// Model URL

let imageModelURL = 'https://teachablemachine.withgoogle.com/models/19BHIISZU/';

​

​

// Video

let video;

let flippedVideo;

// To store the classification

let label = '';

let word = '';

let l = '';

let l1 = '';

let count = 0;

let n = 60;

let sent='';

let f=0;

let len=0;

  let foo = new p5.Speech();

// Load the model first

function preload() {

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

}

function setup() {

  createCanvas(400, 260);

  // Create the video

  button = createButton('Convert');

  button.position(330,30);

  button.mousePressed(convert);

  button = createButton('Clear');

  button.position(330,60);

  button.mousePressed(cls);

  button = createButton('Back');

  button.position(330,90);

  button.mousePressed(back);

  video = createCapture(VIDEO);

  video.size(320, 240);

  video.hide();

​

  colorMode(RGB, 100);

  flippedVideo = ml5.flipImage(video)

  // Start classifying

  classifyVideo();

}

​

function draw() {

  background(0);

  // Draw the video

  image(flippedVideo, 0, 0);

  stroke('green');

​

​

  noFill();

  square(200, 50, 100);

  // Draw the label

  fill(255);

  textSize(16);

  textAlign(LEFT);

  text(label, 10, 10);

  textAlign(CENTER);

  text(word, width / 2, height - 4);

​

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  flippedVideo = ml5.flipImage(video)

  let c = flippedVideo.get(205, 55, 100, 100);

  classifier.classify(c, 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;

  // Classify again!

  triggers();

  if (count === n) {

    letter(l);

    count = 0;

    l = '';

    if (l1 !== '1') {

      word = word.concat(l1);

      f=0;

      len++;

    } else {

       f++;

      if(f===1){

        word = word.concat(' ');

        len++;

      }

  }

  }

  setInterval(classifyVideo(), 1300);

}

​

function letter(l) {

  let k = 0;

  for (let i = 0; i < n; i++) {

    let c = 0;

    for (let j = 0; j < n; j++) {

      if (l[i] === l[j]) {

        c++;

      }

      if (c > k) {

        k = c;

        l1 = l[i];

      }

    }

  }

}

function spell(sent){

var data = null;

var xhr = new XMLHttpRequest();

xhr.withCredentials = true;

​

xhr.addEventListener("readystatechange", function() {

  if (this.readyState === this.DONE) {

    a = this.responseText;

    a = JSON.parse(a);

    console.log(a.suggestion);

    foo.speak(a.suggestion);

  }

});

​

xhr.open("GET", "https://montanaflynn-spellcheck.p.rapidapi.com/check/?text=" + sent);

xhr.setRequestHeader("x-rapidapi-host", "montanaflynn-spellcheck.p.rapidapi.com");

xhr.setRequestHeader("x-rapidapi-key", "64316f0976msh4af7d6244bdf278p11219ejsna08b83584ba5");

​

xhr.send(data);

}

function convert(){

  spell(word);

}

function cls(){

  word='';

}

function back(){

  word=subset(word,0,len--);

}

// </script>