let yolo;

let status;

let objects = [];

var myFont;

​

function preload() {

  myFont=loadFont('Roboto-Medium.ttf');

}

​

function setup() {

  createCanvas(640, 480);

  video = createCapture(VIDEO);

  video.size(width, height);

​

  var options = { filterBoxesThreshold: 0.01, IOUThreshold: 0.4, classProbThreshold: 0.4 }

  // Create a YOLO method

  yolo = ml5.YOLO(video, options, startDetecting);

​

  // Hide the original video

  video.hide();

  status = select('#status');

}

​

function draw() {

  image(video, 0, 0, width, height);

  for (let i = 0; i < objects.length; i++) {

    noStroke();

    fill(0, 255, 0);

    textSize(18);

    textFont(myFont);

    text(objects[i].label + " " + nfc(objects[i].confidence * 100.0, 2) + "%", objects[i].x * width, objects[i].y * height - 5);

    noFill();

    strokeWeight(4);

    stroke(0, 255, 0);

    rect(objects[i].x * width, objects[i].y * height, objects[i].w * width, objects[i].h * height);

  }

}

​

function startDetecting() {

  status.html('Model loaded!');

  detect();

}

​

function detect() {

  yolo.detect(function(err, results) {

    objects = results;

    detect();

  });

}