List of usage examples for org.opencv.core MatOfPoint2f fromArray
public void fromArray(Point... a)
From source file:OctoEye.java
License:Open Source License
private void detectPupil() { // min and max pupil radius int r_min = 2; int r_max = 45; // min and max pupil diameter int d_min = 2 * r_min; int d_max = 2 * r_max; // min and max pupil area double area;/*from ww w. j av a 2 s. com*/ double a_min = Math.PI * r_min * r_min; double a_max = Math.PI * r_max * r_max; // histogram stuff List<Mat> images; MatOfInt channels; Mat mask; Mat hist; MatOfInt mHistSize; MatOfFloat mRanges; // contour and circle stuff Rect rect = null; Rect rectMin; Rect rectMax; List<MatOfPoint> contours; MatOfPoint3 circles; // pupil center Point p; // ellipse test points Point v; Point r; Point s; // rect points Point tl; Point br; // pupil edge detection Vector<Point> pointsTest; Vector<Point> pointsEllipse; Vector<Point> pointsRemoved; // temporary variables double distance; double rad; double length; int x; int y; int tmp; byte buff[]; // ------------------------------------------------------------------------------------------------------------- // step 1 // blur the image to reduce noise Imgproc.medianBlur(src, tmp1, 25); // ------------------------------------------------------------------------------------------------------------- // step 2 // locate the pupil with feature detection and compute a histogram for each, // the best feature will be used as rough pupil location (rectMin) int score = 0; int winner = 0; // feature detection MatOfKeyPoint matOfKeyPoints = new MatOfKeyPoint(); FeatureDetector blobDetector = FeatureDetector.create(FeatureDetector.MSER); // Maximal Stable Extremal Regions blobDetector.detect(tmp1, matOfKeyPoints); List<KeyPoint> keyPoints = matOfKeyPoints.toList(); // histogram calculation for (int i = 0; i < keyPoints.size(); i++) { x = (int) keyPoints.get(i).pt.x; y = (int) keyPoints.get(i).pt.y; tl = new Point(x - 5 >= 0 ? x - 5 : 0, y - 5 >= 0 ? y - 5 : 0); br = new Point(x + 5 < WIDTH ? x + 5 : WIDTH - 1, y + 5 < HEIGHT ? y + 5 : HEIGHT - 1); images = new ArrayList<Mat>(); images.add(tmp1.submat(new Rect(tl, br))); channels = new MatOfInt(0); mask = new Mat(); hist = new Mat(); mHistSize = new MatOfInt(256); mRanges = new MatOfFloat(0f, 256f); Imgproc.calcHist(images, channels, mask, hist, mHistSize, mRanges); tmp = 0; for (int j = 0; j < 256 / 3; j++) { tmp += (256 / 3 - j) * (int) hist.get(j, 0)[0]; } if (tmp >= score) { score = tmp; winner = i; rect = new Rect(tl, br); } if (debug) { // show features (orange) Core.circle(dbg, new Point(x, y), 3, ORANGE); } } if (rect == null) { return; } rectMin = rect.clone(); if (debug) { // show rectMin (red) Core.rectangle(dbg, rectMin.tl(), rect.br(), RED, 1); } // ------------------------------------------------------------------------------------------------------------- // step 3 // compute a rectMax (blue) which is larger than the pupil int margin = 32; rect.x = rect.x - margin; rect.y = rect.y - margin; rect.width = rect.width + 2 * margin; rect.height = rect.height + 2 * margin; rectMax = rect.clone(); if (debug) { // show features (orange) Core.rectangle(dbg, rectMax.tl(), rectMax.br(), BLUE); } // ------------------------------------------------------------------------------------------------------------- // step 4 // blur the image again Imgproc.medianBlur(src, tmp1, 7); Imgproc.medianBlur(tmp1, tmp1, 3); Imgproc.medianBlur(tmp1, tmp1, 3); Imgproc.medianBlur(tmp1, tmp1, 3); // ------------------------------------------------------------------------------------------------------------- // step 5 // detect edges Imgproc.Canny(tmp1, tmp2, 40, 50); // ------------------------------------------------------------------------------------------------------------- // step 6 // from pupil center to maxRect borders, find all edge points, compute a first ellipse p = new Point(rectMin.x + rectMin.width / 2, rectMin.y + rectMin.height / 2); pointsTest = new Vector<Point>(); pointsEllipse = new Vector<Point>(); pointsRemoved = new Vector<Point>(); buff = new byte[tmp2.rows() * tmp2.cols()]; tmp2.get(0, 0, buff); length = Math.min(p.x - rectMax.x - 3, p.y - rectMax.y - 3); length = Math.sqrt(2 * Math.pow(length, 2)); Point z = new Point(p.x, p.y - length); for (int i = 0; i < 360; i += 15) { rad = Math.toRadians(i); x = (int) (p.x + Math.cos(rad) * (z.x - p.x) - Math.sin(rad) * (z.y - p.y)); y = (int) (p.y + Math.sin(rad) * (z.x - p.x) - Math.cos(rad) * (z.y - p.y)); pointsTest.add(new Point(x, y)); } if (debug) { for (int i = 0; i < pointsTest.size(); i++) { Core.line(dbg, p, pointsTest.get(i), GRAY, 1); Core.rectangle(dbg, rectMin.tl(), rectMin.br(), GREEN, 1); Core.rectangle(dbg, rectMax.tl(), rectMax.br(), BLUE, 1); } Core.rectangle(dbg, rectMin.tl(), rectMin.br(), BLACK, -1); Core.rectangle(dbg, rectMin.tl(), rectMin.br(), RED, 1); Core.rectangle(dbg, rectMax.tl(), rectMax.br(), BLUE); } // p: Ursprung ("Mittelpunkt" der Ellipse) // v: Zielpunkt (Testpunkt) // r: Richtungsvektor PV for (int i = 0; i < pointsTest.size(); i++) { v = new Point(pointsTest.get(i).x, pointsTest.get(i).y); r = new Point(v.x - p.x, v.y - p.y); length = Math.sqrt(Math.pow(p.x - v.x, 2) + Math.pow(p.y - v.y, 2)); boolean found = false; for (int j = 0; j < Math.round(length); j++) { s = new Point(Math.rint(p.x + (double) j / length * r.x), Math.rint(p.y + (double) j / length * r.y)); s.x = Math.max(1, Math.min(s.x, WIDTH - 2)); s.y = Math.max(1, Math.min(s.y, HEIGHT - 2)); tl = new Point(s.x - 1, s.y - 1); br = new Point(s.x + 1, s.y + 1); buff = new byte[3 * 3]; rect = new Rect(tl, br); try { (tmp2.submat(rect)).get(0, 0, buff); for (int k = 0; k < 3 * 3; k++) { if (Math.abs(buff[k]) == 1) { pointsEllipse.add(s); found = true; break; } } } catch (Exception e) { break; } if (found) { break; } } } double e_min = Double.POSITIVE_INFINITY; double e_max = 0; double e_med = 0; for (int i = 0; i < pointsEllipse.size(); i++) { v = pointsEllipse.get(i); length = Math.sqrt(Math.pow(p.x - v.x, 2) + Math.pow(p.y - v.y, 2)); e_min = (length < e_min) ? length : e_min; e_max = (length > e_max) ? length : e_max; e_med = e_med + length; } e_med = e_med / pointsEllipse.size(); if (pointsEllipse.size() >= 5) { Point[] points1 = new Point[pointsEllipse.size()]; for (int i = 0; i < pointsEllipse.size(); i++) { points1[i] = pointsEllipse.get(i); } MatOfPoint2f points2 = new MatOfPoint2f(); points2.fromArray(points1); pupil = Imgproc.fitEllipse(points2); } if (pupil.center.x == 0 && pupil.center.y == 0) { // something went wrong, return null reset(); return; } if (debug) { Core.ellipse(dbg, pupil, PURPLE, 2); } // ------------------------------------------------------------------------------------------------------------- // step 7 // remove some outlier points and compute the ellipse again try { for (int i = 1; i <= 4; i++) { distance = 0; int remove = 0; for (int j = pointsEllipse.size() - 1; j >= 0; j--) { v = pointsEllipse.get(j); length = Math.sqrt(Math.pow(v.x - pupil.center.x, 2) + Math.pow(v.y - pupil.center.y, 2)); if (length > distance) { distance = length; remove = j; } } v = pointsEllipse.get(remove); pointsEllipse.removeElementAt(remove); pointsRemoved.add(v); } } catch (Exception e) { // something went wrong, return null reset(); return; } if (pointsEllipse.size() >= 5) { Point[] points1 = new Point[pointsEllipse.size()]; for (int i = 0; i < pointsEllipse.size(); i++) { points1[i] = pointsEllipse.get(i); } MatOfPoint2f points2 = new MatOfPoint2f(); points2.fromArray(points1); pupil = Imgproc.fitEllipse(points2); Point[] vertices = new Point[4]; pupil.points(vertices); double d1 = Math .sqrt(Math.pow(vertices[1].x - vertices[0].x, 2) + Math.pow(vertices[1].y - vertices[0].y, 2)); double d2 = Math .sqrt(Math.pow(vertices[2].x - vertices[1].x, 2) + Math.pow(vertices[2].y - vertices[1].y, 2)); if (d1 >= d2) { pupilMajorAxis = (int) (d1 / 2); pupilMinorAxis = (int) (d2 / 2); axisA = new Point(vertices[1].x + (vertices[2].x - vertices[1].x) / 2, vertices[1].y + (vertices[2].y - vertices[1].y) / 2); axisB = new Point(vertices[0].x + (vertices[1].x - vertices[0].x) / 2, vertices[0].y + (vertices[1].y - vertices[0].y) / 2); } else { pupilMajorAxis = (int) (d2 / 2); pupilMinorAxis = (int) (d1 / 2); axisB = new Point(vertices[1].x + (vertices[2].x - vertices[1].x) / 2, vertices[1].y + (vertices[2].y - vertices[1].y) / 2); axisA = new Point(vertices[0].x + (vertices[1].x - vertices[0].x) / 2, vertices[0].y + (vertices[1].y - vertices[0].y) / 2); } } double ratio = (double) pupilMinorAxis / (double) pupilMajorAxis; if (ratio < 0.75 || 2 * pupilMinorAxis <= d_min || 2 * pupilMajorAxis >= d_max) { // something went wrong, return null reset(); return; } // pupil found if (debug) { Core.ellipse(dbg, pupil, GREEN, 2); Core.line(dbg, pupil.center, axisA, RED, 2); Core.line(dbg, pupil.center, axisB, BLUE, 2); Core.circle(dbg, pupil.center, 1, GREEN, 0); x = 5; y = 5; Core.rectangle(dbg, new Point(x, y), new Point(x + 80 + 4, y + 10), BLACK, -1); Core.rectangle(dbg, new Point(x + 2, y + 2), new Point(x + 2 + pupilMajorAxis, y + 4), RED, -1); Core.rectangle(dbg, new Point(x + 2, y + 6), new Point(x + 2 + pupilMinorAxis, y + 8), BLUE, -1); for (int i = pointsEllipse.size() - 1; i >= 0; i--) { Core.circle(dbg, pointsEllipse.get(i), 2, ORANGE, -1); } for (int i = pointsRemoved.size() - 1; i >= 0; i--) { Core.circle(dbg, pointsRemoved.get(i), 2, PURPLE, -1); } } Core.ellipse(dst, pupil, GREEN, 2); Core.circle(dst, pupil.center, 1, GREEN, 0); }
From source file:com.github.mbillingr.correlationcheck.ImageProcessor.java
License:Open Source License
public List<Point> extractPoints() { Mat gray = new Mat();//work_width, work_height, CvType.CV_8UC1); Mat binary = new Mat(); Mat kernel = Mat.ones(3, 3, CvType.CV_8UC1); debugreset();/*w w w .ja v a2 s. c om*/ Mat image = load_transformed(); working_image = image.clone(); debugsave(image, "source"); Imgproc.cvtColor(image, gray, Imgproc.COLOR_RGB2GRAY); debugsave(gray, "grayscale"); Imgproc.GaussianBlur(gray, gray, new Size(15, 15), 0); debugsave(gray, "blurred"); //Imgproc.equalizeHist(gray, gray); //debugsave(gray, "equalized"); Imgproc.adaptiveThreshold(gray, binary, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY_INV, 129, 5); //Imgproc.threshold(gray, binary, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU); //Imgproc.threshold(gray, binary, 128, 255, Imgproc.THRESH_BINARY_INV); debugsave(binary, "binary"); Imgproc.morphologyEx(binary, binary, Imgproc.MORPH_CLOSE, kernel); debugsave(binary, "closed"); Imgproc.morphologyEx(binary, binary, Imgproc.MORPH_OPEN, kernel); debugsave(binary, "opened"); List<MatOfPoint> contours = new ArrayList<>(); Mat hierarchy = new Mat(); Imgproc.findContours(binary, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE); // is binary is now changed Imgproc.drawContours(image, contours, -1, new Scalar(0, 0, 255), 3); debugsave(image, "contours"); List<PointAndArea> points = new ArrayList<>(); for (MatOfPoint cnt : contours) { MatOfPoint2f c2f = new MatOfPoint2f(); c2f.fromArray(cnt.toArray()); RotatedRect rr = Imgproc.minAreaRect(c2f); double area = Imgproc.contourArea(cnt); if (rr.size.width / rr.size.height < 3 && rr.size.height / rr.size.width < 3 && rr.size.width < 64 && rr.size.height < 64 && area > 9 && area < 10000) { points.add(new PointAndArea((int) area, rr.center)); } } List<Point> final_points = new ArrayList<>(); Collections.sort(points); Collections.reverse(points); int prev = -1; for (PointAndArea p : points) { Log.i("area", Integer.toString(p.area)); if (prev == -1 || p.area >= prev / 2) { prev = p.area; Imgproc.circle(image, p.point, 10, new Scalar(0, 255, 0), 5); final_points.add(new Point(1 - p.point.y / work_height, 1 - p.point.x / work_width)); } } debugsave(image, "circles"); return final_points; }
From source file:com.jonwohl.Attention.java
License:Open Source License
private Mat getPerspectiveTransformation(ArrayList<PVector> inputPoints, int w, int h) { Point[] canonicalPoints = new Point[4]; canonicalPoints[0] = new Point(0, 0); canonicalPoints[1] = new Point(w, 0); canonicalPoints[2] = new Point(w, h); canonicalPoints[3] = new Point(0, h); MatOfPoint2f canonicalMarker = new MatOfPoint2f(); canonicalMarker.fromArray(canonicalPoints); Point[] points = new Point[4]; for (int i = 0; i < 4; i++) { points[i] = new Point(inputPoints.get(i).x, inputPoints.get(i).y); }/*from w ww . j a v a 2 s.c o m*/ MatOfPoint2f marker = new MatOfPoint2f(points); return Imgproc.getPerspectiveTransform(marker, canonicalMarker); }