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                <input type="range" min="1" max="6" value="1" step="1" />
<section>
  <p>Manually create an SVG path over the original illustration</p>
  <p>Draw dots along the paths with a different delay for each one</p>
  <p>Use two gradients to assign a color on each dot</p>
  <p>Make the radii of the dots vary to make the result less flat</p>
  <p>Translate the dots during the animation and use an elastic easing</p>
  <p>Render more dots to simulate continuous lines</p>
</section>
<canvas></canvas>
<svg viewBox="0 0 400 488">
  <path d="m 376.3299,351.06186 c 4.45361,47.0103 -51.46392,124.20619 -127.17526,105.40206 -75.71134,-18.80413 9.89692,-176.65979 69.7732,-140.53608 59.87628,36.12371 -80.02665,144.51868 -165.7732,140.53608 -51.44793,-2.38956 -95.0103,-28.70103 -80.65979,-101.4433 14.35051,-72.74227 207.83505,-255.3402 264.24742,-194.96907 56.41237,60.37113 -171.71134,177.15461 -229.60825,173.6907 -57.89691,-3.46391 -114.55671,-62.35051 -65.31959,-137.567 49.23712,-75.21649 131.76348,-45.721 131.76348,-45.721" fill="none" stroke="#00ff00" stroke-linecap="round" stroke-width="2" />
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</svg>
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" alt="">
              
            
!

CSS

              
                svg {
  width: 70vmin;
  position: absolute;
  left: 50%;
  top: 48%;
  transform: translate(-50%, -50%);
  transition: 0.15s ease-out;
  z-index: 1;
  path {
    opacity: 0;
  }
}
img {
  width: 70vmin;
  position: absolute;
  left: 50%;
  top: 48%;
  transform: translate(-50%, -50%);
  opacity: 0;
}
body {
  height: 100vh;
  overflow: hidden;
  font-family: 'Yanone Kaffeesatz', sans-serif;
}
canvas {
  position: absolute;
  left: 50%;
  top: 48%;
  transform: translate(-50%, -50%);
}


@mixin track {
  box-sizing: border-box;
  height: 6px;
	background: #000;
  -webkit-appearance: none;
  appearance: none;
}

@mixin thumb {
  box-sizing: border-box;
	width: 30px;
  height: 30px;
	border-radius: 50%;
	background: #000;
  border: 2px solid white;
  -webkit-appearance: none;
  appearance: none;
  cursor: grab;
}

input {
  position: fixed;
  left: 50%;
  bottom: 20px;
  transform: translateX(-50%);
  width: 80%;
  height: 34px;
  max-width: 400px;
  background: transparent;
  -webkit-appearance: none;
  appearance: none;
  z-index: 10;
  &:active {
    cursor: grabbing;
  }
  &::-webkit-slider-runnable-track {@include track }
	&::-moz-range-track { @include track }
	&::-ms-track { @include track }
  
  &::-webkit-slider-thumb {margin-top: -12px;@include thumb}
	&::-moz-range-thumb { @include thumb }
  &::-ms-thumb {margin-top:0px;@include thumb}
}

section {
  box-sizing: border-box;
  font-size: 40px;
  position: fixed;
  left: 0;
  top: 20px;
  width: 100%;
  text-align: center;
  padding: 10px 10%;
  z-index: 10;
  pointer-events: none;
  text-shadow: 0 0 3px white, 0 0 4px white, 0 0 5px white;
  background: rgba(255, 255, 255, 0.7);
  p {
    margin: 0;
    display: none;
  }
  @media (max-width: 500px) {
    font-size: 24px;
  }
}
              
            
!

JS

              
                console.clear();

/* Fetch all the dom elements in the page */
const canvas = document.querySelector('canvas');
const svg = document.querySelector('svg');
const paths = svg.querySelectorAll('path');
const ctx = canvas.getContext('2d');
let width = 0;
let height = 0;
let step = parseInt(document.querySelector('input').value);
const texts = document.querySelectorAll('section p');

/* Define the two gradients we need for the paths */
const gradients = [
  [
    [0, [118, 179, 236]],
    [10, [41, 102, 193]],
    [20, [129, 77, 185]],
    [30, [129, 77, 185]],
    [50, [250, 148, 170]],
    [60, [237, 70, 54]],
    [70, [253, 134, 100]],
    [80, [254, 156, 33]],
    [90, [250, 213, 0]],
    [100, [171, 211, 96]]
  ],
  [
    [0, [1, 123, 147]],
    [100, [131, 201, 167]]
  ]
];

const dots = []; // Array to store all dots
class Dot {
  constructor (x, y, color, delay, index) {
    this._x = x; // origin X coordinate of the dot
    this._y = y; // origin Y coordinate of the dot
    this.x = x; // Y coordinate of the dot
    this.y = y; // Y coordinate of the dot
    this.r = 0; // Radius of the dot
    this.index = index; // Index of the dot along the path
    this.color = color; // RGB color of the dot
    this.delay = (delay * 0.9); // Delay for the animation
    this.tl = null; // GSAP tween
  }
  tween () {
    // Kill the previous tween to avoid ovrlapping animations
    if (this.tl) this.tl.kill();
    
    /// Create a new GSAP animation for the dot
    this.tl = gsap.fromTo(this, {
      r: 0,
      // Add translation animation from step 5
      x: () => step > 4 ? this._x - 0.05 : this._x,
      y: () => step > 4 ? this._y - 0.05 : this._y
    }, {
      x: this._x,
      y: this._y,
      r: () => {
        if (step < 4) {
          // Until step 4, draw only 1 of 20 dots
          return this.index % 20 === 0 ? width * 0.03 : 0;
        } else if (step < 6) {
          // From step 4, draw only 1 of 20 dots with custom radius
          return this.index % 20 === 0 ? width * 0.03 + (Math.abs(Math.sin(this.delay * 3.4 - 1.5)) * width * 0.02) : 0;
        } else {
          // On step 6, draw every dot with custom radius
          return width * 0.03 + (Math.abs(Math.sin(this.delay * 3.4 - 1.5)) * width * 0.02);
        }
      },
      duration: 1.8,
      ease: 'elastic.out(1, 0.5)',
      delay: () => {
        if (step === 1) {
          return 0;
        } else {
          return (step > 1 && step < 5) ? this.delay * 4 : this.delay;
        }
      }
    });
    
  }
  draw () {
    /* On step 1, we don't need to render the dots*/
    if (step === 1) return;
    
    /* Once step 3 reached, draw dots with color */
    if (step > 2) {
      ctx.fillStyle = this.color;
    } else {
      /* Else, draw them black */
      ctx.fillStyle = 'black';
    }
    
    /* Draw a circle on the canvas */
    ctx.beginPath();
    ctx.arc(this.x * width, this.y * height, this.r, 0, 2 * Math.PI);
    ctx.fill();
  }
}

function init () {
  // Calculate the total length of both paths
  const totalLength = [...paths].reduce((p) => p.getTotalLength());
  // The sum_length variable helps us knowing at what distance the dot will be from the first dot along both paths
  let sum_length = 0;
  
  // Loop through both paths
  paths.forEach((path, pathIndex) => {
    // Get the path length
    const length = path.getTotalLength();
    // Loop through that path length with a new dot every two pixels
    for (let i = 0; i < length; i+=2) {
      // Get the coordinates of the point along the path
      const point = path.getPointAtLength(i);
      // Divide the coordinates by the viewbox width/height to get a normalized value
      const x = point.x / 400;
      const y = point.y / 488;
      // Get the color of the dot from the gradient algorithm
      const RGB_color = getColor(pathIndex, length, i / length);
      const color = `rgb(${RGB_color[0]}, ${RGB_color[1]}, ${RGB_color[2]})`;
  
      // Create a new dot from all the data above
      const dot = new Dot(x, y, color, (1.5 - (sum_length / totalLength)), i);
      dots.push(dot);
      
      // Increment the sum_length
      sum_length += 2;
    }
  });
}

/* Start gradient code */
/* Code from https://stackoverflow.com/a/30144587 */
function pickHex(color1, color2, weight) {
  var p = weight;
  var w = p * 2 - 1;
  var w1 = (w/1+1) / 2;
  var w2 = 1 - w1;
  var rgb = [Math.round(color1[0] * w1 + color2[0] * w2),
      Math.round(color1[1] * w1 + color2[1] * w2),
      Math.round(color1[2] * w1 + color2[2] * w2)];
  return rgb;
}
function getColor(pathIndex, pathLength, colorIndex) {
  var colorRange = [];
  let stop = false;
  const gradient = gradients[pathIndex];
  gradient.forEach((step, index) => {
    if (!stop && (colorIndex * 100) <= step[0]) {
      if (index === 0) {
        index = 1;
      }
      colorRange = [index - 1, index];
      stop = true;
    }
  });

  //Get the two closest colors
  var firstcolor = gradient[colorRange[0]][1];
  var secondcolor = gradient[colorRange[1]][1];
  //Calculate ratio between the two closest colors
  var firstcolor_x = pathLength * (gradient[colorRange[0]][0]/100);
  var secondcolor_x = pathLength * (gradient[colorRange[1]][0]/100)-firstcolor_x;
  var slider_x = pathLength * colorIndex - firstcolor_x;
  var ratio = slider_x / secondcolor_x;

  //Get the color with pickHex(thx, less.js's mix function!)
  return pickHex(secondcolor, firstcolor, ratio);
}
/* End gradient code */


function render () {
  requestAnimationFrame(render);
  // Clear the canvas
  ctx.clearRect(0, 0, width, height);
  
  // Render every dot
  dots.forEach(dot => {
    dot.draw();
  });
}

/* Listen to resize event on the window */
window.addEventListener('resize', onResize);
function onResize () {
  // Get the SVG width & height
  width = svg.clientWidth;
  height = svg.clientHeight;

  // Apply the nw dimensions to the canvas
  canvas.width = width;
  canvas.height = height;
  
  // Restart everything
  onUpdate();
}

/* Listen when user is updating the input */
document.querySelector('input').addEventListener('input', (e) => {
  // Get the value of the step
  step = parseInt(e.target.value);
  // Restart everything
  onUpdate();
});

function onUpdate () {
  texts.forEach(text => text.style.display = 'none');
  texts[step - 1].style.display = 'block';
  
  if (step === 1) {
    /* STEP 1 */
    /* Play the SVG animation of the paths */
    gsap.set('path', {
      opacity: 1,
      overwrite: true,
      strokeDasharray: (a, b) => {
        return b.getTotalLength();
      },
      strokeDashoffset: (a, b) => {
        return b.getTotalLength() * 3;
      },
    });
    gsap.to('path', {
      strokeDashoffset: (a, b) => {
        return b.getTotalLength() * 4;
      },
      delay: (a) => Math.abs(a - 1) * 3,
      duration: 2,
      ease: 'power2.inOut'
    });
    gsap.to('img', {
      opacity: 0.6,
      duration: 0.2
    });
  } else if (step < 4) {
    /* STEPS 2-3 */
    /* Show the SVG paths but hide the image */
    gsap.to('path', {
      opacity: 1,
      strokeDashoffset: (a, b) => {
        return b.getTotalLength() * 4;
      },
      overwrite: true
    });
    gsap.to('img', {
      opacity: 0,
      duration: 0.2
    });
  } else {
    /* STEPS 4-5-6 */
    /* Hide the SVG paths and the image */
    gsap.to([paths, 'img'], {
      opacity: 0,
      duration: 0.2
    });
  }
  
  /* Restart the animation of each dot */
  dots.forEach(dot => {
    dot.tween();
  });
}


init();
onResize();
requestAnimationFrame(render);

              
            
!
999px

Console