let classifier;

​

// A variable to hold the video we want to classify

let video;

​

// Variable for displaying the results on the canvas

let label = "Model loading...";

​

let imageModelURL = "https://teachablemachine.withgoogle.com/models/7oICg90E2/";

​

// to use original source uncomment the following line

// let imageModelURL = "MobileNet";

​

​

function preload() {

  ml5.setBackend('webgl');

  classifier = ml5.imageClassifier(imageModelURL, {flipped:true});

}

​

function setup() {

  createCanvas(640, 480);

​

  // Create the webcam video and hide it

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

  video.size(640, 480);

  video.hide();

​

  // Start detecting objects in the video

  classifier.classifyStart(video, gotResult);

}

​

function draw() {

  // Each video frame is painted on the canvas

  image(video, 0, 0);

​

  // Printing class with the highest probability on the canvas

  fill(0, 255, 0);

  textSize(32);

  text(label, 20, 50);

  if(label == "Alp") {

    textSize(64);

    text("🐰", width/2, height/2);

  }

}

​

// A function to run when we get the results

function gotResult(results) {

  // Update label variable which is displayed on the canvas

  label = results[0].label;

  //  console.log(results)

}

​