Java Mat.submat方法代碼示例

import org.opencv.core.Mat; //導入方法依賴的package包/類
/**
 * Gets the average color of the object
 *
 * @param img      The image matrix, of any color size
 * @param imgSpace The image's color space
 * @return The average color of the region
 */
public Color averageColor(Mat img, ColorSpace imgSpace) {
    //Coerce values to stay within screen dimensions
    double leftX = MathUtil.coerce(0, img.cols() - 1, left());
    double rightX = MathUtil.coerce(0, img.cols() - 1, right());

    double topY = MathUtil.coerce(0, img.rows() - 1, top());
    double bottomY = MathUtil.coerce(0, img.rows() - 1, bottom());

    //Input points into array for calculation
    //TODO rectangular submatrix-based calculation isn't perfectly accurate when you have ellipses or weird shapes
    Mat subMat = img.submat((int) topY, (int) bottomY, (int) leftX, (int) rightX);

    //Calculate average and return new color instance
    return Color.create(Core.mean(subMat), imgSpace);
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
private void process(Mat f)
  {
  	// grayscale toggle
      if (grayscaleToggle.isSelected()) Imgproc.cvtColor(f, f, Imgproc.COLOR_BGR2GRAY);
      
      // add image to frame
if (thenkToggle.isSelected() && thenkMat != null)
{
	Rect roi = new Rect(f.cols()-thenkMat.cols(), f.rows()-thenkMat.rows(), thenkMat.cols(), thenkMat.rows());
	Mat thenkROI = f.submat(roi);

	Core.addWeighted(thenkROI, 1.0, thenkMat, 1.0, 0.0, thenkROI);
}

  }
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
private Mat cropFingerprint(Mat src) {
    int rowStart = (int) (CameraOverlayView.PADDING * src.rows());
    int rowEnd = (int) ((1 - CameraOverlayView.PADDING) * src.rows());
    int colStart = (int) (CameraOverlayView.PADDING * src.cols());
    int colEnd = (int) ((1 - CameraOverlayView.PADDING) * src.cols());
    Range rowRange = new Range(rowStart, rowEnd);
    Range colRange = new Range(colStart, colEnd);
    return src.submat(rowRange, colRange);
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
/**
 * Calculate ridge frequency.
 */
private double ridgeFrequency(Mat ridgeSegment, Mat segmentMask, Mat ridgeOrientation, Mat frequencies, int blockSize, int windowSize, int minWaveLength, int maxWaveLength) {

    int rows = ridgeSegment.rows();
    int cols = ridgeSegment.cols();

    Mat blockSegment;
    Mat blockOrientation;
    Mat frequency;

    for (int y = 0; y < rows - blockSize; y += blockSize) {
        for (int x = 0; x < cols - blockSize; x += blockSize) {
            blockSegment = ridgeSegment.submat(y, y + blockSize, x, x + blockSize);
            blockOrientation = ridgeOrientation.submat(y, y + blockSize, x, x + blockSize);
            frequency = calculateFrequency(blockSegment, blockOrientation, windowSize, minWaveLength, maxWaveLength);
            frequency.copyTo(frequencies.rowRange(y, y + blockSize).colRange(x, x + blockSize));
        }
    }

    // mask out frequencies calculated for non ridge regions
    Core.multiply(frequencies, segmentMask, frequencies, 1.0, CvType.CV_32FC1);

    // find median frequency over all the valid regions of the image.
    double medianFrequency = medianFrequency(frequencies);

    // the median frequency value used across the whole fingerprint gives a more satisfactory result
    Core.multiply(segmentMask, Scalar.all(medianFrequency), frequencies, 1.0, CvType.CV_32FC1);

    return medianFrequency;
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
/**
 * <p>Build a template from a specific eye area previously substracted
 * uses detectMultiScale for this area, then uses minMaxLoc method to
 * detect iris from the detected eye</p>
 *
 * @param area Preformatted Area
 * @param size minimum iris size
 * @param grayMat image in gray
 * @param rgbaMat image in color
 * @param detectorEye Haar Cascade classifier
 * @return built template
 */
@NonNull
private static Mat buildTemplate(Rect area, final int size,
                                 @NonNull Mat grayMat,
                                 @NonNull Mat rgbaMat,
                                 CascadeClassifier detectorEye) {
    Mat template = new Mat();
    Mat graySubMatEye = grayMat.submat(area);
    MatOfRect eyes = new MatOfRect();
    Rect eyeTemplate;
    detectorEye.detectMultiScale(graySubMatEye, eyes, 1.15, 2,
            Objdetect.CASCADE_FIND_BIGGEST_OBJECT
                    | Objdetect.CASCADE_SCALE_IMAGE, new Size(EYE_MIN_SIZE, EYE_MIN_SIZE),
            new Size());

    Rect[] eyesArray = eyes.toArray();
    if (eyesArray.length > 0) {
        Rect e = eyesArray[0];
        e.x = area.x + e.x;
        e.y = area.y + e.y;
        Rect eyeRectangle = getEyeArea((int) e.tl().x,
                (int) (e.tl().y + e.height * 0.4),
                e.width,
                (int) (e.height * 0.6));
        graySubMatEye = grayMat.submat(eyeRectangle);
        Mat rgbaMatEye = rgbaMat.submat(eyeRectangle);


        Core.MinMaxLocResult minMaxLoc = Core.minMaxLoc(graySubMatEye);

        FaceDrawerOpenCV.drawIrisCircle(rgbaMatEye, minMaxLoc);
        Point iris = new Point();
        iris.x = minMaxLoc.minLoc.x + eyeRectangle.x;
        iris.y = minMaxLoc.minLoc.y + eyeRectangle.y;
        eyeTemplate = getEyeArea((int) iris.x - size / 2,
                (int) iris.y
                        - size / 2, size, size);
        FaceDrawerOpenCV.drawEyeRectangle(eyeTemplate, rgbaMat);
        template = (grayMat.submat(eyeTemplate)).clone();
    }
    return template;
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
public static Mat transEstimateEachChannel(Mat img, int patchSz, double airlight, double lambda, double fTrans) {
	int rows = img.rows();
	int cols = img.cols();
	Mat T = new Mat(rows, cols, img.type());
	for (int i = 0; i < rows; i += patchSz) {
		for (int j = 0; j < cols; j += patchSz) {
			int endRow = i + patchSz > rows ? rows : i + patchSz;
			int endCol = j + patchSz > cols ? cols : j + patchSz;
			Mat blkIm = img.submat(i, endRow, j, endCol);
			double Trans = BlkTransEstimate.blkEstimateEachChannel(blkIm, airlight, lambda, fTrans);
			for (int m = i; m < endRow; m++) for (int n = j; n < endCol; n++) T.put(m, n, Trans);
		}
	}
	return T;
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
private static Mat computeTrans (Mat img, int patchSz, int rows, int cols, int type, double[] airlight, double lambda, double fTrans) {
	Mat T = new Mat(rows, cols, type);
	for (int i = 0; i < rows; i += patchSz) {
		for (int j = 0; j < cols; j += patchSz) {
			int endRow = i + patchSz > rows ? rows : i + patchSz;
			int endCol = j + patchSz > cols ? cols : j + patchSz;
			Mat blkIm = img.submat(i, endRow, j, endCol);
			double Trans = BlkTransEstimate.blkEstimate(blkIm, airlight, lambda, fTrans);
			for (int m = i; m < endRow; m++) for (int n = j; n < endCol; n++) T.put(m, n, Trans);
		}
	}
	return T;
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
public static ArrayList<Mat> ExtractImageBoxes(Mat boxes, Mat img, int method){
	ArrayList<Mat> imBox = new ArrayList<Mat>();
	for(int i = 0; i < boxes.height(); i++){
		Mat imR = img.submat((int)boxes.get(i,0)[0]+2,(int)boxes.get(i,0)[0] + (int)boxes.get(i,2)[0]-4,
							 (int)boxes.get(i,1)[0]+2,(int)boxes.get(i,1)[0] + (int)boxes.get(i,3)[0]-4);
							 
							 
		Imgproc.resize(imR,imR,new Size(28,28),0,0,method);
		imR = Processing.binarize(imR,Imgproc.THRESH_BINARY);

		imBox.add(imR.reshape(0,1));
	}
	
	return imBox;
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
public static double[] estimate(Mat img, int blockSize) {
	int rows = img.rows();
	int cols = img.cols();
	while (rows * cols > blockSize) {
		int midRow = (int) Math.floor(rows / 2.0);
		int midCol = (int) Math.floor(cols / 2.0);
		// divided image into 4 rectangular region
		Mat[] subIm = new Mat[4];
		subIm[0] = img.submat(0, midRow, 0, midCol); // left-top corner
		subIm[1] = img.submat(midRow, rows, 0, midCol); // right-top corner
		subIm[2] = img.submat(0, midRow, midCol, cols); // left-bottom corner
		subIm[3] = img.submat(midRow, rows, midCol, cols); // right-bottom corner
		// for each sub-image, calculate its score (mean - standard deviation)
		double[] score = new double[4];
		score[0] = calculateScore(subIm[0]);
		score[1] = calculateScore(subIm[1]);
		score[2] = calculateScore(subIm[2]);
		score[3] = calculateScore(subIm[3]);
		int index = 0;
		for (int i = 1; i < score.length; i++) {
			if (score[index] < score[i]) index = i;
		}
		img = subIm[index].clone();
		rows = img.rows();
		cols = img.cols();
	}
	// get the selected region and select the correct air-light
	int index_X = 0;
	int index_Y = 0;
	double pointValue = Double.MAX_VALUE;
	for (int i = 0; i < img.rows(); i++) {
		for (int j = 0; j < img.cols(); j++) {
			double[] data = img.get(i, j);
			double tmpValue = Math.sqrt(Math.pow(data[0] - 255.0, 2.0) + Math.pow(data[1] - 255.0, 2.0) + Math.pow(data[2] - 255.0, 2.0));
			if (pointValue > tmpValue) {
				index_X = i;
				index_Y = j;
				pointValue = tmpValue;
			}
		}
	}
	return img.get(index_X, index_Y);
}
 

import org.opencv.core.Mat; //導入方法依賴的package包/類
private Mat getFadeImg(Mat interimImage) {

//        Mat result = getBlendImg();

        int borderImgHeight = (int) Math.round(interimImage.cols() * .1);
        if ((borderImgHeight % 2) == 1)
            borderImgHeight++;


        Mat blendImg = getBlendImg(interimImage, borderImgHeight);

        // Calculate the cutoff in the mInterimImage:
        // Note the same formula is used in NativeWrapper
        float overlapHalf = .1f;
        int patchHeight = (int) Math.round(borderImgHeight * (.5 + overlapHalf));
        int cutOff = Math.round(patchHeight - (float) borderImgHeight / 2);
        int cutPatchHeight = patchHeight - cutOff;
        if (cutOff <= 0 || cutPatchHeight <= 0)
            return interimImage;

        Mat result = interimImage.rowRange(cutOff, interimImage.rows()-cutOff).clone();

        Mat subMatBlendedTop = result.submat(0, patchHeight-cutOff, 0, result.cols());
        blendImg.submat(cutPatchHeight, blendImg.rows(), 0, result.cols()).copyTo(subMatBlendedTop);

        Mat subMatBlendedBottom = result.submat(result.rows()-cutPatchHeight, result.rows(), 0, result.cols());
        blendImg.submat(0, cutPatchHeight, 0, result.cols()).copyTo(subMatBlendedBottom);

        return result;

    }