java类org.opencv.core.Size的实例源码

public static double calibrateCameraExtended(List<Mat> objectPoints, List<Mat> imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List<Mat> rvecs, List<Mat> tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)
{
    Mat objectPoints_mat = Converters.vector_Mat_to_Mat(objectPoints);
    Mat imagePoints_mat = Converters.vector_Mat_to_Mat(imagePoints);
    Mat rvecs_mat = new Mat();
    Mat tvecs_mat = new Mat();
    double retVal = calibrateCameraExtended_2(objectPoints_mat.nativeObj, imagePoints_mat.nativeObj, imageSize.width, imageSize.height, cameraMatrix.nativeObj, distCoeffs.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, stdDeviationsIntrinsics.nativeObj, stdDeviationsExtrinsics.nativeObj, perViewErrors.nativeObj);
    Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
    rvecs_mat.release();
    Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
    tvecs_mat.release();
    return retVal;
}

public static float rectify3Collinear(Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat cameraMatrix3, Mat distCoeffs3, List<Mat> imgpt1, List<Mat> imgpt3, Size imageSize, Mat R12, Mat T12, Mat R13, Mat T13, Mat R1, Mat R2, Mat R3, Mat P1, Mat P2, Mat P3, Mat Q, double alpha, Size newImgSize, Rect roi1, Rect roi2, int flags)
{
    Mat imgpt1_mat = Converters.vector_Mat_to_Mat(imgpt1);
    Mat imgpt3_mat = Converters.vector_Mat_to_Mat(imgpt3);
    double[] roi1_out = new double[4];
    double[] roi2_out = new double[4];
    float retVal = rectify3Collinear_0(cameraMatrix1.nativeObj, distCoeffs1.nativeObj, cameraMatrix2.nativeObj, distCoeffs2.nativeObj, cameraMatrix3.nativeObj, distCoeffs3.nativeObj, imgpt1_mat.nativeObj, imgpt3_mat.nativeObj, imageSize.width, imageSize.height, R12.nativeObj, T12.nativeObj, R13.nativeObj, T13.nativeObj, R1.nativeObj, R2.nativeObj, R3.nativeObj, P1.nativeObj, P2.nativeObj, P3.nativeObj, Q.nativeObj, alpha, newImgSize.width, newImgSize.height, roi1_out, roi2_out, flags);
    if(roi1!=null){ roi1.x = (int)roi1_out[0]; roi1.y = (int)roi1_out[1]; roi1.width = (int)roi1_out[2]; roi1.height = (int)roi1_out[3]; } 
    if(roi2!=null){ roi2.x = (int)roi2_out[0]; roi2.y = (int)roi2_out[1]; roi2.width = (int)roi2_out[2]; roi2.height = (int)roi2_out[3]; } 
    return retVal;
}

public  void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale, double finalThreshold, boolean useMeanshiftGrouping)
{
    Mat foundLocations_mat = foundLocations;
    Mat foundWeights_mat = foundWeights;
    detectMultiScale_0(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height, scale, finalThreshold, useMeanshiftGrouping);

    return;
}

public  void detectMultiScale(Mat image, MatOfRect objects, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize)
{
    Mat objects_mat = objects;
    detectMultiScale_0(nativeObj, image.nativeObj, objects_mat.nativeObj, scaleFactor, minNeighbors, flags, minSize.width, minSize.height, maxSize.width, maxSize.height);

    return;
}

public static Mat initCameraMatrix2D(List<MatOfPoint3f> objectPoints, List<MatOfPoint2f> imagePoints, Size imageSize, double aspectRatio)
{
    List<Mat> objectPoints_tmplm = new ArrayList<Mat>((objectPoints != null) ? objectPoints.size() : 0);
    Mat objectPoints_mat = Converters.vector_vector_Point3f_to_Mat(objectPoints, objectPoints_tmplm);
    List<Mat> imagePoints_tmplm = new ArrayList<Mat>((imagePoints != null) ? imagePoints.size() : 0);
    Mat imagePoints_mat = Converters.vector_vector_Point2f_to_Mat(imagePoints, imagePoints_tmplm);
    Mat retVal = new Mat(initCameraMatrix2D_0(objectPoints_mat.nativeObj, imagePoints_mat.nativeObj, imageSize.width, imageSize.height, aspectRatio));

    return retVal;
}

@Override
public int getWidth(Object obj) {
    Camera.Size size = (Camera.Size) obj;
    return size.width;
}

private static Mat filterSingleChannel(Mat p, double s, ArrayList<Mat> Isubchannels, ArrayList<Mat> Ichannels, 
        Mat mean_I_r, Mat mean_I_g, Mat mean_I_b, Mat invrr, Mat invrg, Mat invrb, Mat invgg, Mat invgb, 
        Mat invbb, double r_sub) {
    Mat p_sub = new Mat();
    Imgproc.resize(p, p_sub, new Size(p.cols() / s, p.rows() / s), 0.0, 0.0, Imgproc.INTER_NEAREST);

    Mat mean_p = boxfilter(p_sub, (int) r_sub);

    Mat mean_Ip_r = boxfilter(Isubchannels.get(0).mul(p_sub), (int) r_sub);
    Mat mean_Ip_g = boxfilter(Isubchannels.get(1).mul(p_sub), (int) r_sub);
    Mat mean_Ip_b = boxfilter(Isubchannels.get(2).mul(p_sub), (int) r_sub);

    // convariance of (I, p) in each local patch
    Mat cov_Ip_r = new Mat();
    Mat cov_Ip_g = new Mat();
    Mat cov_Ip_b = new Mat();
    Core.subtract(mean_Ip_r, mean_I_r.mul(mean_p), cov_Ip_r);
    Core.subtract(mean_Ip_g, mean_I_g.mul(mean_p), cov_Ip_g);
    Core.subtract(mean_Ip_b, mean_I_b.mul(mean_p), cov_Ip_b);

    Mat temp1 = new Mat();
    Mat a_r = new Mat();
    Mat a_g = new Mat();
    Mat a_b = new Mat();
    Core.add(invrr.mul(cov_Ip_r), invrg.mul(cov_Ip_g), temp1);
    Core.add(temp1, invrb.mul(cov_Ip_b), a_r);
    Core.add(invrg.mul(cov_Ip_r), invgg.mul(cov_Ip_g), temp1);
    Core.add(temp1, invgb.mul(cov_Ip_b), a_g);
    Core.add(invrb.mul(cov_Ip_r), invgb.mul(cov_Ip_g), temp1);
    Core.add(temp1, invbb.mul(cov_Ip_b), a_b);

    Mat b = new Mat();
    Core.subtract(mean_p, a_r.mul(mean_I_r), b);
    Core.subtract(b, a_g.mul(mean_I_g), b);
    Core.subtract(b, a_b.mul(mean_I_b), b);

    Mat mean_a_r = boxfilter(a_r, (int) r_sub);
    Mat mean_a_g = boxfilter(a_g, (int) r_sub);
    Mat mean_a_b = boxfilter(a_b, (int) r_sub);
    Mat mean_b = boxfilter(b, (int) r_sub);

    Imgproc.resize(mean_a_r, mean_a_r, 
            new Size(Ichannels.get(0).cols(), Ichannels.get(0).rows()), 0.0, 0.0, Imgproc.INTER_LINEAR);
    Imgproc.resize(mean_a_g, mean_a_g, 
            new Size(Ichannels.get(0).cols(), Ichannels.get(0).rows()), 0.0, 0.0, Imgproc.INTER_LINEAR);
    Imgproc.resize(mean_a_b, mean_a_b, 
            new Size(Ichannels.get(0).cols(), Ichannels.get(0).rows()), 0.0, 0.0, Imgproc.INTER_LINEAR);
    Imgproc.resize(mean_b, mean_b, 
            new Size(Ichannels.get(0).cols(), Ichannels.get(0).rows()), 0.0, 0.0, Imgproc.INTER_LINEAR);

    Mat result = new Mat();
    Core.add(mean_a_r.mul(Ichannels.get(0)), mean_a_g.mul(Ichannels.get(1)), temp1);
    Core.add(temp1, mean_a_b.mul(Ichannels.get(2)), temp1);
    Core.add(temp1, mean_b, result);
    return result;
}

public  Size get_winSize()
{

    Size retVal = new Size(get_winSize_0(nativeObj));

    return retVal;
}

public   VideoWriter(String filename, int fourcc, double fps, Size frameSize)
{

    nativeObj = VideoWriter_1(filename, fourcc, fps, frameSize.width, frameSize.height);

    return;
}

public static float initWideAngleProjMap(Mat cameraMatrix, Mat distCoeffs, Size imageSize, int destImageWidth, int m1type, Mat map1, Mat map2, int projType, double alpha)
{

    float retVal = initWideAngleProjMap_0(cameraMatrix.nativeObj, distCoeffs.nativeObj, imageSize.width, imageSize.height, destImageWidth, m1type, map1.nativeObj, map2.nativeObj, projType, alpha);

    return retVal;
}