let label = "waiting...";

let confidence = 0.0; 

let classifier;

​

function setup() {

  createCanvas(640, 540);

  // Create a video element

  video = createCapture(VIDEO);

  video.hide();

  // STEP 1: Load the model

  classifier = ml5.imageClassifier('MobileNet', video, modelReady);

}

​

function draw() {

  background(0);

  image(video, 0, 0, width, height);

​

  // STEP 4: Show current label

  textSize(32);

  textAlign(CENTER, CENTER);

  fill(255);

  text(label + " " + confidence, width / 2, height - 16);

}

​

function modelReady() {

  console.log('Model Ready');

  classifyVideo();

}

​

// STEP 2: Do the classifying

function classifyVideo() {

  classifier.classify(gotResult);

}

​

// STEP 3: Get the classification

function gotResult(err, results) {

  // The results are in an array ordered by confidence.

  label = results[0].label;

  confidence = nf(results[0].confidence, 0, 2);

  classifyVideo();

}

​