let bild_left;

let bild_right;

let glasses;

let classifier;

let result;

let mySound;

let mover = -100;

let posenet;

let poses = [];

​

​

function preload(){

  bild_left = loadImage("bild.png");

  bild_right = loadImage("bild_right.png");

  glasses = loadImage("glasses.png")

  classifier = ml5.imageClassifier('https://teachablemachine.withgoogle.com/models/njJSdhAOZ/' + 'model.json');

  mySound = loadSound('sound.wav');

}

function setup() {

  createCanvas(640, 480);

  video = createCapture(VIDEO);

  video.hide();

  classifier.classify(video, gotResults)

  posenet = ml5.poseNet(video, poseNetLoaded)

  posenet.on('pose', poseGotResults);

}

​

function draw() {

  mover++;

  if (mover > height - 300){

    mover = -100;

  }

  background(100);

  image(video,0,0);

  if(result == "Weg"){

    if(!mySound.isPlaying()){

    mySound.play()

    }

  image(bild_left,0,100,300,400)

  image(bild_right,400,100,300,400)

    if(poses.length > 0){

   push()

      imageMode(CENTER)

      let nose = poses[0].pose.keypoints[0].position;

      let leftEar = poses[0].pose.keypoints[3].position;

      let rightEar = poses[0].pose.keypoints[4].position;

  image(glasses, nose.x, mover, dist(leftEar.x, leftEar.y, rightEar.x,rightEar.y)*1.5,dist(leftEar.x, leftEar.y, rightEar.x,rightEar.y)/1.3)

      pop()

  }

  }

  else{

    mySound.pause()

  }

}

function poseNetLoaded(){

  console.log("Model Loaded!")

}

function poseGotResults(results){

 // console.log(results)

  poses = results;

}

​

function gotResults(error,results){

  result = results[0].label;

  classifier.classify(video, gotResults)

}