Opencv（3.0.0）模板匹配的Java实现

我想使用Opencv匹配给定图片中的模板（小图像）

我从该端口找到以下代码：

问题是启动OpenVC3.0.0，highgui被分解为新的videoio和IMGCodec，下面的代码使用的是highgui

package opencv;

import org.opencv.core.Core;
import org.opencv.core.Core.MinMaxLocResult;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;

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());

        // / 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;
        } else {
            matchLoc = mmr.maxLoc;
        }

        // / 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_java246");
        new MatchingDemo().run(args[0], args[1], args[2], Imgproc.TM_CCOEFF);
    }
}

---

OpenCV 3.0.0不再具有Highui。改用Imgcodecs.imread

点击这个链接

---

读写函数从

org.opencv.highgui.highgui

移动到

org.opencv.imgcodecs.imgcodecs

。 绘图函数从

org.opencv.core.core

移动到

org.opencv.imgproc.imgproc

。 因此，来源变成：

import org.opencv.core.Core;
import org.opencv.core.Core.MinMaxLocResult;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

class MatchingDemo {
    public void run(String inFile, String templateFile, String outFile,
            int match_method) {
        System.out.println("\nRunning Template Matching");

        Mat img = Imgcodecs.imread(inFile);
        Mat templ = Imgcodecs.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());

        // / 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;
        } else {
            matchLoc = mmr.maxLoc;
        }

        // / Show me what you got
        Imgproc.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);
        Imgcodecs.imwrite(outFile, img);

    }
}

public class TemplateMatching {

    public static void main(String[] args) {
        System.loadLibrary("opencv_java300");
        new MatchingDemo().run(args[0], args[1], args[2], Imgproc.TM_CCOEFF);
    }

}

啊，这很简单；）Imgcodecs.imwrite（…）、Imgcodecs.imread（…）、Imgproc.rectangle（…）（就我目前的能力而言）