Quadrangulismo

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Code by Vamoss

Original code link:

https://openprocessing.org/sketch/1622375

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Author links:

http://vamoss.com.br

http://twitter.com/vamoss

http://github.com/vamoss

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const total = 5000;

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var img;

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const relaxIntensity = 1.0;

var delaunay;

var voronoi;

var cachedBrightness;

​

var points;

const closest = new Float64Array(total * 2);

const weights = new Float64Array(total);

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function preload() {

  img = loadImage('monalisa.jpg');

}

​

function setup() {

  createCanvas(img.width*2, img.height);

  cachedBrightness = new Float64Array(img.width * img.height);

  for (var y = 0, i = 0; y < img.height; y++) {

    for (var x = 0; x < img.width; x++) {

      var index = y * img.width + x;

      cachedBrightness[index] = 1 - red(img.get(x, y)) / 255;

    }

  }

  points = new Float64Array(total * 2);

  addPoints();

  delaunay = new Delaunay(points);

  voronoi = delaunay.voronoi([0, 0, img.width, img.height]);

}

​

function draw() {

  if(frameCount<120){

    relaxPoints();    

  }

  //draw points

  rectMode(CORNER);

  rect(0, 0, img.width, img.height);

  for(var i = 0; i < total; i++){

    circle(points[i*2], points[i*2+1], 3);

  }

  //draw quadtree

  push();

    translate(img.width, 0);

    fill(255);

    rect(0, 0, img.width, img.height);

    var boundary = new Rectangle(0, 0, img.width, img.height);

    var qtree = new QuadTree(boundary, 10);

    for(var i = 0; i < total; i++){

      qtree.insert(new Point(points[i*2], points[i*2+1]));

    }

    noFill();

    qtree.show();

  pop();

}

​

function addPoints(){

  var tries = 0;

  var added = 0;

  while(added < total && ++tries < 1000000){

    var x = round(random(img.width));

    var y = round(random(img.height));

    var index = y * img.width + x;

    if(Math.random() < cachedBrightness[index]){

      points[added * 2 + 0] = x;

      points[added * 2 + 1] = y;

      added++;

    }

  }

}

​

function relaxPoints(){

  // Compute the weighted centroid for each Voronoi cell.

  closest.fill(0);

  weights.fill(0);

  for (let y = 0, i = 0; y < img.height; ++y) {

    for (let x = 0; x < img.width; ++x) {

      const w = cachedBrightness[y * img.width + x];

      i = delaunay.find(x + 0.5, y + 0.5, i);

      weights[i] += w;

      closest[i * 2] += w * (x + 0.5);

      closest[i * 2 + 1] += w * (y + 0.5);

    }

  }

​

  // Relax the diagram by moving points to the weighted centroid.

  // Wiggle the points a little bit so they don’t get stuck.

  const w = Math.pow(frameCount + 1, -0.8) * 10;

  for (let i = 0; i < total; ++i) {

    const x0 = points[i * 2];

    const y0 = points[i * 2 + 1];

    const x1 = weights[i] ? closest[i * 2] / weights[i] : x0;

    const y1 = weights[i] ? closest[i * 2 + 1] / weights[i] : y0;

    points[i * 2] = x0 + (x1 - x0) * relaxIntensity + (Math.random() - 0.5) * w;

    points[i * 2 + 1] = y0 + (y1 - y0) * relaxIntensity + (Math.random() - 0.5) * w;

  }

​

  voronoi.update();

}