​

// set variables

let classifier;

let angry;

let angry_eyes;

let wary_eyes;

let face_mask;

​

​

​

let imageModelURL = "https://teachablemachine.withgoogle.com/models/wTH7ZVDZw/";

​

// Video

let video;

let flippedVideo;

// To store the classification

let label = "";

​

// aja adds these two for the confidence threshold.

let confidence;

let formatted_conf = "";

​

// Text size varibles

var textS = 15;

​

// switch between neutral faces 

var n_count = 0;

​

​

​

// Load the model first

function preload() {

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

//loading images

  angry = loadImage('angry.png');

  angry_eyes = loadImage('angry_eyes.png');

  wary_eyes = loadImage('wary_eyes.png');    

  face_mask = loadImage('face_mask.png');

}

​

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);

​

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  flippedVideo = ml5.flipImage(video);

  classifier.classify(flippedVideo, gotResult);

  flippedVideo.remove();

}

​

// When we get a result

function gotResult(error, results) {

  // If there is an error

  if (error) {

    console.error(error);

    return;

  }

  label = results[0].label;

// tried to change text size based on result but I am not sure if I called the result properly because it did not work

  if (label == "Too Close"){

    image(angry, 0,0);

    image(angry_eyes,0,0);

    image(face_mask,0,0);

  } else if (label == "Close"){

    image(wary_eyes,0,0);

    image(face_mask,0,0);

  } else if (label == "Far"){

    n_count++;

    if (n_count <= 100){

      image(neutral_face_1,0,0);

    } else if (n_count > 100 && n_count <= 200){

      image(neutral_face_2,0,0);

      n_count = 0;

    }

  }

​

​

​

  // Classify again!

  classifyVideo();

}

​