Examples by @jorditost

Examples that use the ControlP5 lib for adjust filtering, blob
persistence and color tracking (of multiple colors):
- WhichFace.pde (adapted from algorithm by @shiffman)
- ImageFiltering.pde
- ImageFilteringWithBlobPersistence.pde
- HSVColorTracking.pde (from the examples of the OpenCV book by
@atduskgreg)
- MultipleColorTracking.pde

examples/HSVColorTracking/HSVColorTracking.pde

@@ -0,0 +1,107 @@
+/**
+ * HSVColorTracking
+ * Greg Borenstein
+ * https://github.com/atduskgreg/opencv-processing-book/blob/master/code/hsv_color_tracking/HSVColorTracking/HSVColorTracking.pde
+ *
+ * Modified by Jordi Tost @jorditost (color selection)
+ *
+ * University of Applied Sciences Potsdam, 2014
+ */
+
+import gab.opencv.*;
+import processing.video.*;
+import java.awt.Rectangle;
+
+Capture video;
+OpenCV opencv;
+PImage src, colorFilteredImage;
+ArrayList<Contour> contours;
+
+// <1> Set the range of Hue values for our filter
+int rangeLow = 20;
+int rangeHigh = 35;
+
+void setup() {
+  video = new Capture(this, 640, 480);
+  video.start();
+
+  opencv = new OpenCV(this, video.width, video.height);
+  contours = new ArrayList<Contour>();
+
+  size(2*opencv.width, opencv.height, P2D);
+}
+
+void draw() {
+
+  // Read last captured frame
+  if (video.available()) {
+    video.read();
+  }
+
+  // <2> Load the new frame of our movie in to OpenCV
+  opencv.loadImage(video);
+
+  // Tell OpenCV to use color information
+  opencv.useColor();
+  src = opencv.getSnapshot();
+
+  // <3> Tell OpenCV to work in HSV color space.
+  opencv.useColor(HSB);
+
+  // <4> Copy the Hue channel of our image into 
+  //     the gray channel, which we process.
+  opencv.setGray(opencv.getH().clone());
+
+  // <5> Filter the image based on the range of 
+  //     hue values that match the object we want to track.
+  opencv.inRange(rangeLow, rangeHigh);
+
+  // <6> Get the processed image for reference.
+  colorFilteredImage = opencv.getSnapshot();
+
+  ///////////////////////////////////////////
+  // We could process our image here!
+  // See ImageFiltering.pde
+  ///////////////////////////////////////////
+
+  // <7> Find contours in our range image.
+  //     Passing 'true' sorts them by descending area.
+  contours = opencv.findContours(true, true);
+
+  // <8> Display background images
+  image(src, 0, 0);
+  image(colorFilteredImage, src.width, 0);
+
+  // <9> Check to make sure we've found any contours
+  if (contours.size() > 0) {
+    // <9> Get the first contour, which will be the largest one
+    Contour biggestContour = contours.get(0);
+
+    // <10> Find the bounding box of the largest contour,
+    //      and hence our object.
+    Rectangle r = biggestContour.getBoundingBox();
+
+    // <11> Draw the bounding box of our object
+    noFill(); 
+    strokeWeight(2); 
+    stroke(255, 0, 0);
+    rect(r.x, r.y, r.width, r.height);
+
+    // <12> Draw a dot in the middle of the bounding box, on the object.
+    noStroke(); 
+    fill(255, 0, 0);
+    ellipse(r.x + r.width/2, r.y + r.height/2, 30, 30);
+  }
+}
+
+void mousePressed() {
+
+  color c = get(mouseX, mouseY);
+  println("r: " + red(c) + " g: " + green(c) + " b: " + blue(c));
+
+  int hue = int(map(hue(c), 0, 255, 0, 180));
+  println("hue to detect: " + hue);
+
+  rangeLow = hue - 5;
+  rangeHigh = hue + 5;
+}