let imageModelURL = 'https://teachablemachine.withgoogle.com/models/IhvUG4ryYm/';

​

let classifier;

let video;

let label = '';  // to store the classification

let confidence = '';

​

// load the model first

function preload() {

  classifier = ml5.imageClassifier(imageModelURL + 'model.json');

}

​

function setup() {

  createCanvas(640, 480);

  // create the video

  // Teachable Machine recorded the camera as if looking into a mirror

  // (right and left swapped); because of this, we flip the camera image as well

  video = createCapture(VIDEO, { flipped: true });

  video.size(640, 480);

  video.hide();

​

  // start classifying

  classifier.classifyStart(video, gotResult);

}

​

function draw() {

  background(0);

  // draw the video

  image(video, 0, 0);

​

  // draw the label

  fill(255);

  textSize(16);

  textAlign(CENTER);

  text(label + " @ " + confidence, width / 2, height - 4);

}

​

// this function is executed whenever classification finishes

// it's thus a "callback function"

function gotResult(results) {

  // the results are in an array ordered by confidence

  label = results[0].label;

  confidence = results[0].confidence;

}

​