Klingeln oder Vibration Statistik

  // Global variable to store the classifier

let classifier;

​

// Label

let label = 'listening...';

let confidence;

​

let Vibration = 0;

let Klingeln = 0;

​

let img, img_Vibration, img_Klingeln;

​

// Teachable Machine model URL:

let soundModel = 'https://teachablemachine.withgoogle.com/models/NdztiyQf4/';

​

​

function preload() {

  // Load the model

  classifier = ml5.soundClassifier(soundModel + 'model.json');

  img = loadImage("Handy.png"); // microphone

  img_Vibration = loadImage("VHandy.png"); // clap

  img_Klingeln = loadImage("KHandy.png"); // snap

}

​

function setup() {

  createCanvas(windowWidth, windowHeight);

  // Start classifying

  // The sound model will continuously listen to the microphone

  classifier.classify(gotResult);

}

​

function draw() {

  background(200);

  imageMode(CENTER); 

  let icon_size = 50;

  // start position

  translate(100, height/4);

  // left to right

  for (i=0; i<Klingeln; i++) {

    image(img_Klingeln, i*icon_size, 0, icon_size, icon_size);

  }

  // next row

  translate(0, icon_size*2);

  for (i=0; i<Vibration; i++) {

    image(img_Vibration, i*icon_size, 0, icon_size, icon_size);

  }

  /*

  // colums

  let colums = 5;

  push();

  translate(width/2 - colums*icon_size - icon_size, height/4);

  for (i=1; i<=snap; i++) {

    image(img_snap, ((i-1)%colums)*icon_size, 0, icon_size, icon_size);

    if (i%colums == 0)

      translate(0, icon_size); // next row

  }

  pop();

  push();

  translate(width/2 + icon_size, height/4);

  for (i=1; i<=clap; i++) {

    image(img_clap, ((i-1)%colums)*icon_size, 0, icon_size, icon_size);

    if (i%colums == 0)

      translate(0, icon_size); // next row

  }

  pop();

  */

  //textSize(50);

  //textAlign(CENTER, CENTER);

  //text("Clap: " + clap, width / 2, height / 3);

  //text("Snap: " + snap, 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("Vibration") > -1 && confidence > 0.9) {

    Vibration += 1;

    //print("clap");

    //img = img_clap;

  }

  else if (label.indexOf("Klingeln") > -1 && confidence > 0.9) {

    Klingeln += 1;

    //print("snap");

    //img = img_snap;

  }

}