let imageModelURL = 'https://teachablemachine.withgoogle.com/models/AI5i76oG/'

​

let video

let flippedVideo

let label = ''

​

let voice = new p5.Speech()

​

function preload() {

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

}

​

function setup() {

  createCanvas(windowWidth, windowWidth * 0.75)

  video = createCapture(VIDEO)

  video.size(width, height)

  video.hide()

​

  flippedVideo = ml5.flipImage(video)

  classifyVideo()

}

​

function draw() {

  background(0)

  image(flippedVideo, 0, 0)

​

  noStroke()

  fill(100, 100, 100, 200)

  rect(0, height - 64, width, 64)

  fill(255)

  textFont('system-ui')

  textSize(48)

  textAlign(CENTER)

  text(label, width / 2, height - 15)

}

​

function classifyVideo() {

  flippedVideo = ml5.flipImage(video)

  classifier.classify(flippedVideo, gotResult)

}

​

function gotResult(error, results) {

  if (error) {

    console.error(error)

    return

  }

  const newLabel = results[0].label

  if (newLabel !== label) {

    voice.speak(label)

    label = newLabel

  }

  classifyVideo()

}

​