Example usage for org.opencv.core Core subtract

List of usage examples for org.opencv.core Core subtract

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Introduction

In this page you can find the example usage for org.opencv.core Core subtract.

Prototype

public static void subtract(Mat src1, Scalar src2, Mat dst)

Source Link

Usage

From source file:Questao1.java

void subtracao() {
    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

    Core.subtract(image1, image2, output);
    Imgcodecs.imwrite("subtracao.jpg", output);
    showResult("subtracao.jpg");
}

From source file:ch.zhaw.facerecognitionlibrary.Helpers.FaceDetection.java

License:Open Source License

public Eyes getEyes(Mat img) {
    double halfWidth = img.cols() / 2;
    double height = img.rows();
    double[] values = new double[4];
    values[0] = 0;//from  w  w w . java2 s  . com
    values[1] = 0;
    values[2] = halfWidth;
    values[3] = height;
    Rect rightHalf = new Rect(values);
    values[0] = halfWidth;
    Rect leftHalf = new Rect(values);
    MatOfRect rightEyes = new MatOfRect();
    MatOfRect leftEyes = new MatOfRect();

    Mat rightHalfImg = img.submat(rightHalf);
    rightEyeDetector.detectMultiScale(rightHalfImg, rightEyes);
    Mat leftHalfImg = img.submat(leftHalf);
    leftEyeDetector.detectMultiScale(leftHalfImg, leftEyes);

    if (rightEyes.empty() || leftEyes.empty() || rightEyes.toArray().length > 1
            || leftEyes.toArray().length > 1) {
        return null;
    }

    Rect rightEye = rightEyes.toArray()[0];
    Rect leftEye = leftEyes.toArray()[0];

    MatOfFloat rightPoint = new MatOfFloat(rightEye.x + rightEye.width / 2, rightEye.y + rightEye.height / 2);
    MatOfFloat leftPoint = new MatOfFloat(img.cols() / 2 + leftEye.x + leftEye.width / 2,
            leftEye.y + leftEye.height / 2);

    MatOfFloat diff = new MatOfFloat();
    Core.subtract(leftPoint, rightPoint, diff);
    double angle = Core.fastAtan2(diff.toArray()[1], diff.toArray()[0]);
    double dist = Core.norm(leftPoint, rightPoint, Core.NORM_L2);
    Eyes eyes = new Eyes(dist, rightPoint, leftPoint, angle);
    return eyes;
}

From source file:ch.zhaw.facerecognitionlibrary.PreProcessor.PreProcessor.java

License:Open Source License

public void normalize01(Mat norm) {
    Core.normalize(norm, norm, 0.0, 1.0, Core.NORM_MINMAX, CvType.CV_64FC1);
    Core.MinMaxLocResult minmax = Core.minMaxLoc(norm);
    Scalar min = new Scalar(minmax.minVal);
    Core.subtract(norm, min, norm);
    minmax = Core.minMaxLoc(norm);//w  w w. ja  v a  2  s . c  om
    Scalar max = new Scalar(minmax.maxVal);
    Core.divide(norm, max, norm);
}

From source file:ch.zhaw.facerecognitionlibrary.Recognition.Eigenfaces.java

License:Open Source License

public String recognize(Mat img, String expectedLabel) {
    // Ignore/*ww  w .jav a  2s.  c om*/
    img = img.reshape(1, 1);
    // Subtract mean
    img.convertTo(img, CvType.CV_32F);
    Core.subtract(img, Psi, img);
    // Project to subspace
    Mat projected = getFeatureVector(img);
    // Save all points of image for tSNE
    img.convertTo(img, CvType.CV_8U);
    addImage(projected, expectedLabel, true);
    //addImage(projected, expectedLabel);
    Mat distance = new Mat(Omega.rows(), 1, CvType.CV_64FC1);
    for (int i = 0; i < Omega.rows(); i++) {
        double dist = Core.norm(projected.row(0), Omega.row(i), Core.NORM_L2);
        distance.put(i, 0, dist);
    }
    Mat sortedDist = new Mat(Omega.rows(), 1, CvType.CV_8UC1);
    Core.sortIdx(distance, sortedDist, Core.SORT_EVERY_COLUMN + Core.SORT_ASCENDING);
    // Give back the name of the found person
    int index = (int) (sortedDist.get(0, 0)[0]);
    return labelMap.getKey(labelList.get(index));
}

From source file:ch.zhaw.facerecognitionlibrary.Recognition.Eigenfaces.java

License:Open Source License

private void computePhi() {
    Mat Psi_repeated = new Mat();
    Core.repeat(Psi, Gamma.rows(), 1, Psi_repeated);
    Core.subtract(Gamma, Psi_repeated, Phi);
}

From source file:com.shootoff.camera.Camera.java

License:Open Source License

public static Mat colorTransfer(Mat source, Mat target) {
    Mat src = new Mat();
    Mat dst = new Mat();

    Imgproc.cvtColor(source, src, Imgproc.COLOR_BGR2Lab);
    Imgproc.cvtColor(target, dst, Imgproc.COLOR_BGR2Lab);

    ArrayList<Mat> src_channels = new ArrayList<Mat>();
    ArrayList<Mat> dst_channels = new ArrayList<Mat>();
    Core.split(src, src_channels);//from ww  w  . ja  v  a 2s .c  o  m
    Core.split(dst, dst_channels);

    for (int i = 0; i < 3; i++) {
        MatOfDouble src_mean = new MatOfDouble(), src_std = new MatOfDouble();
        MatOfDouble dst_mean = new MatOfDouble(), dst_std = new MatOfDouble();
        Core.meanStdDev(src_channels.get(i), src_mean, src_std);
        Core.meanStdDev(dst_channels.get(i), dst_mean, dst_std);

        dst_channels.get(i).convertTo(dst_channels.get(i), CvType.CV_64FC1);
        Core.subtract(dst_channels.get(i), dst_mean, dst_channels.get(i));
        Core.divide(dst_std, src_std, dst_std);
        Core.multiply(dst_channels.get(i), dst_std, dst_channels.get(i));
        Core.add(dst_channels.get(i), src_mean, dst_channels.get(i));
        dst_channels.get(i).convertTo(dst_channels.get(i), CvType.CV_8UC1);
    }

    Core.merge(dst_channels, dst);

    Imgproc.cvtColor(dst, dst, Imgproc.COLOR_Lab2BGR);

    return dst;
}

From source file:com.sikulix.core.Finder.java

License:Open Source License

private Mat doFindMatch(Element target, Mat base, Mat probe) {
    if (SX.isNull(probe)) {
        probe = target.getContent();//from  w w w . j  a  v a  2s .c  o m
    }
    Mat result = new Mat();
    Mat plainBase = base;
    Mat plainProbe = probe;
    if (!target.isPlainColor()) {
        Imgproc.matchTemplate(base, probe, result, Imgproc.TM_CCOEFF_NORMED);
    } else {
        if (target.isBlack()) {
            Core.bitwise_not(base, plainBase);
            Core.bitwise_not(probe, plainProbe);
        }
        Imgproc.matchTemplate(plainBase, plainProbe, result, Imgproc.TM_SQDIFF_NORMED);
        Core.subtract(Mat.ones(result.size(), CvType.CV_32F), result, result);
    }
    return result;
}

From source file:com.trandi.opentld.tld.Tld.java

License:Apache License

/**
 * Output: resized zero-mean patch/pattern
 * @param inImg INPUT, outPattern OUTPUT
 * @return stdev//  ww  w  . ja  v  a  2s  .c  o m
 */
private static double resizeZeroMeanStdev(final Mat inImg, Mat outPattern, int patternSize) {
    if (inImg == null || outPattern == null) {
        return -1;
    }

    Imgproc.resize(inImg, outPattern, new Size(patternSize, patternSize));
    final MatOfDouble mean = new MatOfDouble();
    final MatOfDouble stdev = new MatOfDouble();
    Core.meanStdDev(outPattern, mean, stdev);
    outPattern.convertTo(outPattern, CvType.CV_32F);
    Core.subtract(outPattern, new Scalar(mean.toArray()[0]), outPattern);

    return stdev.toArray()[0];
}

From source file:com.wallerlab.compcellscope.calcDPCTask.java

License:BSD License

protected Long doInBackground(Mat... matrix_list) {
    //int count = urls.length;
    Mat in1 = matrix_list[0];//from  www  .  j  a  v  a  2 s  . c  om
    Mat in2 = matrix_list[1];
    Mat outputMat = matrix_list[2];

    Mat Mat1 = new Mat(in1.width(), in1.height(), in1.type());
    Mat Mat2 = new Mat(in2.width(), in2.height(), in2.type());
    in1.copyTo(Mat1);
    in2.copyTo(Mat2);

    Imgproc.cvtColor(Mat1, Mat1, Imgproc.COLOR_RGBA2GRAY, 1);
    Imgproc.cvtColor(Mat2, Mat2, Imgproc.COLOR_RGBA2GRAY, 1);

    Mat output = new Mat(Mat1.width(), Mat1.height(), CvType.CV_8UC4);
    Mat dpcSum = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1);
    Mat dpcDifference = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1);
    Mat dpcImgF = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1);

    /*
    Log.d(TAG,String.format("Mat1 format is %.1f-%.1f, type: %d",Mat1.size().width,Mat1.size().height,Mat1.type()));
    Log.d(TAG,String.format("Mat2 format is %.1f-%.1f, type: %d",Mat2.size().width,Mat2.size().height,Mat2.type()));
    */

    // Convert to Floats
    Mat1.convertTo(Mat1, CvType.CV_32FC1);
    Mat2.convertTo(Mat2, CvType.CV_32FC1);
    Core.add(Mat1, Mat2, dpcSum);
    Core.subtract(Mat1, Mat2, dpcDifference);
    Core.divide(dpcDifference, dpcSum, dpcImgF);
    Core.add(dpcImgF, new Scalar(1.0), dpcImgF); // Normalize to 0-2.0
    Core.multiply(dpcImgF, new Scalar(110), dpcImgF); // Normalize to 0-255
    dpcImgF.convertTo(output, CvType.CV_8UC1); // Convert back into RGB
    Imgproc.cvtColor(output, output, Imgproc.COLOR_GRAY2RGBA, 4);

    dpcSum.release();
    dpcDifference.release();
    dpcImgF.release();
    Mat1.release();
    Mat2.release();

    Mat maskedImg = Mat.zeros(output.rows(), output.cols(), CvType.CV_8UC4);
    int radius = maskedImg.width() / 2 + 25;
    Core.circle(maskedImg, new Point(maskedImg.width() / 2, maskedImg.height() / 2), radius,
            new Scalar(255, 255, 255), -1, 8, 0);
    output.copyTo(outputMat, maskedImg);
    output.release();
    maskedImg.release();
    return null;
}

From source file:com.wallerlab.compcellscope.MultiModeViewActivity.java

License:BSD License

public Mat calcDPC(Mat in1, Mat in2, Mat out) {
    Mat Mat1 = new Mat(in1.width(), in1.height(), in1.type());
    Mat Mat2 = new Mat(in2.width(), in2.height(), in2.type());
    in1.copyTo(Mat1);/*from w ww .  j a v  a2 s  . c  om*/
    in2.copyTo(Mat2);

    Imgproc.cvtColor(Mat1, Mat1, Imgproc.COLOR_RGBA2GRAY, 1);
    Imgproc.cvtColor(Mat2, Mat2, Imgproc.COLOR_RGBA2GRAY, 1);

    Mat output = new Mat(Mat1.width(), Mat1.height(), CvType.CV_8UC4);
    Mat dpcSum = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1);
    Mat dpcDifference = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1);
    Mat dpcImgF = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1);

    /*
    Log.d(TAG,String.format("Mat1 format is %.1f-%.1f, type: %d",Mat1.size().width,Mat1.size().height,Mat1.type()));
    Log.d(TAG,String.format("Mat2 format is %.1f-%.1f, type: %d",Mat2.size().width,Mat2.size().height,Mat2.type()));
    */

    // Convert to Floats
    Mat1.convertTo(Mat1, CvType.CV_32FC1);
    Mat2.convertTo(Mat2, CvType.CV_32FC1);
    Core.add(Mat1, Mat2, dpcSum);
    Core.subtract(Mat1, Mat2, dpcDifference);
    Core.divide(dpcDifference, dpcSum, dpcImgF);
    Core.add(dpcImgF, new Scalar(1.0), dpcImgF); // Normalize to 0-2.0
    Core.multiply(dpcImgF, new Scalar(110), dpcImgF); // Normalize to 0-255
    dpcImgF.convertTo(output, CvType.CV_8UC1); // Convert back into RGB
    Imgproc.cvtColor(output, output, Imgproc.COLOR_GRAY2RGBA, 4);

    dpcSum.release();
    dpcDifference.release();
    dpcImgF.release();
    Mat1.release();
    Mat2.release();

    Mat maskedImg = Mat.zeros(output.rows(), output.cols(), CvType.CV_8UC4);
    int radius = maskedImg.width() / 2 + 25;
    Core.circle(maskedImg, new Point(maskedImg.width() / 2, maskedImg.height() / 2), radius,
            new Scalar(255, 255, 255), -1, 8, 0);
    output.copyTo(out, maskedImg);
    output.release();
    maskedImg.release();
    return out;
}