Webcam face detection in the browser

Important: Please make sure to allow access to your webcam for this page to work. No video data will be recorded or uploaded.

Note: For mobile phones, please turn them sideways into landscape format to get better results. This demo is optimized for desktop browsers.

This demo is pretty amazing. With just a few lines of code, you can enable your webcam and start doing face detection. The program will recognize your face and then display it on the screen. This is a great demonstration of how easy it is to get started with face recognition.

The source code

Here’s all the code it took to make this happen (credit):

<div style="text-align:center">
<video id="video" autoplay style="display:none"></video>
<canvas id="canvas" width="300px" height="200px" style="margin:0 auto"></canvas>
</div>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/blazeface"></script>
<script>
let video = document.getElementById("video");
let model;
// declare a canvas variable and get its context
let canvas = document.getElementById("canvas");
let ctx = canvas.getContext("2d");

const setupCamera = () => {
  navigator.mediaDevices
    .getUserMedia({
      video: { width: 300, height: 200 },
      audio: false,
    })
    .then((stream) => {
      video.srcObject = stream;
    });
};

let shown = false;
  
const detectFaces = async () => {
  const prediction = await model.estimateFaces(video, false);

  if (shown == false) {
    // log the prediction once to the browser console
    console.log(prediction);
    shown = true;
  }

  // draw the video first
  ctx.drawImage(video, 0, 0, 300, 200);

  prediction.forEach((pred) => {
    
    // draw the rectangle enclosing the face
    ctx.beginPath();
    ctx.lineWidth = "5";
    ctx.strokeStyle = "white";
    // the last two arguments are width and height
    // since blazeface returned only the coordinates, 
    // we can find the width and height by subtracting them.
    ctx.rect(
      pred.topLeft[0],
      pred.topLeft[1],
      pred.bottomRight[0] - pred.topLeft[0],
      pred.bottomRight[1] - pred.topLeft[1]
    );
    ctx.stroke();
    
    // drawing small rectangles for the face landmarks
    ctx.fillStyle = "white";
    pred.landmarks.forEach((landmark) => {
      ctx.fillRect(landmark[0], landmark[1], 5, 5);
    });   
  });
};

setupCamera();
video.addEventListener("loadeddata", async () => {
  model = await blazeface.load();
  // call detect faces every 100 milliseconds or 10 times every second
  setInterval(detectFaces, 500);
});
</script>

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