public static void cvt_YUVtoGRAY(Mat src, Mat dst) {
/** convert YUV image to RGB then GRAY colorspace */
mSrc = new Mat();
src.copyTo(mSrc);
Imgproc.cvtColor(mSrc, dst, Imgproc.COLOR_YUV420sp2RGB);
Imgproc.cvtColor(dst, dst, Imgproc.COLOR_RGB2GRAY);
}
private static Bitmap canny(Bitmap image) {
// convert image to matrix
Mat Mat1 = new Mat(image.getWidth(), image.getHeight(), CvType.CV_32FC1);
Utils.bitmapToMat(image, Mat1);
// create temporary matrix2
Mat Mat2 = new Mat(image.getWidth(), image.getHeight(), CvType.CV_32FC1);
// convert image to grayscale
Imgproc.cvtColor(Mat1, Mat2, Imgproc.COLOR_BGR2GRAY);
// doing a gaussian blur prevents getting a lot of false hits
Imgproc.GaussianBlur(Mat2, Mat1, new Size(3, 3), 2, 2); // ?
// now apply canny function
int param_threshold1 = 25; // manually defined
int param_threshold2 = param_threshold1 * 3; // Cannys recommendation
Imgproc.Canny(Mat1, Mat2, param_threshold1, param_threshold2);
// ?
Imgproc.cvtColor(Mat2, Mat1, Imgproc.COLOR_GRAY2BGRA, 4);
// convert matrix to output bitmap
Bitmap output = Bitmap.createBitmap(image.getWidth(), image.getHeight(), Bitmap.Config.RGB_565);
Utils.matToBitmap(Mat1, output);
return output;
}
public static Mat warp(Mat inputMat, Mat startM, int factor) {
int resultWidth = 400 * factor;
int resultHeight = 240 * factor;
Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC4);
Point ocvPOut1 = new Point(0, 0);
Point ocvPOut2 = new Point(0, resultHeight);
Point ocvPOut3 = new Point(resultWidth, resultHeight);
Point ocvPOut4 = new Point(resultWidth, 0);
List<Point> dest = new ArrayList<Point>();
dest.add(ocvPOut1);
dest.add(ocvPOut2);
dest.add(ocvPOut3);
dest.add(ocvPOut4);
Mat endM = Converters.vector_Point2f_to_Mat(dest);
Mat perspectiveTransform = Imgproc.getPerspectiveTransform(startM, endM);
Imgproc.warpPerspective(
inputMat,
outputMat,
perspectiveTransform,
new Size(resultWidth, resultHeight),
Imgproc.INTER_AREA);
Imgproc.GaussianBlur(outputMat, outputMat, new org.opencv.core.Size(5, 5), 5);
Imgproc.resize(outputMat, outputMat, new Size(resultWidth / factor, resultHeight / factor));
Imgproc.threshold(outputMat, outputMat, 127, 255, Imgproc.THRESH_TOZERO);
return outputMat;
}
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());
}
}
/**
* 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;
}
/**
* Locate rectangles in an image
*
* @param grayImage Grayscale image
* @return Rectangle locations
*/
public RectangleLocationResult locateRectangles(Mat grayImage) {
Mat gray = grayImage.clone();
// Filter out some noise
Filter.downsample(gray, 2);
Filter.upsample(gray, 2);
Mat cacheHierarchy = new Mat();
Mat grayTemp = new Mat();
List<Rectangle> rectangles = new ArrayList<>();
List<Contour> contours = new ArrayList<>();
Imgproc.Canny(gray, grayTemp, 0, THRESHOLD_CANNY, APERTURE_CANNY, true);
Filter.dilate(gray, 2);
List<MatOfPoint> contoursTemp = new ArrayList<>();
// Find contours - the parameters here are very important to compression and retention
Imgproc.findContours(
grayTemp, contoursTemp, cacheHierarchy, Imgproc.CV_RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
// For each contour, test whether the contour is a rectangle
// List<Contour> contours = new ArrayList<>();
MatOfPoint2f approx = new MatOfPoint2f();
for (MatOfPoint co : contoursTemp) {
MatOfPoint2f matOfPoint2f = new MatOfPoint2f(co.toArray());
Contour c = new Contour(co);
// Attempt to fit the contour to the best polygon
Imgproc.approxPolyDP(
matOfPoint2f, approx, c.arcLength(true) * EPLISON_APPROX_TOLERANCE_FACTOR, true);
Contour approxContour = new Contour(approx);
// Make sure the contour is big enough, CLOSED (convex), and has exactly 4 points
if (approx.toArray().length == 4
&& Math.abs(approxContour.area()) > 1000
&& approxContour.isClosed()) {
// TODO contours and rectangles array may not match up, but why would they?
contours.add(approxContour);
// Check each angle to be approximately 90 degrees
double maxCosine = 0;
for (int j = 2; j < 5; j++) {
double cosine =
Math.abs(
MathUtil.angle(
approx.toArray()[j % 4], approx.toArray()[j - 2], approx.toArray()[j - 1]));
maxCosine = Math.max(maxCosine, cosine);
}
if (maxCosine < MAX_COSINE_VALUE) {
// Convert the points to a rectangle instance
rectangles.add(new Rectangle(approx.toArray()));
}
}
}
return new RectangleLocationResult(contours, rectangles);
}
/**
* @param inputImg
* @return Mat
*/
public static Mat watershed(Mat inputImg) {
Mat target = new Mat(inputImg.rows(), inputImg.cols(), CvType.CV_8UC3);
Imgproc.cvtColor(inputImg, target, Imgproc.COLOR_BGR2RGB);
// Conversion to 8UC1 grayscale image
Mat grayScale = new Mat(inputImg.rows(), inputImg.cols(), CvType.CV_32SC1);
Imgproc.cvtColor(inputImg, grayScale, Imgproc.COLOR_BGR2GRAY);
// constructing a 3x3 kernel for morphological opening
Mat openingKernel = Mat.ones(9, 9, CvType.CV_8U);
// яскравість
// target.convertTo(target, -1, 10d * 12 / 100, 0);
// Imgproc.dilate(target, target, new Mat(), new Point(-1, -1), 1);
Size s = new Size(27, 27);
Imgproc.GaussianBlur(target, target, s, 1.7);
Imgproc.morphologyEx(target, target, Imgproc.MORPH_OPEN, openingKernel);
// dilation operation for extracting the background
// Imgproc.dilate(target, target, openingKernel);
// Imgproc.erode(target, target, new Mat(), new Point(-1, -1), 1);
Mat seeds = new Mat(target.rows(), target.cols(), CvType.CV_32SC1);
for (int i = 0; i < 10; i++) {
seeds.put(((int) Math.random()) % target.rows(), ((int) Math.random()) % target.cols(), i);
}
Imgproc.watershed(target, seeds);
// Imgproc.threshold(target,target, 50, 155, Imgproc.THRESH_BINARY );
return target;
}
private Mat rotateImage(Mat src, double angle) {
Point center = new Point(src.cols() / 2, src.rows() / 2);
double scale = 1.0;
Mat rotateMat = Imgproc.getRotationMatrix2D(center, angle, scale);
Mat dst = new Mat();
Size frameSize = new Size(src.rows(), src.cols());
// adjust dst center point
double m[] = new double[6];
rotateMat.get(0, 0, m);
m[2] += (frameSize.width - src.cols()) / 2;
m[5] += (frameSize.height - src.rows()) / 2;
rotateMat.put(0, 0, m);
Imgproc.warpAffine(
src,
dst,
rotateMat,
frameSize,
Imgproc.INTER_LINEAR,
Imgproc.BORDER_CONSTANT,
Scalar.all(0));
return dst;
}
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;
}
/**
* 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;
}
/**
* @param source
* @param size
* @param delta
* @return Mat
*/
public static Mat Laplacian(Mat source, int size, int delta) {
int ddepth = CvType.CV_16S;
Mat abs_dst, dst;
Imgproc.GaussianBlur(source, source, new Size(3.0, 3.0), 0);
Imgproc.GaussianBlur(source, source, new Size(3, 3), 0, 0, Imgproc.BORDER_DEFAULT);
// cvtColor( src, gray, CV_RGB2GRAY );
/// Apply Laplace function
Imgproc.Laplacian(source, source, CvType.CV_16S, size, 1, delta, Imgproc.BORDER_DEFAULT);
return source;
}
/**
* @param image
* @param size
* @return Mat
*/
public static Mat cannyDetection(Mat image, int size) {
Mat grayImage = new Mat();
Mat detectedEdges = new Mat();
// convert to grayscale
Imgproc.cvtColor(image, grayImage, Imgproc.COLOR_BGR2GRAY);
// reduce noise with a 3x3 kernel
Imgproc.blur(grayImage, detectedEdges, new Size(3, 3));
// canny detector, with ratio of lower:upper threshold of 3:1
Imgproc.Canny(detectedEdges, detectedEdges, size, size / 3, 7, false);
return detectedEdges;
}
private static Bitmap imgtrafo(
Bitmap image1,
Bitmap image2,
int p1_x,
int p1_y,
int p2_x,
int p2_y,
int p3_x,
int p3_y,
int p4_x,
int p4_y) {
// set output size same size as input
int resultWidth = image1.getWidth();
int resultHeight = image1.getHeight();
Mat inputMat = new Mat(image1.getWidth(), image1.getHeight(), CvType.CV_32FC1);
Utils.bitmapToMat(image1, inputMat);
Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_32FC1);
Point ocvPIn1 = new Point(p1_x, p1_y);
Point ocvPIn2 = new Point(p2_x, p2_y);
Point ocvPIn3 = new Point(p3_x, p3_y);
Point ocvPIn4 = new Point(p4_x, p4_y);
List<Point> source = new ArrayList<Point>();
source.add(ocvPIn1);
source.add(ocvPIn2);
source.add(ocvPIn3);
source.add(ocvPIn4);
Mat inputQuad = Converters.vector_Point2f_to_Mat(source);
Point ocvPOut1 = new Point(256, 40); // manually set
Point ocvPOut2 = new Point(522, 62);
Point ocvPOut3 = new Point(455, 479);
Point ocvPOut4 = new Point(134, 404);
List<Point> dest = new ArrayList<Point>();
dest.add(ocvPOut1);
dest.add(ocvPOut2);
dest.add(ocvPOut3);
dest.add(ocvPOut4);
Mat outputQuad = Converters.vector_Point2f_to_Mat(dest);
Mat perspectiveTransform = Imgproc.getPerspectiveTransform(inputQuad, outputQuad);
Imgproc.warpPerspective(
inputMat, outputMat, perspectiveTransform, new Size(resultWidth, resultHeight)); // ?
Bitmap output = Bitmap.createBitmap(resultWidth, resultHeight, Bitmap.Config.RGB_565);
Utils.matToBitmap(outputMat, output);
return output;
}
public boolean hasChanges(Mat current) {
int PIXEL_DIFF_THRESHOLD = 5;
int IMAGE_DIFF_THRESHOLD = 5;
Mat bg = new Mat();
Mat cg = new Mat();
Mat diff = new Mat();
Mat tdiff = new Mat();
Imgproc.cvtColor(base, bg, Imgproc.COLOR_BGR2GRAY);
Imgproc.cvtColor(current, cg, Imgproc.COLOR_BGR2GRAY);
Core.absdiff(bg, cg, diff);
Imgproc.threshold(diff, tdiff, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
if (Core.countNonZero(tdiff) <= IMAGE_DIFF_THRESHOLD) {
return false;
}
Imgproc.threshold(diff, diff, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
Imgproc.dilate(diff, diff, new Mat());
Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
Imgproc.morphologyEx(diff, diff, Imgproc.MORPH_CLOSE, se);
List<MatOfPoint> points = new ArrayList<MatOfPoint>();
Mat contours = new Mat();
Imgproc.findContours(diff, points, contours, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
int n = 0;
for (Mat pm : points) {
log(lvl, "(%d) %s", n++, pm);
printMatI(pm);
}
log(lvl, "contours: %s", contours);
printMatI(contours);
return true;
}
public void processFrame(CameraEvents.Frame frameEvent) {
if (service.getActivityMode() != ActivityEvent.Mode.WARP) return;
if (mode == Mode.SAMPLEWARPPLANE || mode == Mode.SAMPLEWARPGLASS) {
synchronized (this) {
if (!isSetup) setupMatrices();
if (captureSample) {
captureSample = false;
Log.d(TAG, "Warp: Capturing Sample");
Mat frame = frameEvent.getCameraFrame().getRGB();
byte[] frameJPEG = frameEvent.getCameraFrame().getJPEG();
if (sampleBGR == null
|| sampleBGR.height() != frame.height()
|| sampleBGR.width() != frame.width())
sampleBGR = new Mat(frame.rows(), frame.cols(), CvType.CV_8UC3);
Imgproc.cvtColor(frame, sampleBGR, Imgproc.COLOR_RGB2BGR);
useSample = true;
// TODO: Specialize it for this group/device
com.dappervision.wearscript.Utils.eventBusPost(
new SendEvent("warpsample", "", ValueFactory.createRawValue(frameJPEG)));
}
}
}
if (busy) return;
synchronized (this) {
busy = true;
if (!isSetup) setupMatrices();
if (mode == Mode.CAM2GLASS) {
Mat inputBGR;
Mat frame = frameEvent.getCameraFrame().getRGB();
if (frameBGR == null
|| frameBGR.height() != frame.height()
|| frameBGR.width() != frame.width())
frameBGR = new Mat(frame.rows(), frame.cols(), CvType.CV_8UC3);
Mat hSmallToGlassMat = getHSmallToGlassMat(frame.rows(), frame.cols());
if (hSmallToGlassMat == null) {
Log.w(TAG, "Warp: Bad size");
busy = false;
return;
}
Imgproc.cvtColor(frame, frameBGR, Imgproc.COLOR_RGB2BGR);
inputBGR = frameBGR;
Imgproc.warpPerspective(
inputBGR, frameWarp, hSmallToGlassMat, new Size(frameWarp.width(), frameWarp.height()));
drawFrame(frameWarp);
}
busy = false;
}
}
public Mat convertImageToBlackWhite(Mat imageMat, boolean applyGaussBlur) {
Mat imageCloneMat = imageMat.clone();
if (applyGaussBlur) {
Imgproc.GaussianBlur(imageCloneMat, imageCloneMat, new Size(3, 3), 0, 0);
}
double thresh =
Imgproc.threshold(
imageCloneMat, imageCloneMat, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU);
Imgproc.threshold(imageCloneMat, imageCloneMat, thresh, 255, Imgproc.THRESH_BINARY_INV);
return (imageCloneMat);
}
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 void init_sd_imgs() {
try {
if (Environment.getExternalStorageState().equals(Environment.MEDIA_MOUNTED)) {
File sdCardDir = Environment.getExternalStorageDirectory();
String str_sd_dir = sdCardDir.getCanonicalPath();
String str_path = str_sd_dir + "/andrcvs/";
File dir = new File(str_path);
Toast.makeText(MainActivity.this, str_path, Toast.LENGTH_LONG).show();
if (!dir.exists()) {
dir.mkdirs();
for (int idx = 0; idx < res_imgs.length; idx++) {
Bitmap bmp = BitmapFactory.decodeResource(getResources(), res_imgs[idx]);
Mat mat_rgb = new Mat();
Utils.bitmapToMat(bmp, mat_rgb);
String str_idx = String.format("%04d", idx + 1);
String str_fn = str_path + "image_" + str_idx + ".jpg";
Imgproc.cvtColor(mat_rgb, mat_rgb, Imgproc.COLOR_BGR2RGB);
Imgcodecs.imwrite(str_fn, mat_rgb);
}
}
}
} catch (Exception e) {
e.printStackTrace();
}
}
@Override
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
// Imgproc.bilateralFilter(inputFrame.gray(), inputFrame.rgba(), 9, 75, 75);
/* if (captureBackground) {
captureBackground = false;
background = new Mat(inputFrame.gray(), new Rect(0, 0, inputFrame.gray().width(), inputFrame.gray().height()));
}
if (background == null) {
return inputFrame.rgba();
}
return background;*/
background = inputFrame.gray();
Imgproc.cvtColor(background, mRgb, Imgproc.COLOR_GRAY2RGB);
/*Imgproc.erode(mFGMask, mFGMask, new Mat());
Imgproc.dilate(mFGMask, mFGMask, new Mat());
Imgproc.findContours(mFGMask, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);
Imgproc.drawContours(mRgb, contours, -1, new Scalar(255, 0, 0), 2);*/
return mRgb;
}
public static void main(String[] args) {
try {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
File input = new File("traffic_signal.jpg");
BufferedImage image = ImageIO.read(input);
byte[] data = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
Mat mat = new Mat(image.getHeight(), image.getWidth(), CvType.CV_8UC3);
mat.put(0, 0, data);
Mat mat1 = new Mat(image.getHeight(), image.getWidth(), CvType.CV_8UC1);
Imgproc.cvtColor(mat, mat1, Imgproc.COLOR_RGB2GRAY);
byte[] data1 = new byte[mat1.rows() * mat1.cols() * (int) (mat1.elemSize())];
mat1.get(0, 0, data1);
BufferedImage image1 =
new BufferedImage(mat1.cols(), mat1.rows(), BufferedImage.TYPE_BYTE_GRAY);
image1.getRaster().setDataElements(0, 0, mat1.cols(), mat1.rows(), data1);
File ouptut = new File("output\\grayscale_" + new Date().getTime() + ".jpg");
ImageIO.write(image1, "jpg", ouptut);
} catch (Exception e) {
System.out.println("Error: " + e.getMessage());
}
}
/**
* Process the given Mat, finding, classifying and displaying all resistors present.
*
* @param originalImg The image to parse
*/
private void parseImage(Mat originalImg) {
Mat workingCopy = new Mat();
originalImg.copyTo(workingCopy);
// blur the original image to form resistor blobs. should remove white/silver/grey bands which
// would otherwise
// get picked up as part of the background, leads or shadows.
Mat blurred = new Mat();
// Imgproc.medianBlur(workingCopy, blurred, 29);
Imgproc.blur(workingCopy, blurred, new Size(20, 20)); // faster
// get a mask off the background
Mat resistorMask = new Mat();
generateResistorMask(blurred, Imgproc.THRESH_BINARY).copyTo(resistorMask);
// find countours in mask
List<MatOfPoint> contours = getContours(resistorMask, originalImg, true);
// extract resistors in input image
List<Resistor> resistors = extractResistorsFromContours(contours, originalImg, true);
// segment and extract colour bands for each resistor
extractColourBandsAndClassify(resistors, true);
// calculate and display resistance value for each resistor based on classified colour bands
calculateAndDisplayResistanceValues(resistors);
}
private void createFigureBitmap() {
if (mFigureBitmap != null) {
mFigureBitmap.recycle();
}
// ビットマップ用意
String targetPngFileUri = Camera72Utils.getTargetPngFileFullPath(mDirectory, mCurTarget);
mFigureBitmap = BitmapFactory.decodeFile(targetPngFileUri, mOpt);
// 抜き出しまだな場合
if (mFigureBitmap == null) {
Utils.showToast(mContext, R.string.not_extract_message);
String targetJpgFileUri = Camera72Utils.getFgJpgFileFullPath(mDirectory, mCurTarget);
mFigureBitmap = BitmapFactory.decodeFile(targetJpgFileUri, mOpt);
}
Log.i(TAG, "targetPngFile = " + targetPngFileUri);
// OpenCV用オブジェクトを用意
Mat mat = new Mat(mFigureBitmap.getHeight(), mFigureBitmap.getWidth(), CvType.CV_8UC4);
org.opencv.android.Utils.bitmapToMat(mFigureBitmap, mat);
// OpenCVで明るさ調整する
Core.convertScaleAbs(mat, mat, mCvBrightScalar, 0);
// OpenCVでぼかし調整する
Imgproc.GaussianBlur(mat, mat, mCvGaussianSize, 0);
// Bitmapに戻す
org.opencv.android.Utils.matToBitmap(mat, mFigureBitmap);
}
public void run() {
do {
synchronized (JavaCameraView.this) {
try {
JavaCameraView.this.wait();
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
if (!mStopThread) {
switch (mPreviewFormat) {
case Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA:
Imgproc.cvtColor(mBaseMat, mFrameChain[mChainIdx], Imgproc.COLOR_YUV2RGBA_NV21, 4);
break;
case Highgui.CV_CAP_ANDROID_GREY_FRAME:
mFrameChain[mChainIdx] = mBaseMat.submat(0, mFrameHeight, 0, mFrameWidth);
break;
default:
Log.e(TAG, "Invalid frame format! Only RGBA and Gray Scale are supported!");
}
;
if (!mFrameChain[mChainIdx].empty()) deliverAndDrawFrame(mFrameChain[mChainIdx]);
mChainIdx = 1 - mChainIdx;
}
} while (!mStopThread);
Log.d(TAG, "Finish processing thread");
}
public MarkerTracker(Mat image, Mat template) {
this.image = image;
this.template = template;
Log.i("Marker-Tracker", "image is null?::" + (null == image));
imgGray = new Mat(image.size(), image.type());
templGray = new Mat(template.size(), template.type());
// Convert them to grayscale
Imgproc.cvtColor(image, imgGray, Imgproc.COLOR_BGRA2GRAY);
// Core.normalize(imgGray, imgGray, 0, 255, Core.NORM_MINMAX);
// Mat grayImage02 = new Mat(image02.rows(), image02.cols(), image02.type());
Imgproc.cvtColor(template, templGray, Imgproc.COLOR_BGRA2GRAY);
// Core.normalize(templGray, templGray, 0, 255, Core.NORM_MINMAX);
}
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));
}
@Override
protected Void doInBackground(Void... params) {
publishProgress(0);
Mat hsvImg = heatmap(data, progressDialog);
Mat finishedImage = new Mat();
Imgproc.cvtColor(hsvImg, finishedImage, Imgproc.COLOR_HSV2BGR);
File mediaStorageDir =
new File(Environment.getExternalStorageDirectory().getPath(), "images/Colored_Images");
if (!mediaStorageDir.exists()) {
if (!mediaStorageDir.mkdirs()) {
Log.e(TAG, "failed to create directory");
return null;
}
}
String timeStamp = new SimpleDateFormat("yyyyMMdd_HHmmss").format(new Date());
Log.v(
TAG,
"SAVING: " + mediaStorageDir.getPath() + File.separator + "scan_" + timeStamp + ".jpg");
Highgui.imwrite(
mediaStorageDir.getPath() + File.separator + "scan_" + timeStamp + ".jpg", finishedImage);
return null;
}
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);
}
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;
}
@Override
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
Imgproc.cvtColor(mRgba, grayScaleImage, Imgproc.COLOR_RGBA2RGB);
MatOfRect faces = new MatOfRect();
// detect faces
if (cascadeClassifier != null) {
cascadeClassifier.detectMultiScale(
grayScaleImage,
faces,
1.1,
2,
2,
new Size(absoluteFaceSize, absoluteFaceSize),
new Size());
}
Rect[] facesArray = faces.toArray();
for (int i = 0; i < facesArray.length; i++)
Core.rectangle(mRgba, facesArray[i].tl(), facesArray[i].br(), new Scalar(0, 255, 0, 255), 3);
if (facesArray.length > 0) {
facesInASecond.add(true);
} else {
facesInASecond.add(false);
}
return mRgba;
}
/**
* @param source
* @param delta
* @return Mat
*/
public static Mat Sobel(Mat source, int delta) {
Mat grey = new Mat();
Imgproc.cvtColor(source, grey, Imgproc.COLOR_BGR2GRAY);
Mat sobelx = new Mat();
Imgproc.Sobel(grey, sobelx, CvType.CV_32F, 1, delta);
double minVal, maxVal;
Core.MinMaxLocResult minMaxLocResult = Core.minMaxLoc(sobelx);
minVal = minMaxLocResult.minVal;
maxVal = minMaxLocResult.maxVal;
Mat draw = new Mat();
sobelx.convertTo(
draw, CvType.CV_8U, 255.0 / (maxVal - minVal), -minVal * 255.0 / (maxVal - minVal));
return draw;
}
