// Coding Challenge

// The Coding Train / Daniel Shiffman

// https://thecodingtrain.com/CodingChallenges/157-zoom-annotations.html

// https://youtu.be/

​

// Basic: https://editor.p5js.org/codingtrain/sketches/EaioB_iJs

// Final: https://editor.p5js.org/codingtrain/sketches/ELpl_VAqs

​

// Classifier Variable

let classifier;

// Model URL

let imageModelURL = 'https://teachablemachine.withgoogle.com/models/iAr6pG2B6/';

​

// Video

let video;

let flippedVideo;

// To store the classification

let label = '';

​

let question;

let questionFade = 0;

​

// Load the model first

function preload() {

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

  question = loadImage('question.png');

}

​

function setup() {

  createCanvas(1280, 720);

  // Create the video

  video = createCapture(VIDEO);

  video.size(160, 120);

  // video.hide();

​

  flippedVideo = ml5.flipImage(video);

  // Start classifying

  classifyVideo();

}

​

function draw() {

  background(0, 255, 0);

  imageMode(CORNER);

​

  // Draw the video

  // tint(255);

  // image(flippedVideo, 0, 0);

  if (label == 'question') {

    questionFade = 255;

  }

  if (questionFade > 0) {

    tint(255, questionFade);

    image(question, 0, 0);

    questionFade -= 10;

  }

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  flippedVideo = ml5.flipImage(video);

  classifier.classify(flippedVideo, 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;

  // Classifiy again!

  classifyVideo();

}

​