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// Global variable to store the classifier
let classifier;
// Label
let label = 'listening...';
let confidence;
let Handyvibration = 0;
let Handyklingeln = 0;
// Teachable Machine model URL:
let soundModel = 'https://teachablemachine.withgoogle.com/models/Ri5ZncWMV/';
function preload() {
// Load the model
classifier = ml5.soundClassifier(soundModel + 'model.json');
}
function setup() {
createCanvas(windowWidth, windowHeight);
// Start classifying
// The sound model will continuously listen to the microphone
classifier.classify(gotResult);
}
function draw() {
background(0);
// Draw the label in the canvas
fill(255);
textSize(50);
textAlign(CENTER, CENTER);
text("Handyvibration: " + Handyvibration, width / 2, height / 3);
text("Handyklingeln: " + Handyklingeln, width / 2, height / 2);
}
// The model recognizing a sound will trigger this event
function gotResult(error, results) {
if (error) {
console.error(error);
return;
}
// The results are in an array ordered by confidence.
// console.log(results[0]);
label = results[0].label;
confidence = nf(results[0].confidence, 0, 2);
//print(label + " / " + confidence);
if (label.indexOf("Hnadyvibration") > -1 && confidence > 0.9)
Handyvibration += 1;
else if (label.indexOf("Handyklingeln") > -1 && confidence > 0.9)
Handyklingeln += 1;
}