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initial commit
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import org.opencv.core.Core;
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import org.opencv.core.Mat;
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import org.opencv.core.MatOfDMatch;
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import org.opencv.core.MatOfKeyPoint;
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import org.opencv.features2d.DescriptorMatcher;
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import org.opencv.features2d.Features2d;
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import org.opencv.highgui.HighGui;
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import org.opencv.imgcodecs.Imgcodecs;
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import org.opencv.xfeatures2d.SURF;
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class SURFMatching {
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public void run(String[] args) {
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String filename1 = args.length > 1 ? args[0] : "../data/box.png";
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String filename2 = args.length > 1 ? args[1] : "../data/box_in_scene.png";
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Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.IMREAD_GRAYSCALE);
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Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.IMREAD_GRAYSCALE);
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if (img1.empty() || img2.empty()) {
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System.err.println("Cannot read images!");
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System.exit(0);
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}
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//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
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double hessianThreshold = 400;
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int nOctaves = 4, nOctaveLayers = 3;
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boolean extended = false, upright = false;
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SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);
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MatOfKeyPoint keypoints1 = new MatOfKeyPoint(), keypoints2 = new MatOfKeyPoint();
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Mat descriptors1 = new Mat(), descriptors2 = new Mat();
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detector.detectAndCompute(img1, new Mat(), keypoints1, descriptors1);
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detector.detectAndCompute(img2, new Mat(), keypoints2, descriptors2);
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//-- Step 2: Matching descriptor vectors with a brute force matcher
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// Since SURF is a floating-point descriptor NORM_L2 is used
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DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);
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MatOfDMatch matches = new MatOfDMatch();
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matcher.match(descriptors1, descriptors2, matches);
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//-- Draw matches
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Mat imgMatches = new Mat();
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Features2d.drawMatches(img1, keypoints1, img2, keypoints2, matches, imgMatches);
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HighGui.imshow("Matches", imgMatches);
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HighGui.waitKey(0);
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System.exit(0);
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}
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}
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public class SURFMatchingDemo {
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public static void main(String[] args) {
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// Load the native OpenCV library
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
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new SURFMatching().run(args);
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}
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}
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