DMatch>& m = rawMatches[i];
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if (m.size() == 2 && m[0].distance < m[1].distance * 0.75)
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{
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p1.push_back(kp1[m[0].queryIdx].pt);
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p2.push_back(kp2[m[0].trainIdx].pt);
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distances.push_back(m[0].distance);
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}
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}
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vector<uchar> status;
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vector< pair<Point2f, Point2f> > pointPairs;
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Mat H = findHomography(p1, p2, status, RANSAC);
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int inliers = 0;
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for (size_t i = 0; i < status.size(); i++)
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{
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if (status[i])
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{
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pointPairs.push_back(make_pair(p1[i], p2[i]));
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distances[inliers] = distances[i];
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// CV_Assert(inliers <= (int)i);
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inliers++;
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}
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}
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distances.resize(inliers);
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cout << "execution time: " << fixed << setprecision(2) << (timer()-start)*1000 << " ms" << endl;
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cout << inliers << " / " << status.size() << " inliers/matched" << endl;
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cout << "visualizing..." << endl;
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vector<int> indices(inliers);
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cv::sortIdx(distances, indices, SORT_EVERY_ROW+SORT_ASCENDING);
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// explore_match
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int h1 = img1.size().height;
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int w1 = img1.size().width;
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int h2 = img2.size().height;
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int w2 = img2.size().width;
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Mat vis = Mat::zeros(max(h1, h2), w1+w2, CV_8U);
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img1.copyTo(Mat(vis, Rect(0, 0, w1, h1)));
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img2.copyTo(Mat(vis, Rect(w1, 0, w2, h2)));
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cvtColor(vis, vis, COLOR_GRAY2BGR);
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vector<Point2f> corners(4);
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corners[0] = Point2f(0, 0);
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corners[1] = Point2f((float)w1, 0);
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corners[2] = Point2f((float)w1, (float)h1);
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corners[3] = Point2f(0, (float)h1);
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vector<Point2i> icorners;
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perspectiveTransform(corners, corners, H);
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transform(corners, corners, Matx23f(1,0,(float)w1,0,1,0));
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Mat(corners).convertTo(icorners, CV_32S);
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polylines(vis, icorners, true, Scalar(255,255,255));
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for (int i = 0; i < min(inliers, maxlines); i++)
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{
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int idx = indices[i];
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const Point2f& pi1 = pointPairs[idx].first;
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const Point2f& pi2 = pointPairs[idx].second;
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circle(vis, pi1, 2, Scalar(0,255,0), -1);
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circle(vis, pi2 + Point2f((float)w1,0), 2, Scalar(0,255,0), -1);
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line(vis, pi1, pi2 + Point2f((float)w1,0), Scalar(0,255,0));
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}
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if (inliers > maxlines)
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cout << "only " << maxlines << " inliers are visualized" << endl;
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imshow("affine find_obj", vis);
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// Mat vis2 = Mat::zeros(max(h1, h2), w1+w2, CV_8U);
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// Mat warp1;
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// warpPerspective(img1, warp1, H, Size(w1, h1));
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// warp1.copyTo(Mat(vis2, Rect(0, 0, w1, h1)));
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// img2.copyTo(Mat(vis2, Rect(w1, 0, w2, h2)));
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// imshow("warped", vis2);
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waitKey();
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cout << "done" << endl;
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return 0;
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}
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