private void displayMarkerImage(Mat srcImgMat, Mat destImageMat) {
// find location of image segment to be replaced in the destination image.
Rect rect = calculateImageSegmentArea(destImageMat);
Mat destSubmat = destImageMat.submat(rect.y, rect.y + rect.height, rect.x, rect.x + rect.width);
// copy image.
srcImgMat.copyTo(destSubmat);
}
public void performMatch() {
// create feature detectors and feature extractors
FeatureDetector orbDetector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor orbExtractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
// set the keypoints
keyPointImg = new MatOfKeyPoint();
orbDetector.detect(imgGray, keyPointImg);
MatOfKeyPoint keyPointTempl = new MatOfKeyPoint();
orbDetector.detect(templGray, keyPointTempl);
// get the descriptions
descImg = new Mat(image.size(), image.type());
orbExtractor.compute(imgGray, keyPointImg, descImg);
Mat descTempl = new Mat(template.size(), template.type());
orbExtractor.compute(templGray, keyPointTempl, descTempl);
// perform matching
matches = new MatOfDMatch();
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
matcher.match(descImg, descTempl, matches);
Log.i("perform match result", matches.size().toString());
}
void drawFrame(Mat modified) {
// Partly from OpenCV CameraBridgeViewBase.java
if (mCacheBitmap == null) {
mCacheBitmap =
Bitmap.createBitmap(modified.width(), modified.height(), Bitmap.Config.ARGB_8888);
}
boolean bmpValid = true;
if (modified != null) {
try {
Utils.matToBitmap(modified, mCacheBitmap);
} catch (Exception e) {
Log.e(TAG, "Mat type: " + modified);
Log.e(TAG, "Bitmap type: " + mCacheBitmap.getWidth() + "*" + mCacheBitmap.getHeight());
Log.e(TAG, "Utils.matToBitmap() throws an exception: " + e.getMessage());
bmpValid = false;
}
}
if (bmpValid && mCacheBitmap != null) {
Canvas canvas = view.getHolder().lockCanvas();
if (canvas != null) {
canvas.drawColor(0, android.graphics.PorterDuff.Mode.CLEAR);
canvas.drawBitmap(
mCacheBitmap,
new Rect(0, 0, mCacheBitmap.getWidth(), mCacheBitmap.getHeight()),
new Rect(
(canvas.getWidth() - mCacheBitmap.getWidth()) / 2,
(canvas.getHeight() - mCacheBitmap.getHeight()) / 2,
(canvas.getWidth() - mCacheBitmap.getWidth()) / 2 + mCacheBitmap.getWidth(),
(canvas.getHeight() - mCacheBitmap.getHeight()) / 2 + mCacheBitmap.getHeight()),
null);
view.getHolder().unlockCanvasAndPost(canvas);
}
}
}
public void setHsvColor(Scalar hsvColor) {
double minH =
(hsvColor.val[0] >= mColorRadius.val[0]) ? hsvColor.val[0] - mColorRadius.val[0] : 0;
double maxH =
(hsvColor.val[0] + mColorRadius.val[0] <= 255)
? hsvColor.val[0] + mColorRadius.val[0]
: 255;
mLowerBound.val[0] = minH;
mUpperBound.val[0] = maxH;
mLowerBound.val[1] = hsvColor.val[1] - mColorRadius.val[1];
mUpperBound.val[1] = hsvColor.val[1] + mColorRadius.val[1];
mLowerBound.val[2] = hsvColor.val[2] - mColorRadius.val[2];
mUpperBound.val[2] = hsvColor.val[2] + mColorRadius.val[2];
mLowerBound.val[3] = 0;
mUpperBound.val[3] = 255;
Mat spectrumHsv = new Mat(1, (int) (maxH - minH), CvType.CV_8UC3);
for (int j = 0; j < maxH - minH; j++) {
byte[] tmp = {(byte) (minH + j), (byte) 255, (byte) 255};
spectrumHsv.put(0, j, tmp);
}
Imgproc.cvtColor(spectrumHsv, mSpectrum, Imgproc.COLOR_HSV2RGB_FULL, 4);
}
// javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel, withDerivatives, pyrBorder,
// derivBorder, tryReuseInputImage)
public static int buildOpticalFlowPyramid(
Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel,
boolean withDerivatives,
int pyrBorder,
int derivBorder,
boolean tryReuseInputImage) {
Mat pyramid_mat = new Mat();
int retVal =
buildOpticalFlowPyramid_0(
img.nativeObj,
pyramid_mat.nativeObj,
winSize.width,
winSize.height,
maxLevel,
withDerivatives,
pyrBorder,
derivBorder,
tryReuseInputImage);
Converters.Mat_to_vector_Mat(pyramid_mat, pyramid);
pyramid_mat.release();
return retVal;
}
public List<ArtifactDetectedObject> detectObjects(BufferedImage bImage) {
List<ArtifactDetectedObject> detectedObjectList = new ArrayList<>();
Mat image = OpenCVUtils.bufferedImageToMat(bImage);
if (image != null) {
MatOfRect faceDetections = new MatOfRect();
double width = image.width();
double height = image.height();
for (CascadeClassifierHolder objectClassifier : objectClassifiers) {
objectClassifier.cascadeClassifier.detectMultiScale(image, faceDetections);
for (Rect rect : faceDetections.toArray()) {
ArtifactDetectedObject detectedObject =
new ArtifactDetectedObject(
rect.x / width,
rect.y / height,
(rect.x + rect.width) / width,
(rect.y + rect.height) / height,
objectClassifier.conceptIRI,
PROCESS);
detectedObjectList.add(detectedObject);
}
}
}
return detectedObjectList;
}
protected static void rotateXAxis(Mat rotation) {
// get the matrix corresponding to the rotation vector
Mat R = new Mat(3, 3, CvType.CV_64FC1);
Calib3d.Rodrigues(rotation, R);
// create the matrix to rotate 90º around the X axis
// 1, 0, 0
// 0 cos -sin
// 0 sin cos
double[] rot = {
1, 0, 0,
0, 0, -1,
0, 1, 0
};
// multiply both matrix
Mat res = new Mat(3, 3, CvType.CV_64FC1);
double[] prod = new double[9];
double[] a = new double[9];
R.get(0, 0, a);
for (int i = 0; i < 3; i++)
for (int j = 0; j < 3; j++) {
prod[3 * i + j] = 0;
for (int k = 0; k < 3; k++) {
prod[3 * i + j] += a[3 * i + k] * rot[3 * k + j];
}
}
// convert the matrix to a vector with rodrigues back
res.put(0, 0, prod);
Calib3d.Rodrigues(res, rotation);
}
public static void bhadis() {
Mat a =
new Mat(6, 4, CvType.CV_32F) {
{
put(0, 0, 0, 1, 1, 5);
put(1, 0, 1, 0, 2, 4);
put(2, 0, 2, 2, 3, 6);
put(3, 0, 0, 4, 6, 1);
put(4, 0, 5, 4, 6, 1);
put(5, 0, 4, 2, 8, 1);
}
};
Mat b =
new Mat(6, 4, CvType.CV_32F) {
{
put(0, 0, 4, 9, 2, 1);
put(1, 0, 9, 6, 0, 3);
put(2, 0, 2, 0, 8, 6);
put(3, 0, 1, 3, 6, 9);
put(4, 0, 5, 7, 6, 1);
put(5, 0, 4, 2, 8, 1);
}
};
System.out.println(a.dump());
System.out.println(b.dump());
double d = Distance.Bhattacharyya(b, b);
System.out.println("Bhattacharyya distance = " + d);
}
/**
* Finds and extracts all contours in the given Mat. Optionally also removes contours with areas
* below that of MIN_CONTOUR_AREA.
*
* @param mask A mask of all resistors in the image
* @param originalImage The original image from which the mask was created
* @param thresholdByArea If true, remove contours below threshold
* @return The list a found contours
*/
private List<MatOfPoint> getContours(Mat mask, Mat originalImage, boolean thresholdByArea) {
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
Imgproc.findContours(
mask,
contours,
hierarchy,
Imgproc.RETR_EXTERNAL,
Imgproc.CHAIN_APPROX_SIMPLE,
new Point(0, 0));
// remove any remaining noise by only keeping contours which area > threshold
if (thresholdByArea) {
for (int i = 0; i < contours.size(); i++) {
double area = Imgproc.contourArea(contours.get(i));
if (area < MIN_CONTOUR_AREA || area > 6000) {
contours.remove(i);
i--;
}
}
}
Mat drawing = Mat.zeros(originalImage.size(), CvType.CV_8U);
for (int i = 0; i < contours.size(); i++) {
Scalar color = new Scalar(255, 255, 255);
Imgproc.drawContours(drawing, contours, i, color, 4, 8, hierarchy, 0, new Point());
}
paintBR(drawing);
return contours;
}
private void displayMarkersDebug(Mat imgMat, Scalar contourColor, Scalar codesColor) {
ArrayList<MatOfPoint> components = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
DtouchMarker marker = new DtouchMarker();
boolean markerFound = findMarkers(imgMat, marker, components, hierarchy);
if (markerFound) {
String code = codeArrayToString(marker.getCode());
Point codeLocation = new Point(imgMat.cols() / 4, imgMat.rows() / 8);
Core.putText(mRgba, code, codeLocation, Core.FONT_HERSHEY_COMPLEX, 1, codesColor, 3);
Imgproc.drawContours(
mRgba,
components,
marker.getComponentIndex(),
contourColor,
3,
8,
hierarchy,
2,
new Point(0, 0));
}
if (components != null) components.clear();
if (hierarchy != null) hierarchy.release();
components = null;
hierarchy = null;
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
frame = inputFrame.rgba();
outputFrame = frame.clone();
if (homography != null) {
if (markerValue != -1 && markerValue != oldMarkerValue) {
oldMarkerValue = markerValue;
outputLogo = logo.clone();
Core.putText(
outputLogo,
Integer.toString(markerValue),
new Point(5, 505),
Core.FONT_HERSHEY_SIMPLEX,
5,
new Scalar(255, 0, 0),
5);
}
Imgproc.warpPerspective(
outputLogo,
outputFrame,
homography,
new Size(WIDTH, HEIGHT),
Imgproc.INTER_NEAREST,
Imgproc.BORDER_TRANSPARENT,
new Scalar(0));
}
return outputFrame;
}
/**
* Returns square area for image segment.
*
* @param imgMat Source image from which to compute image segment.
* @return square area which contains image segment.
*/
private Rect calculateImageSegmentArea(Mat imgMat) {
int width = imgMat.cols();
int height = imgMat.rows();
double aspectRatio = (double) width / (double) height;
int imgWidth = width / 2;
int imgHeight = height / 2;
// Size of width and height varies of input image can vary. Make the image segment width and
// height equal in order to make
// the image segment square.
// if width is more than the height.
if (aspectRatio > 1) {
// if total height is greater than imgWidth.
if (height > imgWidth) imgHeight = imgWidth;
} else if (aspectRatio < 1) { // height is more than the width.
// if total width is greater than the imgHeight.
if (width > imgHeight) imgWidth = imgHeight;
}
// find the centre position in the source image.
int x = (width - imgWidth) / 2;
int y = (height - imgHeight) / 2;
return new Rect(x, y, imgWidth, imgHeight);
}
/**
* Helper function to convert a Mat into a BufferedImage. Taken from
* http://answers.opencv.org/question/10344/opencv-java-load-image-to-gui Author: 'Lucky Luke'
*
* @param matrix Mat of type CV_8UC3 or CV_8UC1
* @return BufferedImage of type TYPE_3BYTE_BGR or TYPE_BYTE_GRAY
*/
private static BufferedImage matToBufferedImage(Mat matrix) {
int cols = matrix.cols();
int rows = matrix.rows();
int elemSize = (int) matrix.elemSize();
byte[] data = new byte[cols * rows * elemSize];
int type;
matrix.get(0, 0, data);
switch (matrix.channels()) {
case 1:
type = BufferedImage.TYPE_BYTE_GRAY;
break;
case 3:
type = BufferedImage.TYPE_3BYTE_BGR;
// bgr to rgb
byte b;
for (int i = 0; i < data.length; i = i + 3) {
b = data[i];
data[i] = data[i + 2];
data[i + 2] = b;
}
break;
default:
return null;
}
BufferedImage image = new BufferedImage(cols, rows, type);
image.getRaster().setDataElements(0, 0, cols, rows, data);
return image;
}
private void processFrameForMarkersDebug(VideoCapture capture) {
ArrayList<MatOfPoint> components = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
// Get original image.
capture.retrieve(mRgba, Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA);
// Get gray scale image.
capture.retrieve(mGray, Highgui.CV_CAP_ANDROID_GREY_FRAME);
// Get image segment to detect marker.
Mat imgSegmentMat = cloneMarkerImageSegment(mGray);
Mat thresholdedImgMat = new Mat(imgSegmentMat.size(), imgSegmentMat.type());
applyThresholdOnImage(imgSegmentMat, thresholdedImgMat);
copyThresholdedImageToRgbImgMat(thresholdedImgMat, mRgba);
Scalar contourColor = new Scalar(0, 0, 255);
Scalar codesColor = new Scalar(255, 0, 0, 255);
displayMarkersDebug(thresholdedImgMat, contourColor, codesColor);
// displayThresholds(mRgba, codesColor, localThresholds);
displayRectOnImageSegment(mRgba, false);
if (components != null) components.clear();
if (hierarchy != null) hierarchy.release();
components = null;
hierarchy = null;
}
/**
* Order the detected bands into band 1, band 2 and the multiplier. The farthest band from the
* center of the resistor Mat will always be band 1.
*
* <p>Band contours are created from top left to bottom right of the image. Therefore unless
* resistor is perfectly horizontal, the middle band will always be 2nd, and the order just needs
* to be flipped if necessary
*/
public void orderBands() {
// Calculate the center of the resistor image.
Point resistorImageCenter = new Point(resistorMat.cols() / 2, resistorMat.rows() / 2);
double farthestDist = 0;
int band1Idx = 0;
// find the band farthest from the center.
for (int i = 0; i < bands.size(); i++) {
ColourBand cb = bands.get(i);
double dist = euclidDist(resistorImageCenter, cb.center);
if (dist > farthestDist) {
farthestDist = dist;
band1Idx = i;
}
}
// assume bands are already in the correct order band1Idx == 0
orderedBands = bands;
// if bands are in reverse order, reverse the array to get the ordered bands
if (band1Idx == 2) {
java.util.Collections.reverse(orderedBands);
}
}
private Scalar converScalarHsv2Rgba(Scalar hsvColor) {
Mat pointMatRgba = new Mat();
Mat pointMatHsv = new Mat(1, 1, CvType.CV_8UC3, hsvColor);
Imgproc.cvtColor(pointMatHsv, pointMatRgba, Imgproc.COLOR_HSV2RGB_FULL, 4);
return new Scalar(pointMatRgba.get(0, 0));
}
public static void main(String[] args) {
try {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
Mat source = Imgcodecs.imread("test_image.jpg", 0);
Mat destination = new Mat(source.rows(), source.cols(), source.type());
Imgproc.GaussianBlur(source, source, new Size(45, 45), 0);
Imgproc.adaptiveThreshold(
source, source, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, 75, 10);
Core.bitwise_not(source, source);
// Line detection
Mat img2 = null;
Imgproc.cvtColor(source, img2, Imgproc.COLOR_GRAY2RGB);
Mat img3 = null;
Imgproc.cvtColor(source, img3, Imgproc.COLOR_GRAY2RGB);
MatOfInt4 lines = new MatOfInt4();
// Imgproc.HoughLines(img, lines, rho, theta, threshold);
// Write to File
Imgcodecs.imwrite("gaussian.jpg", source);
System.out.println("Success!");
} catch (Exception e) {
System.out.println("Error has occurred: " + e.getMessage());
}
}
private static double perceptualHash(String sourceImagePath, String targetImagePath) {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
Mat matSrc = Imgcodecs.imread(sourceImagePath, Imgcodecs.CV_LOAD_IMAGE_COLOR);
Mat matTrgt = Imgcodecs.imread(targetImagePath, Imgcodecs.CV_LOAD_IMAGE_COLOR);
Mat matSrcResize = new Mat();
Mat matTrgtResize = new Mat();
Imgproc.resize(
matSrc,
matSrcResize,
new Size(matSrc.width(), matSrc.height()),
0,
0,
Imgproc.INTER_NEAREST);
Imgproc.resize(
matTrgt,
matTrgtResize,
new Size(matTrgt.width(), matTrgt.height()),
0,
0,
Imgproc.INTER_LANCZOS4);
Mat matSrcDst = new Mat();
Mat matTrgtDst = new Mat();
Imgproc.resize(matSrcResize, matSrcDst, new Size(8, 8), 0, 0, Imgproc.INTER_CUBIC);
Imgproc.resize(matTrgtResize, matTrgtDst, new Size(8, 8), 0, 0, Imgproc.INTER_CUBIC);
Imgproc.cvtColor(matSrcDst, matSrcDst, Imgproc.COLOR_BGR2GRAY);
Imgproc.cvtColor(matTrgtDst, matTrgtDst, Imgproc.COLOR_BGR2GRAY);
int iAvgSrc = 0, iAvgTrgt = 0;
int[] arrSrc = new int[64];
int[] arrTrgt = new int[64];
for (int i = 0; i < 8; i++) {
byte[] dataSrc = new byte[8];
matSrcDst.get(i, 0, dataSrc);
byte[] dataTrgt = new byte[8];
matTrgtDst.get(i, 0, dataTrgt);
int tmp = i * 8;
for (int j = 0; j < 8; j++) {
int tmpSrc = tmp + j;
arrSrc[tmpSrc] = dataSrc[j] / 4 * 4;
arrTrgt[tmpSrc] = dataTrgt[j] / 4 * 4;
iAvgSrc += arrSrc[tmpSrc];
iAvgTrgt += arrTrgt[tmpSrc];
}
}
iAvgSrc /= 64;
iAvgTrgt /= 64;
for (int i = 0; i < 64; i++) {
arrSrc[i] = (arrSrc[i] >= iAvgSrc) ? 1 : 0;
arrTrgt[i] = (arrTrgt[i] >= iAvgTrgt) ? 1 : 0;
}
int iDiffNum = 0;
for (int i = 0; i < 64; i++) if (arrSrc[i] != arrTrgt[i]) ++iDiffNum;
return 1.0 - (double) iDiffNum / 64;
}
public static Mat findCardNumber(String path) {
Mat mat = Highgui.imread(path);
int x = 0;
int y = (int) (mat.height() * ((double) 30 / 54));
int width = mat.cols();
int height = (int) (mat.height() * ((double) 7 / 54));
return mat.submat(new Rect(x, y, width, height));
}
@Override
public void OnKeypointsFoundForOther(Mat image) {
Bitmap disp =
Bitmap.createBitmap(
image.cols(), image.rows(), Bitmap.Config.ARGB_8888); // Android uses ARGB_8888
Utils.matToBitmap(image, disp);
mImageAdapter.setOtherKeyPointImage(disp);
}
public static void V2M() {
Vector<double[]> v = new Vector<double[]>();
double[] temp = {1.0, 2.0, 3.0, 4.0};
v.add(temp);
v.add(temp);
v.add(temp);
Mat m = DataConverter.jvector2Mat(v);
System.out.println(m.dump());
}
public Mat process(Mat srcImage) {
if (stage == 0) return srcImage;
List<PolygonCv> targets = new ArrayList<>();
PolygonCv bestTarget;
Mat workingImage = srcImage.clone();
_ColorSpace.process(workingImage);
_ColorRange.process(workingImage);
_Erode.process(workingImage);
_Dilate.process(workingImage);
// _GrayScale.process(workingImage);
// _BlackWhite.process(workingImage);
if (stage == 1) return workingImage;
targets = findTargets(workingImage);
workingImage = srcImage.clone();
addTargetingRectangle(workingImage);
if (targets.size() > 0) {
bestTarget = findBestTarget(targets);
if (networkTable != null) {
targetAnalysis(bestTarget); // no return as it simply writes data to netTables
networkTable.putNumber("FrameCount", frameCount++);
}
targetAnalysis(bestTarget, false);
if (stage == 2) return workingImage; // commandline, so don't bother drawing anything
if (stage == 3) {
_OtherTargets.setPolygon(targets);
_OtherTargets.process(workingImage);
_BestTarget.setPolygon(bestTarget);
_BestTarget.process(workingImage);
_Reticle.setCenter(bestTarget.getCenterX(), bestTarget.getMaxY());
_Reticle.setSize(Render.RETICLE_SIZE, Render.RETICLE_SIZE);
_Reticle.process(workingImage);
}
if (stage == 4) {
_BoundingBox.setCenter(bestTarget.getCenterX(), bestTarget.getCenterY());
_BoundingBox.setSize(bestTarget.getHeight() / 2, bestTarget.getWidth() / 2);
_BoundingBox.process(workingImage);
}
}
// _CrossHair.process(workingImage);
return workingImage;
}
Mat setupMatrix(double hSmallToGlass[], double hGlassToSmall[]) {
Mat hSmallToGlassMat = HMatFromArray(hSmallToGlass);
Mat hGlassToSmallMat = hSmallToGlassMat.inv();
double denominator = hGlassToSmallMat.get(2, 2)[0];
for (int i = 0; i < 3; i++)
for (int j = 0; j < 3; j++)
hGlassToSmall[i * 3 + j] = hGlassToSmallMat.get(i, j)[0] / denominator;
return hSmallToGlassMat;
}
private static void printMatI(Mat mat) {
int[] data = new int[mat.channels()];
for (int r = 0; r < mat.rows(); r++) {
for (int c = 0; c < mat.cols(); c++) {
mat.get(r, c, data);
log(lvl, "(%d, %d) %s", r, c, Arrays.toString(data));
}
}
}
public MarkerTracker(Mat image) {
this.image = image;
imgGray = new Mat(image.size(), image.type());
// Convert them to grayscale
Imgproc.cvtColor(image, imgGray, Imgproc.COLOR_BGRA2GRAY);
// Core.normalize(imgGray, imgGray, 0, 255, Core.NORM_MINMAX);
}
public void testGetTrainDescriptors() {
Mat train = new Mat(1, 1, CvType.CV_8U, new Scalar(123));
Mat truth = train.clone();
matcher.add(Arrays.asList(train));
List<Mat> descriptors = matcher.getTrainDescriptors();
assertEquals(1, descriptors.size());
assertMatEqual(truth, descriptors.get(0));
}
/**
* Rotate a Mat by the specified degree
*
* @param src The source Mat
* @param angle The angle by which to rotate by
* @return The rotated Mat
*/
public static Mat rotate(Mat src, double angle) {
int len = src.cols() > src.rows() ? src.cols() : src.rows();
Point pt = new Point(len / 2.0, len / 2.0);
Mat r = Imgproc.getRotationMatrix2D(pt, angle, 1.0);
Mat dst = new Mat();
Imgproc.warpAffine(src, dst, r, new Size(len, len));
return dst;
}
// javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel)
public static int buildOpticalFlowPyramid(
Mat img, List<Mat> pyramid, Size winSize, int maxLevel) {
Mat pyramid_mat = new Mat();
int retVal =
buildOpticalFlowPyramid_1(
img.nativeObj, pyramid_mat.nativeObj, winSize.width, winSize.height, maxLevel);
Converters.Mat_to_vector_Mat(pyramid_mat, pyramid);
pyramid_mat.release();
return retVal;
}
public Mat onCameraFrame(Mat inputFrame) {
inputFrame.copyTo(mRgba);
Point center = new Point(mRgba.width() / 2, mRgba.height() / 2);
double angle = -90;
double scale = 1.0;
Mat mapMatrix = Imgproc.getRotationMatrix2D(center, angle, scale);
Imgproc.warpAffine(mRgba, mGrayMat, mapMatrix, mRgba.size(), Imgproc.INTER_LINEAR);
return mGrayMat;
}
public static BufferedImage bufferedImage(Mat m) {
int type = BufferedImage.TYPE_BYTE_GRAY;
if (m.channels() > 1) {
type = BufferedImage.TYPE_3BYTE_BGR;
}
BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
m.get(
0, 0, ((DataBufferByte) image.getRaster().getDataBuffer()).getData()); // get all the pixels
return image;
}
