// Intro to ML for the Arts, IMA Fall 2021

// https://github.com/ml5js/Intro-ML-Arts-IMA-F21

​

// Classifier Variable

let classifier;

// Model URL

const imageModelURL = 'https://teachablemachine.withgoogle.com/models/Vz2SwhNTm/';

​

// Video

let video;

let flippedVideo;

// To store the classification

let label = "";

​

// Load the model first

function preload() {

  // eslint-disable-next-line prefer-template

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

}

​

function setup() {

  createCanvas(320, 260);

  // Create the video

  video = createCapture(VIDEO);

  video.size(320, 240);

  video.hide();

​

  flippedVideo = ml5.flipImage(video)

  // Start classifying

  classifyVideo();

}

​

function draw() {

  background(0);

  // Draw the video

  image(flippedVideo, 0, 0);

​

  // Draw the label

  fill(255);

  textSize(16);

  textAlign(CENTER);

  text(label, width / 2, height - 4);

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  classifier.classify(gotResult);

}

​

// When we get a result

function gotResult(error, results) {

  // If there is an error

  if (error) {

    console.error(error);

    return;

  }

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

  // console.log(results[0]);

  label = results[0].label;

  console.log(label)

  // Classifiy again!

  classifyVideo();

}

​