//

// This software is released under the MIT License.

// https://opensource.org/licenses/MIT

​

​

​

// The classifier will use our model to try and classify

// the video image

let classifier;

​

// Model URL

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

​

// Video

let video;

​

// To store the classification

let label = "";

​

// And the confidence of that classification

let confidence = 0;

​

// The confidence threshhold determines how strict we'll be with classifying an image, from 0 to 1.

let threshold = 0.8;

​

// Load the model first

function preload() {

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

}

​

function setup() {

  createCanvas(400, 400);

  // Create the video

  video = createCapture(VIDEO);

  video.size(400, 400);

  video.hide();

​

  // Start classifying

  classifyVideo();

}

​

function draw() {

  background(255);

  // Uncomment below to see your video input

  //image(video, 0, 0);

  if (confidence > threshold) {

    if (label == "apple") {

      stroke("brown");

      strokeWeight(5);

      line(200, 100, 210, 80);

      noStroke();

      fill("red");

      ellipse(200, 200, 200, 200);

    } else if (label == "lemon") {

      noStroke();

      fill("yellow");

      ellipse(200, 200, 150, 200);

    } else if (label == "lime") {

      noStroke();

      fill("lime");

      ellipse(200, 200, 175, 150);

    }

    noStroke();

    fill(0);

    textSize(16);

    textAlign(CENTER);

    text(label, width / 2, height - 4);

  } else {

    noStroke();

    fill(0);

    textSize(25);

    textAlign(CENTER);

    text("I'm not sure what that is.\nTry holding up an apple,\nlemon, or lime.", width / 2, height / 2);

  }

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  classifier.classify(video, 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;

  confidence = results[0].confidence;

  // Classifiy again!

  classifyVideo();

}