​

let winLen = 10;

let win = [];

​

function setup() {

  createCanvas(400, 400);

  setTimeout(init, 4000);

  connect_button = createButton("connect arduino");

  connect_button.position(width / 2, height / 1.5);

  connect_button.id("connect");

}

​

function draw() {

  // background(220);

}

​

// More API functionssinit

// https://github.com/googlecreativelab/teachablemachine-community/tree/master/libraries/pose

​

// the link to your model provided by Teachable Machine export panel

const URL = "https://teachablemachine.withgoogle.com/models/WW3TWA2XJ/";

let model, webcam, ctx, labelContainer, maxPredictions;

​

async function init() {

  const modelURL = URL + "model.json";

  const metadataURL = URL + "metadata.json";

​

  // load the model and metadata

  // Refer to tmImage.loadFromFiles() in the API to support files from a file picker

  // Note: the pose library adds a tmPose object to your window (window.tmPose)

  model = await tmPose.load(modelURL, metadataURL);

  maxPredictions = model.getTotalClasses();

​

  // Convenience function to setup a webcam

  const size = 600;

  const flip = true; // whether to flip the webcam

  webcam = new tmPose.Webcam(size, size, flip); // width, height, flip

  await webcam.setup(); // request access to the webcam

  await webcam.play();

  window.requestAnimationFrame(camera_loop);

​

  // append/get elements to the DOM

  const canvas = document.getElementById("defaultCanvas0");

  canvas.width = size;

  canvas.height = size;

  ctx = canvas.getContext("2d");

  labelContainer = document.getElementById("label-container");

  for (let i = 0; i < maxPredictions; i++) {

    // and class labels

    labelContainer.appendChild(document.createElement("div"));

  }

}

​

async function camera_loop(timestamp) {

  webcam.update(); // update the webcam frame

  await predict();

  window.requestAnimationFrame(camera_loop);

}

​

function sendToArduino(prediction) {

  console.log('actually sent something');

    //create array for sending data to arduino

  let data_to_send = new Uint8Array(1);

  //get the value to send to arduino

  //getSmoothedPrediction will return a number between 0 - 1

  let value_to_send = getSmoothedPrediction(prediction[0].probability);

​

  //send data if the arduino is connected

  if (port != undefined) {

    if (value_to_send > 0.5) {

      data_to_send[0] = 0;

      port.send(data_to_send);

      console.log('sending 0')

    } else {

      data_to_send[0] = 1;

      port.send(data_to_send);

      console.log('sending 1')

    }

  }

}

​

​

​

function debounce(func, timeout = 300){

  let timer;

  return (...args) => {

    console.log('tried to send something')

    clearTimeout(timer);

    timer = setTimeout(() => { func.apply(this, args); }, timeout);

  };

}

​

const sendToArduinoDebounced = debounce(sendToArduino, 1000);

​

async function predict() {

  // Prediction #1: run input through posenet

  // estimatePose can take in an image, video or canvas html element

  const { pose, posenetOutput } = await model.estimatePose(webcam.canvas);

  // Prediction 2: run input through teachable machine classification model

  const prediction = await model.predict(posenetOutput);

​

  for (let i = 0; i < maxPredictions; i++) {

    const classPrediction =

      prediction[i].className + ": " + prediction[i].probability.toFixed(2);

    labelContainer.childNodes[i].innerHTML = classPrediction;

  }

​

  // finally draw the poses

  drawPose(pose);

  sendToArduinoDebounced(prediction);

  // console.log(prediction[0]);

​

  //console log the predictions

  // prediction.forEach((cls) => console.log(cls.className, cls.probability))

​

}

​

​

​

​

​

function getSmoothedPrediction(pred) {

  win.push(pred);

  if (win.length > winLen) {

    win.shift();

  }

  let avg = 0;

  win.forEach((p) => (avg += p));

  return avg / win.length;

}

​

function drawPose(pose) {

  if (webcam.canvas) {

    ctx.drawImage(

      webcam.canvas,

      0,

      0,

      webcam.canvas.width,

      webcam.canvas.height,

      0,

      0,

      width,

      height

    );

    // draw the keypoints and skeleton

    if (pose) {

      const minPartConfidence = 0.5;

      tmPose.drawKeypoints(pose.keypoints, minPartConfidence, ctx);

      tmPose.drawSkeleton(pose.keypoints, minPartConfidence, ctx);

    }

  }

}

​