--------------read edit below---------------
I am trying to detect the edge of the pupils and iris within various images. I am altering parameters and such but I can only manage to ever get one iris/pupil outline correct, or get unnecessary outlines in the background, or none at all. Is the some specific parameters that I should try to try and get the correct outlines. Or is there a way that I can crop the image just to the eyes, so the system can focus on that part?
This is my UPDATED method:
private void findPupilIris() throws IOException {
//converts and saves image in grayscale
Mat newimg = Imgcodecs.imread("/Users/.../pic.jpg");
Mat des = new Mat(newimg.rows(), newimg.cols(), newimg.type());
Mat norm = new Mat();
Imgproc.cvtColor(newimg, des, Imgproc.COLOR_BGR2HSV);
List<Mat> hsv = new ArrayList<Mat>();
Core.split(des, hsv);
Mat v = hsv.get(2); //gets the grey scale version
Imgcodecs.imwrite("/Users/Lisa-Maria/Documents/CapturedImages/B&Wpic.jpg", v); //only writes mats
CLAHE clahe = Imgproc.createCLAHE(2.0, new Size(8,8) ); //2.0, new Size(8,8)
clahe.apply(v,v);
// Imgproc.GaussianBlur(v, v, new Size(9,9), 3); //adds left pupil boundary and random circle on 'a'
// Imgproc.GaussianBlur(v, v, new Size(9,9), 13); //adds right outer iris boundary and random circle on 'a'
Imgproc.GaussianBlur(v, v, new Size(9,9), 7); //adds left outer iris boundary and random circle on left by hair
// Imgproc.GaussianBlur(v, v, new Size(7,7), 15);
Core.addWeighted(v, 1.5, v, -0.5, 0, v);
Imgcodecs.imwrite("/Users/.../after.jpg", v); //only writes mats
if (v != null) {
Mat circles = new Mat();
Imgproc.HoughCircles( v, circles, Imgproc.CV_HOUGH_GRADIENT, 2, v.rows(), 100, 20, 20, 200 );
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
System.out.println("circles.cols() " + circles.cols());
if(circles.cols() > 0) {
System.out.println("1");
for (int x = 0; x < circles.cols(); x++) {
System.out.println("2");
double vCircle[] = circles.get(0, x);
if(vCircle == null) {
break;
}
Point pt = new Point(Math.round(vCircle[0]), Math.round(vCircle[1]));
int radius = (int) Math.round(vCircle[2]);
//draw the found circle
Imgproc.circle(v, pt, radius, new Scalar(255,0,0),2); //newimg
//Imgproc.circle(des, pt, radius/3, new Scalar(225,0,0),2); //pupil
Imgcodecs.imwrite("/Users/.../Houghpic.jpg", v); //newimg
//draw the mask: white circle on black background
// Mat mask = new Mat( new Size( des.cols(), des.rows() ), CvType.CV_8UC1 );
// Imgproc.circle(mask, pt, radius, new Scalar(255,0,0),2);
// des.copyTo(des,mask);
// Imgcodecs.imwrite("/Users/..../mask.jpg", des); //newimg
Imgproc.logPolar(des, norm, pt, radius, Imgproc.WARP_FILL_OUTLIERS);
Imgcodecs.imwrite("/Users/..../Normalised.jpg",norm);
}
}
}
}
Result: hough pic
Following discussion in comments, I am posting a general answer with some results I got on the worst case image uploaded by the OP.
Note : The code I am posting is in Python, since it is the fastest for me to write
Step 1. As you ask for a way to crop the image, so as to focus on the eyes only, you might want to look at Face Detection. Since, the image essentially requires to find eyes only, I did the following:
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
eyes = eye_cascade.detectMultiScale(v) // v is the value channel of the HSV image
// The results "eyes" gives you the dimensions of the rectangle where the eyes are detected as [x, y, w, h]
// Just for drawing
cv2.rectangle(v, (x1, y1), (x1+w1, y1+h1), (0, 255, 0), 2)
cv2.rectangle(v, (x2, y2), (x2+w2, y2+h2), (0, 255, 0), 2)
Now, once you have the bounding rectangles, you can crop the rectangles from the image like:
crop_eye1 = v[y1:y1+h1, x1:x1+w1]
crop_eye2 = v[y2:y2+h2, x2:x2+w2]
After you obtain the rectangles, I would suggest looking into different color spaces instead of RGB/BGR, HSV/Lab/Luv in particular.
Because the R, G, and B components of an object’s color in a digital image are all correlated with the amount of light hitting the object, and therefore with each other, image descriptions in terms of those components make object discrimination difficult. Descriptions in terms of hue/lightness/chroma or hue/lightness/saturation are often more relevant
Then, once, you have the eyes, its time to equalize the contrast of the image, however, I suggest using CLAHE and play with the parameters for clipLimit and tileGridSize. Here is a code which I implemented a while back in Java:
private static Mat clahe(Mat image, int ClipLimit, Size size){
CLAHE clahe = Imgproc.createCLAHE();
clahe.setClipLimit(ClipLimit);
clahe.setTilesGridSize(size);
Mat dest_image = new Mat();
clahe.apply(image, dest_image);
return dest_image;
}
Once you are satisfied, you should sharpen the image so that HoughCircle is robust. You should look at unsharpMask. Here is the code in Java for UnsharpMask I implemented in Java:
private static Mat unsharpMask(Mat input_image, Size size, double sigma){
// Make sure the {input_image} is gray.
Mat sharpend_image = new Mat(input_image.rows(), input_image.cols(), input_image.type());
Mat Blurred_image = new Mat(input_image.rows(), input_image.cols(), input_image.type());
Imgproc.GaussianBlur(input_image, Blurred_image, size, sigma);
Core.addWeighted(input_image, 2.0D, Blurred_image, -1.0D, 0.0D, sharpened_image);
return sharpened_image;
}
Alternatively, you could use bilateral filter, which is edge preserving smoothing, or read through this for defining a custom kernel for sharpening image.
Hope it helps and best of luck!
Related
I am new to android. I am using opencv to detect face and mouth of a person. It is not detecting mouth correctly. Can you help me in this?
Here is my code:
mJavaDetectorLip =
loadClassifier(R.raw.haarcascade_mcs_mouth,"haarcascade_mcs_mouth.xml",
cascadeDir);
......
Rect liparea = new Rect(new Point(20,20),new Point(mGray.width() - 20,
mGray.height() - 20 ));
lipArea(mJavaLip,liparea,100);
......
here is my code:
private Mat lipArea(CascadeClassifier clasificator, Rect area, int
size) {
Mat template = new Mat();
Mat mROI = mGray.submat(area);
MatOfRect mouths = new MatOfRect();
Point lips = new Point();
//isolate the eyes first
clasificator.detectMultiScale(mROI, mouths, 1.1, 2, Objdetect.CASCADE_FIND_BIGGEST_OBJECT
| Objdetect.CASCADE_SCALE_IMAGE, new Size(30, 30), new Size());
Rect[] mouthArray = mouths.toArray();
for (int i = 0; i < mouthArray.length;) {
Rect e = mouthArray[i];
e.x = area.x + e.x;
e.y = area.y + e.y;
Point center1 = new Point(e.x + mouthArray[i].width * 0.5,
e.y + mouthArray[i].height * 0.5);
int radius = (int) Math.round(mouthArray[i].width / 2);
Imgproc.circle(mRgba, center1, radius, new Scalar(255, 0, 0), 4, 8, 0);
new Scalar(0,255,0),1,8,0);
return template;
}
return template;
}
It is not staying in one place, it is moving around the whole face.
It is not staying in one place, it is moving around the whole face.
It is an expected behavior as the features of mouth are very much limited and there is a high chance of false positives. For example your eyes would also have similar features as your lip. To mitigate this issue, OpenCV docs suggest that we must first detect the faces in a given frame, if there are multiple then choose a single one depending upon area of face rect or some other param. After successful detection of face, divide the face rect into halves and search for the lips in the lower half only.
This would significantly increase your accuracy, because the Haar features for face are pretty complex and well trained. Narrowing down your search domain from the whole frame to lower half of your face would save time as well.
I have a captured image, the image consists of a table. I want to crop the table out of that image.
This is a sample image.
Can someone suggest what can be done?
I have to use it in android.
Use a hough transform to find the lines in the image.
OpenCV can easily do this and has java bindings. See the tutorial on this page on how to do something very similar.
https://docs.opencv.org/3.4.1/d9/db0/tutorial_hough_lines.html
Here is the java code provided in the tutorial:
import org.opencv.core.*;
import org.opencv.core.Point;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
class HoughLinesRun {
public void run(String[] args) {
// Declare the output variables
Mat dst = new Mat(), cdst = new Mat(), cdstP;
String default_file = "../../../../data/sudoku.png";
String filename = ((args.length > 0) ? args[0] : default_file);
// Load an image
Mat src = Imgcodecs.imread(filename, Imgcodecs.IMREAD_GRAYSCALE);
// Check if image is loaded fine
if( src.empty() ) {
System.out.println("Error opening image!");
System.out.println("Program Arguments: [image_name -- default "
+ default_file +"] \n");
System.exit(-1);
}
// Edge detection
Imgproc.Canny(src, dst, 50, 200, 3, false);
// Copy edges to the images that will display the results in BGR
Imgproc.cvtColor(dst, cdst, Imgproc.COLOR_GRAY2BGR);
cdstP = cdst.clone();
// Standard Hough Line Transform
Mat lines = new Mat(); // will hold the results of the detection
Imgproc.HoughLines(dst, lines, 1, Math.PI/180, 150); // runs the actual detection
// Draw the lines
for (int x = 0; x < lines.rows(); x++) {
double rho = lines.get(x, 0)[0],
theta = lines.get(x, 0)[1];
double a = Math.cos(theta), b = Math.sin(theta);
double x0 = a*rho, y0 = b*rho;
Point pt1 = new Point(Math.round(x0 + 1000*(-b)), Math.round(y0 + 1000*(a)));
Point pt2 = new Point(Math.round(x0 - 1000*(-b)), Math.round(y0 - 1000*(a)));
Imgproc.line(cdst, pt1, pt2, new Scalar(0, 0, 255), 3, Imgproc.LINE_AA, 0);
}
// Probabilistic Line Transform
Mat linesP = new Mat(); // will hold the results of the detection
Imgproc.HoughLinesP(dst, linesP, 1, Math.PI/180, 50, 50, 10); // runs the actual detection
// Draw the lines
for (int x = 0; x < linesP.rows(); x++) {
double[] l = linesP.get(x, 0);
Imgproc.line(cdstP, new Point(l[0], l[1]), new Point(l[2], l[3]), new Scalar(0, 0, 255), 3, Imgproc.LINE_AA, 0);
}
// Show results
HighGui.imshow("Source", src);
HighGui.imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst);
HighGui.imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP);
// Wait and Exit
HighGui.waitKey();
System.exit(0);
}
}
public class HoughLines {
public static void main(String[] args) {
// Load the native library.
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new HoughLinesRun().run(args);
}
}
Lines or LinesP will contain the found lines. Instead of drawing them (as in the example) you will want to manipulate them a little further.
Sort the found lines by slope.
The two largest clusters will be horizontal lines and then vertical lines.
For the horizontal lines calculate and sort by the y intercept.
The largest y intercept describes the top of the table.
The smallest y intercept is the bottom of the table.
For the vertical lines calculate and sort by the x intercept.
The largest x intercept is the right side of the table.
The smallest x intercept is the left side of the table.
You'll now have the coordinates of the four table corners and can do standard image manipulation to crop/rotate etc. OpenCV can help you will this step too.
Convert your image to grayscale.
Threshold your image to drop noise.
Find the minimum area rect of the non-blank pixels.
In python the code would look like:
import cv2
import numpy as np
img = cv2.imread('table.jpg')
imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 222, 255, cv2.THRESH_BINARY )
# write out the thresholded image to debug the 222 value
cv2.imwrite("thresh.png", thresh)
indices = np.where(thresh != 255)
coords = np.array([(b,a) for a, b in zip(*(indices[0], indices[1]))])
# coords = cv2.convexHull(coords)
rect = cv2.minAreaRect(coords)
box = cv2.boxPoints(rect)
box = np.int0(box)
cv2.drawContours(img, [box], 0, (0, 0, 255), 2)
cv2.imwrite("box.png", img)
For me this produces the following image.
If your image didn't have the red squares it would be a tighter fit.
I am able to detect and draw a bounding rectangle around a region of interest like so:
Now I need to find the "x" value of the bottom horizontal line of the green bounding rectangle. My main aim is to find the "x" value of the base of the battery, and the "x" value of the blue strip of paper, so that I can calculate the distance between them.
There are only 2 values, rect.tl() and rect.br(), that I can see be used to draw the bounding rectangle Imgproc.rectangle(sourceMat, rect.tl(), rect.br(), green, 3);. I'm under the assumption that the "x" value from the bottom right point of the bounding rectangle will be the x co-ordinate of the pixel point.
How do i get the 'x' value from rect.br()
When i print out rect.br() like so Log.e("BR", rect.br().toString()); i get this:
E/BR: {793.0, 1686.0}
private Bitmap findRoi(Bitmap sourceBitmap) {
Bitmap roiBitmap = null;
Scalar green = new Scalar(0, 255, 0, 255);
Mat sourceMat = new Mat(sourceBitmap.getWidth(), sourceBitmap.getHeight(), CvType.CV_8UC3);
Utils.bitmapToMat(sourceBitmap, sourceMat);
Mat roiTmp = sourceMat.clone();
final Mat hsvMat = new Mat();
sourceMat.copyTo(hsvMat);
// convert mat to HSV format for Core.inRange()
Imgproc.cvtColor(hsvMat, hsvMat, Imgproc.COLOR_RGB2HSV);
Scalar lowerb = new Scalar(85, 50, 40); // lower color border for BLUE
Scalar upperb = new Scalar(135, 255, 255); // upper color border for BLUE
Core.inRange(hsvMat, lowerb, upperb, roiTmp); // select only blue pixels
// find contours
List<MatOfPoint> contours = new ArrayList<>();
List<RotatedRect> boundingRects = new ArrayList<>();
Imgproc.findContours(roiTmp, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
// find appropriate bounding rectangles
for (MatOfPoint contour : contours) {
MatOfPoint2f areaPoints = new MatOfPoint2f(contour.toArray());
RotatedRect boundingRect = Imgproc.minAreaRect(areaPoints);
double rectangleArea = boundingRect.size.area();
// test min ROI area in pixels
if (rectangleArea > 40001) {//400000
Point rotated_rect_points[] = new Point[4];
boundingRect.points(rotated_rect_points);
Rect rect = Imgproc.boundingRect(new MatOfPoint(rotated_rect_points));
// test horizontal ROI orientation
if (rect.width > rect.height) {
Imgproc.rectangle(sourceMat, rect.tl(), rect.br(), green, 3);
}
}
}
roiBitmap = Bitmap.createBitmap(sourceMat.cols(), sourceMat.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(sourceMat, roiBitmap);
return roiBitmap;
}
I don't know a lot about Java but AFAIK it must be similar to c++, so whether you know about it or not,I try my code in c++. Suppose that you are working on the below rectangle:
For having the above Rect in OpenCV:
Rect r = Rect(20,20,30,20); // Rect(x,y,width,height)
And we could access the below-right x with using the br() like the below.
int x2=r.br().x ;
Below pic will tell you the whole story.
I've just learnt how to detect a color from OpenCV Java, Getting region of interest from image.
Ultimately, I want to know how can I detect the AA battery(with and or without black tape)
I'm now trying to detect the battery in the picture, but the battery is not fully black, and in turn giving me weird result:
I covered the battery with black tape and tried again the result seems better but it is detecting the battery in two separate sections:
Code:
private Bitmap findRoiBlack(Bitmap sourceBitmap) {
Bitmap roiBitmap = null;
Scalar green = new Scalar(0, 255, 0, 255);
Mat sourceMat = new Mat(sourceBitmap.getWidth(), sourceBitmap.getHeight(), CvType.CV_8UC3);
Utils.bitmapToMat(sourceBitmap, sourceMat);
Mat roiTmp = sourceMat.clone();
final Mat hsvMat = new Mat();
sourceMat.copyTo(hsvMat);
// convert mat to HSV format for Core.inRange()
Imgproc.cvtColor(hsvMat, hsvMat, Imgproc.COLOR_RGB2HSV);
Scalar lowerb = new Scalar(0, 0, 0); // lower color border for BLACK
Scalar upperb = new Scalar(180, 255, 30); // upper color border for BLACK
//Scalar lowerb = new Scalar(0, 0, 200); // lower color border for WHITE
//Scalar upperb = new Scalar(180, 255, 255); // upper color border for WHITE
Core.inRange(hsvMat, lowerb, upperb, roiTmp); // select only blue pixels
// find contours
List<MatOfPoint> contours = new ArrayList<>();
List<RotatedRect> boundingRects = new ArrayList<>();
Imgproc.findContours(roiTmp, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
// find appropriate bounding rectangles
for (MatOfPoint contour : contours) {
MatOfPoint2f areaPoints = new MatOfPoint2f(contour.toArray());
RotatedRect boundingRect = Imgproc.minAreaRect(areaPoints);
double rectangleArea = boundingRect.size.area();
// test min ROI area in pixels
if (rectangleArea > 400) {
Point rotated_rect_points[] = new Point[4];
boundingRect.points(rotated_rect_points);
Rect rect = Imgproc.boundingRect(new MatOfPoint(rotated_rect_points));
// test vertical ROI orientation
if (rect.height > rect.width) {
Imgproc.rectangle(sourceMat, rect.tl(), rect.br(), green, 3);
}
}
}
roiBitmap = Bitmap.createBitmap(sourceMat.cols(), sourceMat.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(sourceMat, roiBitmap);
return roiBitmap;
}
Easiest way - is add color marker to battery. Other way is set solid, well distinguishable background for vertical channel of Your installation (may be even backlight - in this case You should find just black/low brightness object on white/high brightness background). If it's not possible and You have solid background - try to "invert" approach: don't try find battery (because it has many colors) - find background (because it has one solid color) - object with "non background" colors probably battery (and You have additional hints: battery is "vertical" rectangle with 1/4 proportions (AAA battery has 10.5 mm diameter and 44.6 mm length), it is approximately on the vertical center of image and has chromium-plated high brightness elements on top and bottom, etc.).
I want to draw some (filled) polygons with libGDX. It shoudn't be filled with a graphic/texture. I have only the vertices of the polygon (closed path) and tried to visualize with meshes but at some point this is not the best solution, I think.
My code for an rectangle is:
private Mesh mesh;
#Override
public void create() {
if (mesh == null) {
mesh = new Mesh(
true, 4, 0,
new VertexAttribute(Usage.Position, 3, "a_position")
);
mesh.setVertices(new float[] {
-0.5f, -0.5f, 0
0.5f, -0.5f, 0,
-0.5f, 0.5f, 0,
0.5f, 0.5f, 0
});
}
}
// ...
#Override
public void render() {
Gdx.gl.glClear(GL10.GL_COLOR_BUFFER_BIT);
mesh.render(GL10.GL_TRIANGLE_STRIP, 0, 4);
}
is there a function or something to draw filled polygons in an easier way?
Since recent updates of LibGDX, #Rus answer is using deprecated functions. However, I give him/her credits for the new updated version below:
PolygonSprite poly;
PolygonSpriteBatch polyBatch = new PolygonSpriteBatch(); // To assign at the beginning
Texture textureSolid;
// Creating the color filling (but textures would work the same way)
Pixmap pix = new Pixmap(1, 1, Pixmap.Format.RGBA8888);
pix.setColor(0xDEADBEFF); // DE is red, AD is green and BE is blue.
pix.fill();
textureSolid = new Texture(pix);
PolygonRegion polyReg = new PolygonRegion(new TextureRegion(textureSolid),
new float[] { // Four vertices
0, 0, // Vertex 0 3--2
100, 0, // Vertex 1 | /|
100, 100, // Vertex 2 |/ |
0, 100 // Vertex 3 0--1
}, new short[] {
0, 1, 2, // Two triangles using vertex indices.
0, 2, 3 // Take care of the counter-clockwise direction.
});
poly = new PolygonSprite(polyReg);
poly.setOrigin(a, b);
polyBatch = new PolygonSpriteBatch();
For good triangulating algorithms if your polygon is not convex, see the almost-linear earclipping algorithm from Toussaint (1991)
Efficient triangulation of simple polygons, Godfried Toussaint, 1991
Here is a libGDX example which draws a 2D concave polygon.
Define class members for PolygonSprite PolygonSpriteBatch
PolygonSprite poly;
PolygonSpriteBatch polyBatch;
Texture textureSolid;
Create instances, 1x1 size texture used with red pixel as workaround. An array of coordinates (x, y) is used for initialization of the polygon.
ctor() {
textureSolid = makeTextureBox(1, 0xFFFF0000, 0, 0);
float a = 100;
float b = 100;
PolygonRegion polyReg = new PolygonRegion(new TextureRegion(textureSolid),
new float[] {
a*0, b*0,
a*0, b*2,
a*3, b*2,
a*3, b*0,
a*2, b*0,
a*2, b*1,
a*1, b*1,
a*1, b*0,
});
poly = new PolygonSprite(polyReg);
poly.setOrigin(a, b);
polyBatch = new PolygonSpriteBatch();
}
Draw and rotate polygon
void draw() {
super.draw();
polyBatch.begin();
poly.draw(polyBatch);
polyBatch.end();
poly.rotate(1.1f);
}
I believe the ShapeRenderer class now has a polygon method for vertex defined polygons:
ShapeRenderer.polygon()
You can use the ShapeRenderer API to draw simple, solid-color shapes with Libgdx.
The code you've given is a reasonable way to draw solid color polygons too. Its much more flexible than ShapeRenderer, but is a good bit more complicated. You'll need to use glColor4f to set the color, or add a Usage.Color attribute to each vertex. See the SubMeshColorTest example for more details on the first approach and the MeshColorTexture example for details on the second approach.
Another option to think about is using sprite textures. If you're only interested in simple solid colors objects, you can use very simple 1x1 textures of a single color and let the system stretch that across the sprite. Much of Libgdx and the underlying hardware are really optimized for rendering textures, so you may find it easier to use even if you're not really taking advantage of the texture contents. (You can even use a 1x1 white texture, and then use a SpriteBatch with setColor and draw()
to draw different color rectangles easily.)
You can also mix and match the various approaches, too.
Use triangulation algorithm and then draw all triangles as GL_TRIANGLE_STRIP
http://www.personal.psu.edu/cxc11/AERSP560/DELAUNEY/13_Two_algorithms_Delauney.pdf
just wanted to share my related solution with you, namely for implementing and drawing a walkZone with scene2d. I basically had to put together the different suggestions of the others' posts:
1) The WalkZone:
import com.badlogic.gdx.graphics.Pixmap;
import com.badlogic.gdx.graphics.Texture;
import com.badlogic.gdx.graphics.g2d.PolygonRegion;
import com.badlogic.gdx.graphics.g2d.TextureRegion;
import com.badlogic.gdx.math.EarClippingTriangulator;
import com.badlogic.gdx.math.Polygon;
import com.mygdx.game.MyGame;
public class WalkZone extends Polygon {
private PolygonRegion polygonRegion = null;
public WalkZone(float[] vertices) {
super(vertices);
if (MyGame.DEBUG) {
Pixmap pix = new Pixmap(1, 1, Pixmap.Format.RGBA8888);
pix.setColor(0x00FF00AA);
pix.fill();
polygonRegion = new PolygonRegion(new TextureRegion(new Texture(pix)),
vertices, new EarClippingTriangulator().computeTriangles(vertices).toArray());
}
}
public PolygonRegion getPolygonRegion() {
return polygonRegion;
}
}
2) The Screen:
you can then add a listener in the desired Stage:
myStage.addListener(new InputListener() {
#Override
public boolean touchDown(InputEvent event, float x, float y, int pointer, int button) {
if (walkZone.contains(x, y)) player.walkTo(x, y);
// or even directly: player.addAction(moveTo ...
return super.touchDown(event, x, y, pointer, button);
}
});
3) The implementation:
The array passed to te WZ constructor is a set of x,y,x,y... points. If you put them counter-clockwise, it works (I didn't check the other way, nor know how it exactly works); for example this generates a 100x100 square:
yourScreen.walkZone = new WalkZone(new int[]{0, 0, 100, 0, 100, 100, 0, 100});
In my project it works like a charm, even with very intricated polygons. Hope it helps!!
Most answers suggest triangulation, which is fine, but you can also do it using the stencil buffer. It handles both convex and concave polygons. This may be a better solution if your polygon changes a lot, since otherwise you'd have to do triangulation every frame. Also, this solution properly handles self intersecting polygons, which EarClippingTriangulator does not.
FloatArray vertices = ... // The polygon x,y pairs.
Color color = ... // The color to draw the polygon.
ShapeRenderer shapes = ...
ImmediateModeRenderer renderer = shapes.getRenderer();
Gdx.gl.glClearStencil(0);
Gdx.gl.glClear(GL20.GL_STENCIL_BUFFER_BIT);
Gdx.gl.glEnable(GL20.GL_STENCIL_TEST);
Gdx.gl.glStencilFunc(GL20.GL_NEVER, 0, 1);
Gdx.gl.glStencilOp(GL20.GL_INVERT, GL20.GL_INVERT, GL20.GL_INVERT);
Gdx.gl.glColorMask(false, false, false, false);
renderer.begin(shapes.getProjectionMatrix(), GL20.GL_TRIANGLE_FAN);
renderer.vertex(vertices.get(0), vertices.get(1), 0);
for (int i = 2, n = vertices.size; i < n; i += 2)
renderer.vertex(vertices.get(i), vertices.get(i + 1), 0);
renderer.end();
Gdx.gl.glColorMask(true, true, true, true);
Gdx.gl.glStencilOp(GL20.GL_ZERO, GL20.GL_ZERO, GL20.GL_ZERO);
Gdx.gl.glStencilFunc(GL20.GL_EQUAL, 1, 1);
Gdx.gl.glEnable(GL20.GL_BLEND);
shapes.setColor(color);
shapes.begin(ShapeType.Filled);
shapes.rect(-9999999, -9999999, 9999999 * 2, 9999999 * 2);
shapes.end();
Gdx.gl.glDisable(GL20.GL_STENCIL_TEST);
To use the stencil buffer, you must specify the number of bits for the stencil buffer when your app starts. For example, here is how to do that using the LWJGL2 backend:
LwjglApplicationConfiguration config = new LwjglApplicationConfiguration();
config.stencil = 8;
new LwjglApplication(new YourApp(), config);
For more information on this technique, try one of these links:
http://commaexcess.com/articles/7/concave-polygon-triangulation-shortcut
http://glprogramming.com/red/chapter14.html#name13
http://what-when-how.com/opengl-programming-guide/drawing-filled-concave-polygons-using-the-stencil-buffer-opengl-programming/