* 👋 Hello! This is an ml5.js example made and shared with ❤️.

 * Learn more about the ml5.js project: https://ml5js.org/

 * ml5.js license and Code of Conduct: https://github.com/ml5js/ml5-next-gen/blob/main/LICENSE.md

 *

 * This example demonstrates drawing skeletons on poses for the MoveNet model.

 */

​

let textResponse = "like a sparrow in the rain";

let textResponseArr = ["like","a","sparrow","in","the","rain"];

let prevPoses = [];

let videoScale = 1;

let textOffset = 0;

​

let video;

let bodyPose;

let poses = [];

let connections;

​

function preload() {

  // Load the bodyPose model

  bodyPose = ml5.bodyPose();

}

​

function setup() {

  let aspect = 640/480;

  createCanvas(windowWidth, windowWidth/aspect);

​

  // Create the video and hide it

  video = createCapture(VIDEO);

  video.size(640, 480);

  video.hide();

  background(0);

  // set angles to degrees

  angleMode(DEGREES)

​

  // Start detecting poses in the webcam video

  bodyPose.detectStart(video, gotPoses);

  // Get the skeleton connection information

  connections = bodyPose.getSkeleton();

}

​

function draw() {

  // if (frameCount % 50 == 0) textOffset += 1;

  // Draw the webcam video

  // image(video, 0, 0, width, height);

​

  background(0,0,0,10);

  // Draw the skeleton connections

  for (let i = 0; i < poses.length; i++) {

    let pose = poses[i];

    for (let j = 0; j < connections.length; j++) {

      let pointAIndex = connections[j][0];

      let pointBIndex = connections[j][1];

      let pointA = pose.keypoints[pointAIndex];

      let pointB = pose.keypoints[pointBIndex];

      // Only draw a line if both points are confident enough

      if (pointA.confidence > 0.1 && pointB.confidence > 0.1) {

        stroke(255, 255, 255);

        strokeWeight(2);

        // line(pointA.x, pointA.y, pointB.x, pointB.y);

      }

    }

  }

​

  // Draw all the tracked landmark points

  for (let i = 0; i < poses.length; i++) {

    let pose = poses[i];

    let prevPose = prevPoses[i]

    for (let j = 0; j < pose.keypoints.length; j++) {

      if (prevPoses.length){

      let keypoint = pose.keypoints[j];

        let prevKeypoint = prevPose.keypoints[j]

      // Only draw a circle if the keypoint's confidence is bigger than 0.1

      if (keypoint.confidence > 0.1) {

        fill(sin(frameCount / 100) * 255, 255, 255);

        strokeWeight(2);

​

        // circle(keypoint.x, keypoint.y, 10);

        // line(keypoint.x, keypoint.y, prevKeypoint.x, prevKeypoint.y);

        noStroke();

        textSize(18)

        let v1 = createVector(prevKeypoint.x - keypoint.x,prevKeypoint.y - keypoint.y);

        let distanceToPreviousKeypoint = v1.mag();

        // let v2 = createVector(keypoint.x,keypoint.y);

        // let angle = v1.angleBetween(v2)

        let angle = v1.heading();

        console.log(distanceToPreviousKeypoint);

        push();

        translate(keypoint.x, keypoint.y);

        // rotate(angle);

        let oneWord = textResponseArr[(j + textOffset) % textResponseArr.length]

        let phrasePart = textResponseArr.slice((j + textOffset) % textResponseArr.length,(j + textOffset) % textResponseArr.length+3)

        let phrasePartWithSpaces = "";

        phrasePart.forEach(word => {

          phrasePartWithSpaces += word + " "

        })

        if (distanceToPreviousKeypoint > 10){

        text(oneWord, 0,0)

          }

​

        pop();

      }

        }

    }

    prevPoses = poses;

  }

}

​

// Callback function for when bodyPose outputs data

function gotPoses(results) {

  // Save the output to the poses variable

  poses = results;

}

​