/**
* 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;
}
public static Mat getCCH(Mat image) {
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
Imgproc.findContours(
image, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);
Mat chainHistogram = Mat.zeros(1, 8, CvType.CV_32F);
int n = 0;
MatOfPoint2f approxCurve = new MatOfPoint2f();
for (MatOfPoint contour : contours) {
// get the freeman chain code from the contours
int rows = contour.rows();
// System.out.println("\nrows"+rows+"\n"+contour.dump());
int direction = 7;
Mat prevPoint = contours.get(0).row(0);
n += rows - 1;
for (int i = 1; i < rows; i++) {
// get the current point
double x1 = contour.get(i - 1, 0)[1];
double y1 = contour.get(i - 1, 0)[0];
// get the second point
double x2 = contour.get(i, 0)[1];
double y2 = contour.get(i, 0)[0];
if (x2 == x1 && y2 == y1 + 1) direction = 0;
else if (x2 == x1 - 1 && y2 == y1 + 1) direction = 1;
else if (x2 == x1 - 1 && y2 == y1) direction = 2;
else if (x2 == x1 - 1 && y2 == y1 - 1) direction = 3;
else if (x2 == x1 && y2 == y1 - 1) direction = 4;
else if (x2 == x1 + 1 && y2 == y1 - 1) direction = 5;
else if (x2 == x1 + 1 && y2 == y1) direction = 6;
else if (x2 == x1 + 1 && y2 == y1 + 1) direction = 7;
else System.out.print("err");
double counter = chainHistogram.get(0, direction)[0];
chainHistogram.put(0, direction, ++counter);
System.out.print(direction);
}
}
System.out.println("\n" + chainHistogram.dump());
Scalar alpha = new Scalar(n); // the factor
Core.divide(chainHistogram, alpha, chainHistogram);
System.out.println("\nrows=" + n + " " + chainHistogram.dump());
return chainHistogram;
}
/**
* Creates Resistor objects for all resistors extracted from given contours. Optionally, also
* displays a bounding rectangle for all contours in the top left frame of the GUI.
*
* @param contours The contours defining the resistors
* @param image The image from which the contours were extracted
* @param showBoundingRect If true draws a bounding rectange for each contour
* @return A list of Resistor objects
*/
private List<Resistor> extractResistorsFromContours(
List<MatOfPoint> contours, Mat image, boolean showBoundingRect) {
List<Mat> extractedResistors = new ArrayList<Mat>();
List<Rect> boundingRect = new ArrayList<Rect>();
List<Resistor> resistors = new ArrayList<Resistor>();
for (int i = 0; i < contours.size(); i++) {
// bounding rectangle
boundingRect.add(Imgproc.boundingRect(contours.get(i)));
Mat mask = Mat.zeros(image.size(), CvType.CV_8U);
Imgproc.drawContours(mask, contours, i, new Scalar(255), Core.FILLED);
Mat contourRegion;
Mat imageROI = new Mat();
image.copyTo(imageROI, mask);
contourRegion = new Mat(imageROI, boundingRect.get(i));
extractedResistors.add(contourRegion);
// the center of the resistor as a point within the original captured image
Point resistorCenterPoint = findCenter(contours.get(i));
// create a new resistor entry
Resistor r = new Resistor(resistorCenterPoint, contourRegion);
resistors.add(r);
}
if (showBoundingRect) {
Mat drawing = new Mat();
image.copyTo(drawing);
for (int i = 0; i < contours.size(); i++) {
Core.rectangle(
drawing, boundingRect.get(i).tl(), boundingRect.get(i).br(), new Scalar(0, 0, 255), 2);
}
paintTL(drawing);
}
return resistors;
}
/**
* @param inputImg
* @return Mat
*/
public static Mat kmeans(Mat inputImg) {
Mat rgba = inputImg;
Mat tempMat = inputImg;
rgba = new Mat(inputImg.cols(), inputImg.rows(), CvType.CV_8UC3);
inputImg.copyTo(rgba);
List<Mat> hsv_planes_temp = new ArrayList<Mat>(3);
Core.split(tempMat, hsv_planes_temp);
double threshValue1 = PreProcessingOperation.getHistAverage(inputImg, hsv_planes_temp.get(0));
sample.util.Estimate.setFirstHistAverageValue(threshValue1);
System.out.println("Defore eqau " + threshValue1);
System.out.println(
Estimate.getBlueAverage() + " ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;");
if (threshValue1 > 140) {
if (Estimate.getBlueAverage() > 110) {
rgba.convertTo(rgba, -1, 10d * 31 / 100, 0);
System.out.println("11");
} else {
rgba.convertTo(rgba, -1, 10d * 40 / 100, 0);
System.out.println("12");
}
} else if (threshValue1 > 135) {
rgba.convertTo(rgba, -1, 10d * 32 / 100, 0);
System.out.println("21");
} else if (threshValue1 > 125) {
if (Estimate.getBlueAverage() > 110) {
rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 5);
System.out.println("31");
} else {
rgba.convertTo(rgba, -1, 10d * 37 / 100, 0);
System.out.println("32");
}
} else if (threshValue1 > 120) {
rgba.convertTo(rgba, -1, 10d * 35 / 100, 0);
System.out.println("41");
} else if (threshValue1 > 110) {
if (Estimate.getBlueAverage() > 110) {
rgba.convertTo(rgba, -1, 10d * 35 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 5);
System.out.println("51");
}
} else if (threshValue1 > 100) {
if (Estimate.getBlueAverage() > 107) {
rgba.convertTo(rgba, -1, 10d * 24 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 5);
System.out.println("61");
} else if (Estimate.getBlueAverage() > 90) {
rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 5);
System.out.println("62");
}
} else if (threshValue1 > 50) {
if (Estimate.getBlueAverage() > 160) {
rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 3);
System.out.println("81");
} else if (Estimate.getBlueAverage() > 160) {
rgba.convertTo(rgba, -1, 10d * 27 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 9);
System.out.println("82");
} else if (Estimate.getBlueAverage() > 130) {
rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 9);
System.out.println("83");
} else if (Estimate.getBlueAverage() > 70) {
rgba.convertTo(rgba, -1, 10d * 29 / 100, 0);
rgba = PreProcessing.Dilate(rgba, 9);
System.out.println("84");
}
} else if (threshValue1 > 30) {
if (Estimate.getBlueAverage() > 190) {
rgba.convertTo(rgba, -1, 10d * 25 / 100, 0);
System.out.println("91");
} else if (Estimate.getBlueAverage() > 160) {
rgba.convertTo(rgba, -1, 10d * 35 / 100, 0);
System.out.println("92");
}
} else {
if (Estimate.getBlueAverage() > 240) {
rgba.convertTo(rgba, -1, 10d * 24 / 100, 0);
System.out.println("7");
} else {
rgba.convertTo(rgba, -1, 10d * 17 / 100, 0);
System.out.println("7");
}
}
tempMat.release();
Mat mHSV = new Mat();
Imgproc.cvtColor(rgba, mHSV, Imgproc.COLOR_RGBA2RGB, 3);
Imgproc.cvtColor(rgba, mHSV, Imgproc.COLOR_RGB2HSV, 3);
List<Mat> hsv_planes = new ArrayList<Mat>(3);
Core.split(mHSV, hsv_planes);
Mat channel = hsv_planes.get(0);
channel = Mat.zeros(mHSV.rows(), mHSV.cols(), CvType.CV_8UC1);
hsv_planes.set(2, channel);
Core.merge(hsv_planes, mHSV);
mHSV.convertTo(mHSV, CvType.CV_8UC1);
mHSV = Histogram(mHSV);
/*
Mat clusteredHSV = new Mat();
mHSV.convertTo(mHSV, CvType.CV_32FC3);
TermCriteria criteria = new TermCriteria(TermCriteria.EPS + TermCriteria.MAX_ITER,100,0.1);
Core.kmeans(mHSV, 1, clusteredHSV, criteria, 20, Core.KMEANS_PP_CENTERS);
Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
hsvImg.create(mHSV.size(), CvType.CV_8U);
Imgproc.cvtColor(mHSV, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
Imgproc.threshold(hsvPlanes.get(1), thresholdImg, 0 , 200 , thresh_type);
double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
Estimate.setSecondHistAverageValue(threshValue);
System.out.println("After equa " + Estimate.getSecondHistAverageValue());*/
Imgproc.threshold(mHSV, mHSV, 0, 150, Imgproc.THRESH_BINARY_INV);
// mHSV.convertTo(mHSV, CvType.CV_8UC1);
return mHSV;
}
/**
* Extracts and classifies colour bands for each Resistor. Each ColourBand object is instantiated
* and linked to their parent Resistor object.
*
* @param resistorList A list of Resistor objects from which to extract the colour bands
* @param paintDebugInfo If ture, the extracted colour band ROIs are displayed on the GUI
*/
private void extractColourBandsAndClassify(List<Resistor> resistorList, boolean paintDebugInfo) {
if (resistorList.size() > 0) {
for (int r = 0; r < resistorList.size(); r++) {
Mat resImg = resistorList.get(r).resistorMat;
Mat imgHSV = new Mat();
Mat satImg = new Mat();
Mat hueImg = new Mat();
// convert to HSV
Imgproc.cvtColor(resImg, imgHSV, Imgproc.COLOR_BGR2HSV);
ArrayList<Mat> channels = new ArrayList<Mat>();
Core.split(imgHSV, channels);
// extract channels
satImg = channels.get(1); // saturation
hueImg = channels.get(0); // hue
// threshold saturation channel
Mat threshedROISatBands = new Mat(); // ~130 sat thresh val
Imgproc.threshold(satImg, threshedROISatBands, SAT_BAND_THRESH, 255, Imgproc.THRESH_BINARY);
// threshold hue channel
Mat threshedROIHueBands = new Mat(); // ~50 hue thresh val
Imgproc.threshold(hueImg, threshedROIHueBands, HUE_BAND_THRESH, 255, Imgproc.THRESH_BINARY);
// combine the thresholded binary images
Mat bandROI = new Mat();
Core.bitwise_or(threshedROIHueBands, threshedROISatBands, bandROI);
// find contours in binary ROI image
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
Imgproc.findContours(
bandROI,
contours,
hierarchy,
Imgproc.RETR_EXTERNAL,
Imgproc.CHAIN_APPROX_SIMPLE,
new Point(0, 0));
// remove any remaining noise by only keeping contours which area > threshold
for (int i = 0; i < contours.size(); i++) {
double area = Imgproc.contourArea(contours.get(i));
if (area < MIN_BAND_AREA) {
contours.remove(i);
i--;
}
}
// create a ColourBand object for each detected band
// storing its center, the contour and the bandROI
for (int i = 0; i < contours.size(); i++) {
MatOfPoint contour = contours.get(i);
// extract this colour band and store in a Mat
Rect boundingRect = Imgproc.boundingRect(contour);
Mat mask = Mat.zeros(bandROI.size(), CvType.CV_8U);
Imgproc.drawContours(mask, contours, i, new Scalar(255), Core.FILLED);
Mat imageROI = new Mat();
resImg.copyTo(imageROI, mask);
Mat colourBandROI = new Mat(imageROI, boundingRect);
// instantiate new ColourBand object
ColourBand cb = new ColourBand(findCenter(contour), contour, colourBandROI);
// cluster the band colour
cb.clusterBandColour(BAND_COLOUR_K_MEANS);
// classify using the Lab colourspace as feature vector
Mat sampleMat =
new Mat(1, 3, CvType.CV_32FC1); // create a Mat contacting the clustered band colour
sampleMat.put(0, 0, cb.clusteredColourLAB[0]);
sampleMat.put(0, 1, cb.clusteredColourLAB[1]);
sampleMat.put(0, 2, cb.clusteredColourLAB[2]);
Mat classifiedValue = new Mat(1, 1, CvType.CV_32FC1);
Mat neighborResponses = new Mat(); // dont actually use this
Mat dists = new Mat(); // dont actually use this
// classify
knn.find_nearest(sampleMat, 3, classifiedValue, neighborResponses, dists);
// cast classified value into Colour enum and store
cb.classifiedColour = ColourEnumVals[(int) classifiedValue.get(0, 0)[0]];
// add the band to the parent resistor
resistorList.get(r).bands.add(cb);
}
// paint the extracted band ROIs
if (paintDebugInfo) {
Mat finalBandROIMask = Mat.zeros(bandROI.size(), CvType.CV_8U);
for (int i = 0; i < contours.size(); i++) {
Scalar color = new Scalar(255, 255, 255);
Imgproc.drawContours(
finalBandROIMask, contours, i, color, -1, 4, hierarchy, 0, new Point());
}
Mat colourROI = new Mat();
resImg.copyTo(colourROI, finalBandROIMask);
paintResistorSubRegion(colourROI, r);
}
}
}
}
/**
* Determines which pieces are kings
*
* @param in Mat image of board
*/
public void determineKings(Mat in) {
int playSquares = 32;
Mat dst = new Mat(in.rows(), in.cols(), in.type());
in.copyTo(dst);
Imgproc.cvtColor(dst, dst, Imgproc.COLOR_BGR2GRAY); // change to single color
Mat canny = new Mat();
Imgproc.Canny(dst, canny, 100, 200); // make image a canny image that is only edges; 2,4
// lower threshold values find more edges
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat(); // holds nested contour information
Imgproc.findContours(
canny,
contours,
hierarchy,
Imgproc.RETR_LIST,
Imgproc.CHAIN_APPROX_SIMPLE); // Imgproc.RETR_LIST, TREE
// draw contour image
Mat mask = new Mat();
mask = Mat.zeros(dst.size(), dst.type());
Imgproc.drawContours(
mask, contours, -1, new Scalar(255, 255, 255), 1, 8, hierarchy, 2, new Point());
Highgui.imwrite("contours.jpg", mask);
ArrayList occupied = new ArrayList<Integer>();
for (int i = 0; i < playSquares; i++) {
if (board[i] != 0) occupied.add(i);
}
for (int i = 0; i < contours.size(); i++) // assuming only contours are checker pieces
{
// determine if it should be a king
// use Rect r = Imgproc.boundingRect then find height of it by r.height
// Get bounding rect of contour
Rect bound = Imgproc.boundingRect(contours.get(i));
if (bound.height > in.rows() / 8) {
// board[(int) occupied.get(0)]++; // make it a king
// occupied.remove(0);
}
}
// or apply to each region of interest
/*
// keep track of starting row square
int parity = 0; // 0 is even, 1 is odd, tied to row number
int count = 0; // row square
int rowNum = 0; // row number, starting at 0
int vsegment = in.rows() / 8; // only accounts 8 playable
int hsegment = in.cols() / 12; // 8 playable, 2 capture, 2 extra
int offset = hsegment * 2; // offset for playable board
// For angle of camera
int dx = 48;
hsegment -= 8;
// Go through all playable squares
for (int i = 0; i < playSquares; i++)
{
// change offset depending on the row
if (parity == 0) // playable squares start on immediate left
offset = hsegment * 3 + dx;
else // playable squares start on 2nd square from left
offset = hsegment * 2 + dx;
// find where roi should be
Point p1 = new Point(offset + count * hsegment, rowNum * vsegment); // top left point of rectangle (x,y)
Point p2 = new Point(offset + (count + 1) * hsegment, (rowNum + 1) * vsegment); // bottom right point of rectangle (x,y)
// create rectangle that is board square
Rect bound = new Rect(p1, p2);
// frame only includes rectangle
Mat roi = new Mat(in, bound);
Imgproc.cvtColor(roi, roi, Imgproc.COLOR_BGR2GRAY); // change to single color
Mat canny = new Mat();
Imgproc.Canny(roi, canny, 2, 4); // make image a canny image that is only edges; 2,4
// lower threshold values find more edges
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat(); // holds nested contour information
Imgproc.findContours(canny, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Imgproc.RETR_LIST, TREE
// Get bounding rect of contour
Rect rect = Imgproc.boundingRect(contours.get(0));
if (rect.height > in.rows() / 8)
{
board[i]++; // make it a king
}
count += 2;
if (count == 8)
{
parity = ++parity % 2; // change odd or even
count = 0;
rowNum++;
hsegment += 1;
dx -= 6;
}
}*/
}
public Point findLaser(Mat inputFrame) {
Mat mHsv = new Mat();
Imgproc.cvtColor(inputFrame, mHsv, Imgproc.COLOR_RGB2HSV);
// Find laser center
Mat center = new Mat();
Core.inRange(mHsv, new Scalar(0, 0, 250), new Scalar(180, 16, 255), center);
Mat h = new Mat();
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(center, contours, h, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
center.release();
Mat center_mask = Mat.zeros(inputFrame.rows(), inputFrame.cols(), CvType.CV_8U);
if (contours.size() > 0) {
for (int i = 0; i < contours.size(); i++) {
int radius = 10;
// Point[] cont_pos = contours.get(i).toArray();
Moments m = Imgproc.moments(contours.get(i));
Point p = new Point();
p.x = m.get_m10() / m.get_m00();
p.y = m.get_m01() / m.get_m00();
Core.circle(center_mask, p, radius * 2, new Scalar(255), -1);
}
}
// Find halo
Mat ranged = new Mat();
Core.inRange(mHsv, new Scalar(100, 32, 225), new Scalar(150, 255, 255), ranged);
mHsv.release();
// Mat f_frame =ranged.clone();
// Find halo around bright dot
Core.bitwise_and(ranged, center_mask, ranged);
center_mask.release();
// Find biggest resulting contour
for (int i = 1; i < contours.size(); i++) {
contours.get(i).release();
}
contours.clear();
Imgproc.findContours(ranged, contours, h, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
h.release();
ranged.release();
if (contours.size() > 0) {
MatOfPoint biggest_cont = contours.get(0);
double cont_size = Imgproc.contourArea(biggest_cont);
for (int i = 1; i < contours.size(); i++) {
MatOfPoint cur = contours.get(i);
if (Imgproc.contourArea(cur) > cont_size) {
biggest_cont = cur;
cont_size = Imgproc.contourArea(cur);
}
}
Moments m = Imgproc.moments(biggest_cont);
Point p = new Point();
p.x = m.get_m10() / m.get_m00();
p.y = m.get_m01() / m.get_m00();
for (int i = 1; i < contours.size(); i++) {
contours.get(i).release();
}
biggest_cont.release();
return p;
} else {
return null;
}
}