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;
}
/**
* calculates the center of mass using <code>colorForTrackingHSV</code> and <code>colorRadius
* </code> as radius (in HSV-color space)
*
* @param hsv the frame of which the center of mass should be calculated off
* @return the center of mass as a point in pixel coordinates (i.e. integer)
*/
public Point calcCenterOfMass(Mat hsv) {
blackWhiteMask = new Mat();
Core.inRange(hsv, lowerBound, upperBound, blackWhiteMask);
dilatedMask = new Mat();
Imgproc.dilate(blackWhiteMask, dilatedMask, new Mat());
contour = new ArrayList<MatOfPoint>();
Mat mHierarchy = new Mat();
Mat tempDilatedMask = dilatedMask.clone();
Imgproc.findContours(
tempDilatedMask, contour, mHierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
boundingRect = Imgproc.boundingRect(findLargestContour(contour));
int centerOfMassX = boundingRect.x + boundingRect.width / 2;
int centerOfMassY = boundingRect.y + boundingRect.height / 2;
Point centerOfMass = new Point(centerOfMassX, centerOfMassY);
trackPath.add(centerOfMass);
return centerOfMass;
}
/**
* @param inputImg
* @param minValue
* @param maxValue
* @return Mat
*/
public static Mat thresholding(Mat inputImg, Integer minValue, Integer maxValue) {
Mat frame = inputImg;
// яскравість
// frame.convertTo(frame , -1, 10d * 33 / 100, 0);
// Imgproc.medianBlur(frame,frame, 17);
// Core.bitwise_not(frame,frame );
// Mat frame = new Mat(image.rows(), image.cols(), image.type());
// frame.convertTo(frame, -1, 10d * 20 / 100, 0);
Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// if (this.inverse.isSelected())
// thresh_type = Imgproc.THRESH_BINARY;
// threshold the image with the average hue value
// System.out.println("size " +frame.size());
hsvImg.create(frame.size(), CvType.CV_8U);
// Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
// double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
// System.out.println(threshValue);
/*
if(threshValue > 40){
maxValue = 160;
}else{
maxValue = 40;
}*/
// Imgproc.threshold(hsvPlanes.get(1), thresholdImg, minValue , maxValue , thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(27, 27));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.threshold(thresholdImg, thresholdImg, minValue, maxValue, Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
Core.bitwise_not(thresholdImg, foreground);
frame.copyTo(foreground, thresholdImg);
///////////////////////////////////////////////////////////////////////////////////////
///
////
return foreground;
/*Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// threshold the image with the average hue value
hsvImg.create(inputImg.size(), CvType.CV_8U);
Imgproc.cvtColor(inputImg, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
Imgproc.threshold(hsvPlanes.get(0), thresholdImg, minValue,
maxValue, thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(3, 3));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 3);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.threshold(thresholdImg, thresholdImg, minValue,
maxValue, Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(inputImg.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
inputImg.copyTo(foreground, thresholdImg);
Core.bitwise_not(foreground,foreground);
return foreground;*/
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
// convert to Gray scale
Imgproc.cvtColor(mRgba, img_gray, Imgproc.COLOR_BGR2GRAY);
// make it binary with threshold=100
Imgproc.threshold(img_gray, erd, 100, 255, Imgproc.THRESH_OTSU);
// remove pixel noise by "erode" with structuring element of 9X9
Mat erode = Imgproc.getStructuringElement(Imgproc.MORPH_ERODE, new Size(9, 9));
Imgproc.erode(erd, tgt, erode);
// apply "dilation" to enlarge object
Mat dilate = Imgproc.getStructuringElement(Imgproc.MORPH_DILATE, new Size(9, 9));
Imgproc.dilate(tgt, erd, dilate);
// take a window
Size s = erd.size();
int W = (int) s.width;
int H = (int) s.height;
Rect r = new Rect(0, H / 2 - 100, W, 200);
Mat mask = new Mat(s, CvType.CV_8UC1, new Scalar(0, 0, 0));
rectangle(mask, r.tl(), r.br(), new Scalar(255, 255, 255), -1);
erd.copyTo(window, mask);
// find the contours
Imgproc.findContours(window, contours, dest, 0, 2);
// find largest contour
int maxContour = -1;
double area = 0;
for (int i = 0; i < contours.size(); i++) {
double contArea = Imgproc.contourArea(contours.get(i));
if (contArea > area) {
area = contArea;
maxContour = i;
}
}
// form bounding rectangle for largest contour
Rect rect = null;
if (maxContour > -1) rect = Imgproc.boundingRect(contours.get(maxContour));
// position to center
while (!train) {
if (rect != null) {
Imgproc.rectangle(mRgba, rect.tl(), rect.br(), new Scalar(255, 255, 255), 5);
if ((rect.x + rect.width / 2) > W / 2 - 20 && (rect.x + rect.width / 2) < W / 2 + 20) {
runOnUiThread(
new Runnable() {
@Override
public void run() {
Toast.makeText(getApplicationContext(), "OK", Toast.LENGTH_SHORT).show();
}
});
train = true;
}
}
if (contours != null) contours.clear();
return mRgba;
}
if (train) {
if (rect != null) {
Imgproc.rectangle(mRgba, rect.tl(), rect.br(), new Scalar(255, 255, 255), 5);
// direction of movement
int thr = 100;
if ((rect.x + rect.width / 2) < (W / 2 - thr)) {
// move to the RIGHT
uHandler.obtainMessage(MainActivity.LEFT).sendToTarget();
} else {
if ((rect.x + rect.width / 2) > (W / 2 + thr)) {
uHandler.obtainMessage(MainActivity.RIGHT).sendToTarget();
} else {
uHandler.obtainMessage(MainActivity.FORWARD).sendToTarget();
}
}
} else {
// stop moving
uHandler.obtainMessage(MainActivity.STOP).sendToTarget();
}
}
if (contours != null) contours.clear();
return mRgba;
}
public void run() {
ArrayList<Geometry.Quad> squares;
Mat image = new Mat();
Utils.bitmapToMat(source, image);
Mat bwimage = new Mat();
cvtColor(image, bwimage, COLOR_RGB2GRAY);
Mat blurred = new Mat();
medianBlur(image, blurred, 9);
int width = blurred.width();
int height = blurred.height();
int depth = blurred.depth();
Mat gray0 = new Mat(width, height, depth);
blurred.copyTo(gray0);
squares = new ArrayList<Geometry.Quad>();
// find squares in every color plane of the image
for (int c = 0; c < 3; c++) {
Core.mixChannels(
Arrays.asList(blurred), Arrays.asList(new Mat[] {gray0}), new MatOfInt(c, 0));
// try several threshold levels
int thresholdLevel = 8;
for (int l = 0; l < thresholdLevel; l++) {
// use canny instead of 0 threshold level
// canny helps catch squares with gradient shading
Mat gray = new Mat();
if (l == 0) {
Canny(gray0, gray, 10.0, 20.0, 3, false);
Mat kernel = new Mat(11, 11, CvType.CV_8UC1, new Scalar(1));
dilate(gray, gray, kernel);
} else {
Mat thresh = new Mat(gray0.rows(), gray0.cols(), gray0.type());
threshold(gray0, thresh, ((double) l) / thresholdLevel * 255, 128, THRESH_BINARY_INV);
cvtColor(thresh, gray, COLOR_BGR2GRAY);
}
// find contours and store them in a list
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
findContours(gray, contours, new Mat(), RETR_LIST, CHAIN_APPROX_SIMPLE);
// test contours
for (MatOfPoint contour : contours) {
// approximate contour with accuracy proportional to the contour perimeter
MatOfPoint2f thisContour = new MatOfPoint2f(contour.toArray());
double arclength = 0.02 * arcLength(thisContour, true);
MatOfPoint2f approx = new MatOfPoint2f();
approxPolyDP(thisContour, approx, arclength, true);
double area = contourArea(approx);
boolean isConvex = isContourConvex(new MatOfPoint(approx.toArray()));
if (approx.rows() == 4 && Math.abs(area) > SQUARE_SIZE && isConvex) {
double maxCosine = 0;
Point[] approxArray = approx.toArray();
for (int j = 2; j < 5; j++) {
double cosine =
Math.abs(angle(approxArray[j % 4], approxArray[j - 2], approxArray[j - 1]));
maxCosine = Math.max(maxCosine, cosine);
}
if (maxCosine > THRESHOLD_COS) {
squares.add(new Geometry.Quad(approxArray));
Log.d(TAG, "area = " + area);
}
}
}
}
}
result = new Bundle();
result.putParcelableArrayList("squares", squares);
Log.d(TAG, "result created");
finish();
}
public void processImage(Mat imageToProcess) {
try {
final Mat processedImage = imageToProcess.clone();
// red
final Mat redUpper = new Mat();
final Mat redLower = new Mat();
Core.inRange(processedImage, new Scalar(170, 100, 20), new Scalar(180, 255, 255), redUpper);
Core.inRange(processedImage, new Scalar(0, 100, 20), new Scalar(20, 255, 255), redLower);
Core.bitwise_or(redLower, redUpper, processedImage);
// refining the binary image
Imgproc.erode(processedImage, processedImage, new Mat(), new Point(-1, -1), 1);
Imgproc.dilate(processedImage, processedImage, new Mat(), new Point(-1, -1), 0);
// create a clone for the processedImage to be used in finding contours
final Mat clone = processedImage.clone();
Imgproc.cvtColor(processedImage, processedImage, Imgproc.COLOR_GRAY2RGB);
// finds list of contours and draw the biggest on the processedImage
final Scalar color1 = new Scalar(0, 0, 255);
final Scalar color2 = new Scalar(255, 255, 0);
final Scalar color3 = new Scalar(255, 255, 255);
final List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(
clone, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_NONE);
final List<MatOfPoint> contour = new ArrayList<MatOfPoint>(1);
double maxArea = 0.0;
for (int index = 0; index < contours.size(); index++) {
double area = Imgproc.contourArea(contours.get(index));
if (area > maxArea && area > 25 && Imgproc.boundingRect(contours.get(index)).y > 40) {
maxArea = area;
contour.add(0, contours.get(index));
}
}
// finds bounding Rectangle and draws contours
Rect boundingRect = new Rect();
if (contour.size() > 0) {
Imgproc.drawContours(processedImage, contour, -2, color1);
boundingRect = Imgproc.boundingRect(contour.get(0));
final double x = boundingRect.x;
final double y = boundingRect.y;
final double width = boundingRect.width;
final double height = boundingRect.height;
Core.rectangle(processedImage, new Point(x, y), new Point(x + width, y + height), color3);
}
// finding bounding Circle and draws it
final Point center = new Point();
final float[] radius = new float[1];
if (contour.size() > 0) {
final MatOfPoint2f contour2f = new MatOfPoint2f(contour.get(0).toArray());
Imgproc.minEnclosingCircle(contour2f, center, radius);
Core.circle(processedImage, center, (int) radius[0], color2);
}
final BallStruct redBallStruct = new BallStruct(boundingRect, center, (double) radius[0]);
final BallTargeting ballTargeting = new BallTargeting(redBallStruct);
synchronized (this) {
distanceToRed = ballTargeting.getDistance();
angleToRedInDegrees = ballTargeting.getAngle() * (180 / Math.PI);
this.processedImage = processedImage;
}
} catch (Exception e) {
}
}
public void process(Mat rgbaImage) {
Mat pyrDownMat = new Mat();
Imgproc.pyrDown(rgbaImage, pyrDownMat);
Imgproc.pyrDown(pyrDownMat, pyrDownMat);
Mat hsvMat = new Mat();
Imgproc.cvtColor(pyrDownMat, hsvMat, Imgproc.COLOR_RGB2HSV_FULL);
Mat Mask = new Mat();
Core.inRange(hsvMat, mLowerBound, mUpperBound, Mask);
Mat dilatedMask = new Mat();
Imgproc.dilate(Mask, dilatedMask, new Mat());
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
Imgproc.findContours(
dilatedMask, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
blobCenters[0] = new Point();
blobCenters[1] = new Point();
if (contours.size() > 0) {
// Find max contour area of the two biggest
double[] maxArea = new double[2];
maxArea[0] = 0; // biggest
maxArea[1] = 0; // 2nd biggest
Iterator<MatOfPoint> each = contours.iterator();
int[] contourIndex = new int[2];
contourIndex[0] = 0;
contourIndex[1] = 0;
int index = 0;
while (each.hasNext()) {
MatOfPoint wrapper = each.next();
double area = Imgproc.contourArea(wrapper);
if (area > maxArea[0]) { // area bigger than the maximum found
maxArea[1] = maxArea[0];
contourIndex[1] = contourIndex[0];
maxArea[0] = area;
contourIndex[0] = index;
} else if (area > maxArea[1]) { // area bigger than the second maximum found
maxArea[1] = area;
contourIndex[1] = index;
}
index++;
}
// // another possibility to iterate through contours
// for (index = 0; index < contours.size(); index++) {
// d = Imgproc.contourArea (contours.get(index));
Log.d("index0", Integer.toString(contourIndex[0]));
Log.d("index1", Integer.toString(contourIndex[1]));
MatOfPoint2f mMOP2f1 = new MatOfPoint2f();
float[] radius = new float[contours.size()];
// contours is a List<MatOfPoint>
// so contours.get(x) is a single MatOfPoint
// but to use approxPolyDP we need to pass a MatOfPoint2f
// so we need to do a conversion
contours.get(contourIndex[0]).convertTo(mMOP2f1, CvType.CV_32FC2);
// get the center of the bigger contour found
Point tempCenter = new Point();
Imgproc.minEnclosingCircle(mMOP2f1, tempCenter, radius);
blobCenters[0].x = tempCenter.x;
blobCenters[0].y = tempCenter.y;
blobRadius[0] = radius[0];
Log.d("center0.x", Double.toString(blobCenters[0].x));
Log.d("center0.y", Double.toString(blobCenters[0].y));
Log.d("radius0", Double.toString(blobRadius[0]));
contours.get(contourIndex[1]).convertTo(mMOP2f1, CvType.CV_32FC2);
Imgproc.minEnclosingCircle(mMOP2f1, tempCenter, radius);
blobCenters[1].x = tempCenter.x;
blobCenters[1].y = tempCenter.y;
blobRadius[1] = radius[0];
Log.d("center1.x", Double.toString(blobCenters[1].x));
Log.d("center1.y", Double.toString(blobCenters[1].y));
Log.d("radius1", Double.toString(blobRadius[1]));
// Filter contours by area and resize to fit the original image size
mContours.clear();
each = contours.iterator();
while (each.hasNext()) {
MatOfPoint contour = each.next();
if (Imgproc.contourArea(contour) > mMinContourArea * maxArea[1]) {
Core.multiply(contour, new Scalar(4, 4), contour);
mContours.add(contour);
}
}
} else {
blobCenters[0].x = 0;
blobCenters[0].y = 0;
blobCenters[1].x = 0;
blobCenters[1].y = 0;
}
}