ml5+TeachableMachine-2024

// Uses: https://unpkg.com/ml5@1/dist/ml5.js

​

// Model URL, obtained from Teachable Machine. 

let imageModelURL = 'https://teachablemachine.withgoogle.com/models/3Z2oOfxPq/';

    ///'https://teachablemachine.withgoogle.com/models/GEEZvxKqB/'

    //

​

// Classifier Variable

let classifier;

// Video

let video;

// To store the current classification

let currentCategoryLabel = "";

​

//--------------------------------------------------

// Load the model first

function preload() {

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

}

​

//--------------------------------------------------

function setup() {

  createCanvas(320, 260);

  // Create the webcam video 

  video = createCapture(VIDEO);

  video.size(320, 240);

  video.hide();

​

  // Start classifying

  classifyVideo();

}

​

//--------------------------------------------------

function draw() {

  background('white');

  // Draw the webcam video

  image(video, 0,0);

  // Display the categorization label (if any)

  fill('red');

  textSize(16);

  textAlign(CENTER);

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

}

​

//--------------------------------------------------

// Get a prediction for the current video frame

function classifyVideo() {

  classifier.classify(video, gotResult);

}

​

// What to do when the classifier returns a result.

// Note that the order of the arguments (results, error)

// has been swapped since earlier versions of ml5!

function gotResult(results, error) {

  // If there is an error

  if (error) {

    console.error(error);

    return;

  }

  // The results are stored in an array ordered by confidence.

  // console.log(results[0]);

  currentCategoryLabel = results[0].label;

  // Now, trigger classify to happen again!

  classifyVideo();

}