// Coding Challenge

// The Coding Train / Daniel Shiffman

// https://thecodingtrain.com/CodingChallenges/158-shape-classifier.html

// https://youtu.be/3MqJzMvHE3E

​

// Generate Dataset: 

// https://github.com/CodingTrain/website/tree/gh-pages/CodingChallenges/CC_158_Shape_Classifier/dataset

// Generate Dataset (port): https://editor.p5js.org/codingtrain/sketches/7leVIzy5l

// Training: https://github.com/CodingTrain/website/tree/gh-pages/CodingChallenges/CC_158_Shape_Classifier/training

// Mouse:  https://editor.p5js.org/codingtrain/sketches/JgLVfCS4E

// Webcam: https://editor.p5js.org/codingtrain/sketches/2hZGBkqqq

​

//let circles = [];

//let squares = [];

//let triangles = [];

let bign =[];

let ch =[];

let ll =[];

let rr =[]

let n = []

​

function preload() {

  for (let i = 0; i < 50; i++) {

    //let index = nf(i + 1, 4, 0);

    let dan = i + 1

    //circles[i]   = loadImage(`data/circle${index}.png`);

    //squares[i]   = loadImage(`data/square${index}.png`);

    //triangles[i] = loadImage(`data/triangle${index}.png`);

    bign[i]        = loadImage(`spanish/bign-${dan}.png`);

    ch[i]          = loadImage(`spanish/ch-${dan}.png`);

    //ll[i]          = loadImage(`spanish/ll-${dan}.png`);

    //rr[i]          = loadImage(`spanish/rr-${dan}.png`);

    //n[i]           = loadImage(`spanish/n-${dan}.png`);

  }

}

​

let shapeClassifier;

let trained_epochs = 0;

​

function setup() {

  createCanvas(200, 200);

  background(200);

  //image(squares[0], 0, 0, width, height);

​

  let options = {

    inputs: [128, 128, 4],

    task: 'imageClassification',

    debug: true

  };

  shapeClassifier = ml5.neuralNetwork(options);

​

  for (let i = 0; i < bign.length; i++) {

    //shapeClassifier.addData({ image: circles[i] }, { label: 'circle' });

    //shapeClassifier.addData({ image: squares[i] }, { label: 'square' });

    //shapeClassifier.addData({ image: triangles[i] }, { label: 'triangle' });

    shapeClassifier.addData({ image: bign[i] }, { label: 'bign' });

    shapeClassifier.addData({ image: ch[i] }, { label: 'ch' });

    //shapeClassifier.addData({ image: bign[i] }, { label: 'bign' });

    //shapeClassifier.addData({ image: ch[i] }, { label: 'ch' });

    //shapeClassifier.addData({ image: ch[i] }, { label: 'ch' });

  }

  shapeClassifier.normalizeData();

  trained_epochs = 50;

  shapeClassifier.train({ epochs: 50 }, finishedTraining);

  console.log('Click into Preview and press S for saving of the model.')

  console.log('Press C to continue training.')

}

​

function finishedTraining() {

  console.log('Finished training! Epochs:', trained_epochs);

  // shapeClassifier.save();

}

​

function keyPressed() {

  if (key == 's') {

    shapeClassifier.save();

  } else if (key == 'c') {

    trained_epochs += 50;

    shapeClassifier.train({ epochs: 50 }, finishedTraining);

  }

}