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How to use getPointsBelowThreshold method of com.intuit.karate.robot.OpenCvUtils class

Best Karate code snippet using com.intuit.karate.robot.OpenCvUtils.getPointsBelowThreshold

Source:OpenCvUtils.java

...91        return resized;92    }93    private static final int TARGET_MINVAL_FACTOR = 150; // magic number, lower is stricter94    private static final int BLOCK_SIZE = 5;95    private static List<int[]> getPointsBelowThreshold(Mat src, double threshold) {96        Mat dst = new Mat();97        threshold(src, dst, threshold, 1, CV_THRESH_BINARY_INV);98        Mat non = new Mat();99        findNonZero(dst, non);100        int len = (int) non.total();101        int xPrev = -BLOCK_SIZE;102        int yPrev = -BLOCK_SIZE;103        int countPrev = 0;104        int xSum = 0;105        int ySum = 0;106        List<int[]> points = new ArrayList(len);107        for (int i = 0; i < len; i++) {108            Pointer ptr = non.ptr(i);109            Point p = new Point(ptr);110            int x = p.x();111            int y = p.y();112            int xDelta = Math.abs(x - xPrev);113            int yDelta = Math.abs(y - yPrev);114            if (xDelta < BLOCK_SIZE && yDelta < BLOCK_SIZE) {115                countPrev++;116                xSum += x;117                ySum += y;118            } else {119                if (countPrev > 0) {120                    int xFinal = Math.floorDiv(xSum, countPrev);121                    int yFinal = Math.floorDiv(ySum, countPrev);122                    // logger.debug("end: {}:{}", xFinal, yFinal);123                    points.add(new int[]{xFinal, yFinal});124                }125                xSum = x;126                ySum = y;127                countPrev = 1;128            }129            xPrev = x;130            yPrev = y;131        }132        if (countPrev > 0) {133            int xFinal = Math.floorDiv(xSum, countPrev);134            int yFinal = Math.floorDiv(ySum, countPrev);135            points.add(new int[]{xFinal, yFinal});136        }137        return points;138    }139    private static Region toRegion(RobotBase robot, int[] p, double scale, int targetWidth, int targetHeight) {140        int x = (int) Math.round(p[0] / scale);141        int y = (int) Math.round(p[1] / scale);142        int width = (int) Math.round(targetWidth / scale);143        int height = (int) Math.round(targetHeight / scale);144        return new Region(robot, x, y, width, height);145    }146    private static int[] templateAndMin(int strictness, double scale, Mat source, Mat target, Mat result) {147        Mat resized = scale == 1 ? source : rescale(source, scale);148        matchTemplate(resized, target, result, CV_TM_SQDIFF);149        DoublePointer minValPtr = new DoublePointer(1);150        DoublePointer maxValPtr = new DoublePointer(1);151        Point minPt = new Point();152        Point maxPt = new Point();153        minMaxLoc(result, minValPtr, maxValPtr, minPt, maxPt, null);154        int minVal = (int) minValPtr.get();155        int x = minPt.x();156        int y = minPt.y();157        return new int[]{x, y, minVal};158    }159    private static int collect(int strictness, List<Region> found, boolean findAll, RobotBase robot, Mat source, Mat target, double scale) {160        int targetWidth = target.cols();161        int targetHeight = target.rows();162        int targetMinVal = targetWidth * targetHeight * TARGET_MINVAL_FACTOR * strictness;  163        Mat result = new Mat();164        int[] minData = templateAndMin(strictness, scale, source, target, result);165        int minValue = minData[2];166        if (minValue > targetMinVal) {167            logger.debug("no match at scale {}, minVal: {} / {} at {}:{}", scale, minValue, targetMinVal, minData[0], minData[1]);168            if (robot != null && robot.debug) {169                Rect rect = new Rect(minData[0], minData[1], targetWidth, targetHeight);170                Mat temp = drawOnImage(source, rect, Scalar.RED);171                show(temp, scale + " " +  minData[0] + ":" + minData[1] + " " + minValue + " / " + targetMinVal);172            }173            return minData[2];174        }175        logger.debug("found match at scale {}, minVal: {} / {} at {}:{}", scale, minValue, targetMinVal, minData[0], minData[1]);176        if (findAll) {177            List<int[]> points = getPointsBelowThreshold(result, targetMinVal);178            for (int[] p : points) {179                Region region = toRegion(robot, p, scale, targetWidth, targetHeight);180                found.add(region);181            }182        } else {183            Region region = toRegion(robot, minData, scale, targetWidth, targetHeight);184            found.add(region);185        }186        return minValue;187    }188    public static List<Region> find(int strictness, boolean findAll, RobotBase robot, Mat source, Mat target, boolean resize) {189        List<Region> found = new ArrayList();190        collect(strictness, found, findAll, robot, source, target, 1);191        if (!found.isEmpty()) {...

getPointsBelowThreshold

Using AI Code Generation

1import com.intuit.karate.robot.OpenCvUtils2import java.awt.image.BufferedImage3import java.io.File4import javax.imageio.ImageIO5import java.awt.Color6import java.awt.Graphics2D7import java.awt.BasicStroke8import java.awt.Font9def image = ImageIO.read(new File('src/test/resources/opencv/opencv1.jpg'))10def points = OpenCvUtils.getPointsBelowThreshold(image, threshold)11def g = image.createGraphics()12g.setStroke(new BasicStroke(2))13g.setPaint(Color.red)14g.setFont(new Font('Arial Black', Font.BOLD, 20))15points.eachWithIndex{ point, index ->16    g.drawString(index.toString(), point.x, point.y)17    g.drawOval(point.x - 10, point.y - 10, 20, 20)18}19ImageIO.write(image, 'jpg', new File('target/opencv1.jpg'))20import com.intuit.karate.robot.OpenCvUtils21import java.awt.image.BufferedImage22import java.io.File23import javax.imageio.ImageIO24import java.awt.Color25import java.awt.Graphics2D26import java.awt.BasicStroke27import java.awt.Font28def image = ImageIO.read(new File('src/test/resources/opencv/opencv2.jpg'))29def points = OpenCvUtils.getPointsBelowThreshold(image, threshold)30def g = image.createGraphics()31g.setStroke(new BasicStroke(2))32g.setPaint(Color.red)33g.setFont(new Font('Arial Black', Font.BOLD, 20))34points.eachWithIndex{ point, index ->35    g.drawString(index.toString(), point.x, point.y)36    g.drawOval(point.x - 10, point.y - 10, 20, 20)37}38ImageIO.write(image, 'jpg', new File('target/opencv2.jpg'))39import com.intuit.karate.robot.OpenCvUtils40import java.awt.image.BufferedImage41import java.io.File42import javax.imageio.ImageIO43import java.awt.Color44import java.awt.Graphics2D45import java.awt.BasicStroke46import java.awt.Font47def image = ImageIO.read(new File('

getPointsBelowThreshold

Using AI Code Generation

1import com.intuit.karate.robot.OpenCvUtils2import org.opencv.core.Mat3import org.opencv.core.Point4def pointsBelowThreshold = OpenCvUtils.getPointsBelowThreshold(image, threshold)5def message = "There are " + pointsBelowThreshold.size() + " points below threshold " + threshold6log(message)7def pointsBelowThresholdAsString = pointsBelowThreshold.collect { Point point -> point.toString() }.join("\r8log(pointsBelowThresholdAsString)9* def pointsBelowThresholdAsString = pointsBelowThreshold.collect { Point point -> point.toString() }.join("\r10* log(pointsBelowThresholdAsString)11* def message = "There are " + pointsBelowThreshold.size() + " points below threshold " + threshold12* log(message)13* def pointsBelowThreshold = OpenCvUtils.getPointsBelowThreshold(image, threshold)14* def message = "There are " + pointsBelowThreshold.size() + " points below threshold " + threshold15* log(message)16* def pointsBelowThresholdAsString = pointsBelowThreshold.collect { Point point -> point.toString() }.join("\r17* log(pointsBelowThresholdAsString)18* def pointsBelowThreshold = OpenCvUtils.getPointsBelowThreshold(image, threshold)19* def message = "There are " + pointsBelowThreshold.size() + " points below threshold " + threshold20* log(message)21* def pointsBelowThresholdAsString = pointsBelowThreshold.collect { Point point -> point.toString() }.join("\r22* log(pointsBelowThresholdAsString)

getPointsBelowThreshold

Using AI Code Generation

1def points = OpenCvUtils.getPointsBelowThreshold(image, threshold, maxPoints)2def points = OpenCvUtils.removePointsWithinRadius(image, points, radius)3def circleCenter = OpenCvUtils.findCircleCenter(image, threshold, minRadius, maxRadius)4def rectangleCenter = OpenCvUtils.findRectangleCenter(image, threshold, minArea, maxArea)5def triangleCenter = OpenCvUtils.findTriangleCenter(image, threshold, minArea, maxArea)6def squareCenter = OpenCvUtils.findSquareCenter(image, threshold, minArea, maxArea)7def pentagonCenter = OpenCvUtils.findPentagonCenter(image, threshold, minArea, maxArea)8def hexagonCenter = OpenCvUtils.findHexagonCenter(image, threshold, minArea, maxArea)9def starCenter = OpenCvUtils.findStarCenter(image, threshold, minArea, maxArea)

getPointsBelowThreshold

Using AI Code Generation

1* def image = read('classpath:opencv/gradient.png')2* def gray = com.intuit.karate.robot.OpenCvUtils.toGray(image)3* def points = com.intuit.karate.robot.OpenCvUtils.getPointsBelowThreshold(gray, threshold)4* def image = read('classpath:opencv/gradient.png')5* def gray = com.intuit.karate.robot.OpenCvUtils.toGray(image)6* def points = com.intuit.karate.robot.OpenCvUtils.getPointsBelowThreshold(gray, threshold)7* fileChooser.sendKeys('C:\\Users\\abc\\Desktop\\test.xlsx')8* fileChooser.click()9* driver.switchTo().activeElement().sendKeys('C:\\Users\\abc\\Desktop\\test.xlsx')

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