let len = 784;

let catData = [];

let rainbowData = [];

let trainData = [];

let myNN;

let isModelReady = false;

let mySpeech;

​

function preload() {

  catFile = loadBytes("data/cats1000.bin");

  rainbowFile = loadBytes("data/rainbows1000.bin");

  trainFile = loadBytes("data/trains1000.bin");

}

​

function prepareData() {

  for (let i = 0; i < 1000; i++) {

    catData[i] = [];

    rainbowData[i] = [];

    trainData[i] = [];

    for (let j = 0; j < len; j++) {

      const catValue = (catFile.bytes[i*len + j]) / 255;

      const rainbowValue = (rainbowFile.bytes[i*len + j]) / 255;

      const trainValue = (trainFile.bytes[i*len + j]) / 255;

      catData[i].push(catValue);

      rainbowData[i].push(rainbowValue);

      trainData[i].push(trainValue);

    }

  }

  addData();

}

​

function addData() {

  const option = {

    inputs: 784,

    outputs: 3,

    task: 'classification',

    debug: true

  };

  myNN = ml5.neuralNetwork(option);

  for (let i = 0; i < 1000; i++) {

    myNN.addData(catData[i], ['cat']);

    myNN.addData(rainbowData[i], ['rainbow']);

    myNN.addData(trainData[i], ['train']);

  }

  myNN.train({

    epochs: 30,

  }, doneTraining);

}

​

​

function setup() {

  createCanvas(400, 400);

  background(255);

  prepareData();

  stroke(0);

  strokeWeight(30);

  mySpeech = new p5.Speech();

}

​

function draw() {

  if (mouseIsPressed) {

    line(pmouseX, pmouseY, mouseX, mouseY);

  }

}

​

function mouseReleased() {

  if (isModelReady) {

    const myInput = [];

    let c = get();

    c.resize(28, 28);

    c.loadPixels();

    for (let i = 0; i < len; i++) {

      const value = (255 - c.pixels[i * 4]) / 255;

      myInput.push(value);

    }

    myNN.classify(myInput, gotResults);

  }

}

​

function keyPressed() {

  if (keyCode === 32) {

    background(255);

  }

}

​

function gotResults(error, results) {

  // console.log(results);

  mySpeech.speak("I think it is a " + results[0].label);

}

​

function doneTraining() {

  isModelReady = true;

}

​