lena.png:

pattern.png:

class MatchingDemo { public void run(String inFile, String templateFile, String outFile, int match_method) { System.out.println("\nRunning Template Matching"); Mat img = Highgui.imread(inFile); Mat templ = Highgui.imread(templateFile); // / Create the result matrix int result_cols = img.cols() - templ.cols() + 1; int result_rows = img.rows() - templ.rows() + 1; Mat result = new Mat(result_rows, result_cols, CvType.CV_32FC1); // / Do the Matching and Normalize Imgproc.matchTemplate(img, templ, result, match_method); Core.normalize(result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat()); Highgui.imwrite("out2.png", result); // / Localizing the best match with minMaxLoc MinMaxLocResult mmr = Core.minMaxLoc(result); Point matchLoc; if (match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED) { matchLoc = mmr.minLoc; System.out.println(mmr.minVal); } else { matchLoc = mmr.maxLoc; System.out.println(mmr.maxVal); } // / Show me what you got Core.rectangle(img, matchLoc, new Point(matchLoc.x + templ.cols(), matchLoc.y + templ.rows()), new Scalar(0, 255, 0)); // Save the visualized detection. System.out.println("Writing " + outFile); Highgui.imwrite(outFile, img); } } public class TemplateMatching { public static void main(String[] args) { System.loadLibrary("opencv_java249"); new MatchingDemo().run("lena.png", "pattern.png", "output.png", Imgproc.TM_CCOEFF); } }
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