let targetLabel = "C";

//let trainingData = [];

function setup() {

  createCanvas(400, 400);

  let options = {

    inputs: ["x", "y"],

    outputs: ["label"],

    task: "classification",

    debug: "true"

  };

  model = ml5.neuralNetwork(options);

  background(255);

}

function keyPressed() {

  if (key == "t") {

    model.normalizeData();

    let options = {

      epochs: 100

    };

    model.train(options, whileTraining, finishedTraining);

  }

  targetLabel = key.toUpperCase();

}

function whileTraining() {

  console.log(epoch);

}

​

function finishedTraining() {

  console.log("Done Training");

}

function mousePressed() {

  let inputs = {

    x: mouseX,

    y: mouseY

  };

  let target = {

    label: targetLabel

  };

  model.addData(inputs, target);

  stroke(0);

  noFill();

  circle(mouseX, mouseY, 24);

  fill(0);

  noStroke();

  textAlign(CENTER, CENTER);

  text(targetLabel, mouseX, mouseY);

}

​