let video;

let label = "waiting...";

let confidence = 0.0;

let classifier;

let modelURL = 'https://teachablemachine.withgoogle.com/models/fmhBNG9g/'; //you can go to this URL to test your model outside of P5JS if you wish. Mightt be a good troubleshooting method? 

​

let imgA;

let imgB;

​

// STEP 1: Load the model and your outputs.

function preload() {

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

​

}

​

function setup() {

  createCanvas(640, 520);

  video = createCapture(VIDEO);

  video.hide();

  classifyVideo();

}

​

function draw() {

  background(0);

  image(video, 0, 0);

​

​

  // STEP 4: Show current label

  textSize(42);

  textAlign(CENTER, CENTER);

  //label = label.toUpperCase(); //capitalise

  fill(255, 0, 255);

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

​

  //STEP 5: Do something with the classification labels. 

  if (label == 'Person') {

    fill(255);

    ellipse(width / 2, height / 2, 50, 50);

  } else if (label == 'Phone') {

    fill(255, 0, 0);

    ellipse(width / 2, height -100, 50, 50);

​

  }

​

}

​

// STEP 2: Do the classifying

function classifyVideo() {

  classifier.classify(video, gotResults);

}

​

// STEP 3: Get the classification

function gotResults(error, results) {

  if (error) {

    console.error(error);

    return;

  }

  // Store the label and classify again

  //these are the variables useful to you!!!

  console.log(results);

  label = results[0].label; //classification label

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

  classifyVideo();

}