let img;

let c;

​

function setup() {

  c = createCanvas(400, 400);

  background(0);

  // c.drop(gotFile);

  classifier = ml5.imageClassifier('MobileNet', modelReady);

  img = new Image();

  img.crossOrigin = "Anonymous";

  img.src = 'rat.jpg';

  document.body.appendChild(img);

    classifier.predict(img, processResults);

}

​

function draw() {

}

​

function modelReady() {

    print('Model is ready!'); 

}

​

function processResults(err, results) {

  if (err) { 

    console.error(err)

  } else {

    print(results);

    createP(results[0].className);

  }

}

​

function gotFile(file) {

  // If it's an image file

  if (file.type === 'image') {

    removeElements();

    // Create an image DOM element but don't show it

    // let img = createImg(file.data).hide();

    let img = createImg(file.data, '', function() {

      img.hide();

      background(255);

      if (img.width > img.height) {

        image(img, 0, 0, width, img.height * width / img.width);

      } else {

        image(img, 0, 0, img.width * height / img.height, height);

      }

      classifier.predict(img, processResults);

      // img.style('display', 'none');

    });

    // Draw the image onto the canvas

  } else {

    println('Not an image file!');

  }

}