OpenCV and Processing 17 – Magic & Love Interactive

The example explores the Hough Circle detection in the Imgproc module. It starts with a greyscale copy of the live webcam image with an application of a blur filter, in this case, a medianBlur.

It also makes use of the CVImage class for the conversion between PImage and Mat in OpenCV.

import processing.video.*;
 
import org.opencv.video.Video;
import org.opencv.core.Mat;
import org.opencv.imgproc.Imgproc;
 
Capture cap;
CVImage img;
 
void setup() {
  size(640, 480, P3D);
  background(0);
  System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
  cap = new Capture(this, width, height);
  cap.start();
  cap.read();
  img = new CVImage(width, height);
  smooth();
}
 
void draw() {
  img.copy(cap, 0, 0, cap.width, cap.height, 0, 0, img.width, img.height);
  img.toCV();
 
  Mat grey = img.getGrey();
  Mat dst = new Mat(grey.size(), grey.type());
  Imgproc.medianBlur(grey, dst, 5);
  Mat circles = new Mat();
  Imgproc.HoughCircles(dst, circles, Imgproc.CV_HOUGH_GRADIENT, 1, 10, 100, 30, 10, 40);
 
  background(0);
  image(img, 0, 0);
 
  fill(255, 200, 0);
  if (circles.rows()>0) {
    for (int i=0; i<circles.cols(); i++) {
      double [] v = circles.get(0, i);
      float x = (float)v[0];
      float y = (float)v[1];
      float r = (float)v[2];
      ellipse(x, y, r*2, r*2);
    }
  }
 
  fill(0);
  noStroke();
  rect(0, 0, 110, 30);
  fill(255);
  text("Frame rate: " + nf(round(frameRate), 2), 10, 20, 0);
  grey.release();
  dst.release();
  circles.release();
}
 
void captureEvent(Capture _c) {
  _c.read();
}