let amplitude;

let ampMin = 0;

let ampMax = 0.05;

​

// Sound classification variables

let classifier;

let predictedSound = "listening";

let confidence = 0;

let confidenceThreshold = 0.5;

​

// Teachable Machine model URL - Replace with your model here:

let soundModelURL = "https://teachablemachine.withgoogle.com/models/qH19IouyB/";

​

// Visuals variables

let x, y;

let s = 5;

let speed = 3;

let colorPalette = ["#0794cd", "#fd40a9", "#35d528", "#fee712", "#ffac49", "#ff6f7d"];

let currentColor = colorPalette[4];

​

// Map sound labels to specific colors

// Adjust these keys to match the labels provided by your model.

let soundColorMap = {

  "Clap": "#0794cd",

  "Voice": "#fd40a9",

  "Knocking": "#35d528",

  "Ukulele": "#fee712",

  "Background Noise": "#ffac49",

};

​

function preload() {

  // Load the sound classifier model

  classifier = ml5.soundClassifier(soundModelURL);

}

​

function setup() {

  createCanvas(600, 400);

  mic = new p5.AudioIn();

  mic.start();

  classifier.classifyStart(gotResult);

  x = width / 2;

  y = height / 2;

  background(50);

}

​

function draw() {

  // Get the current amplitude level

  amplitude = mic.getLevel();

  // Map amplitude to speed and size (clamped)

  speed = map(amplitude, ampMin, ampMax, 5, 20, true);

  s = map(amplitude, ampMin, ampMax, 5, 30);

  let transColor = color(currentColor);

  transColor.setAlpha(50); 

  stroke(currentColor);

  fill(transColor);

  // Store the previous position

  let prevX = x;

  let prevY = y;

  // Update position with boundary checks

  if (x < 0) {

    x += 100; 

  } else if (x > width) {

    x -= 100;

  } else if (y < 0) {

    y += 100;

  } else if (y > height) {

    y -= 100;

  } else {

    x += random(-speed, speed);

    y += random(-speed, speed);

  }

  // If the classified sound is "Background Noise", draw a line; otherwise draw a circle.

  if (predictedSound === "Background Noise" || predictedSound === "listening") {

    line(prevX, prevY, x, y);

  } else {

    circle(x, y, s);

  }

  print(predictedSound);

}

​

function gotResult(results) {

  if (results.length > 0) {

    let newConfidence = results[0].confidence;

    let newSound = results[0].label;

    // Only update if confidence exceeds the threshold and the sound has changed

    if (newConfidence > confidenceThreshold && newSound !== predictedSound) {

      predictedSound = newSound;

      confidence = newConfidence;

      // Update currentColor using the mapping. If the sound is not in the mapping, use a default color.

      if (soundColorMap.hasOwnProperty(predictedSound)) {

        currentColor = soundColorMap[predictedSound];

      } else {

        currentColor = colorPalette[0];

      }

    }

  }

}

​

function mousePressed() {

  save("workshop.png");

}

​