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Face Detection Using Shape Detection API

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Face Detection Using Shape Detection API

The Shape Detection API is currently in Chrome Canary and can detect both faces and barcodes.

· Web Dev Zone
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I was at the party of the Chrome Dev Summit and Miguel Casa-Sanchez on the Chrome team came up to me and said, “Hey Paul, I have a demo for you”. Once I saw it, I had to get it into my talk.

That API was the Shape Detection API that is currently in the WICG in an incubation and experimentation phase and is a nice incremental addition to the platform.

The Shape Detection API is interesting because it creates a standard interface on top of some underlaying hardware features on the user’s device and opens up a new set of capabilities to the web platform.

Shape Detection has been possible on the web for a long time. There are numerous libraries that have been able to do Edge Detection, Face Detection, barcode and QR code detection (I even wrote a web app that has done it.)

The Shape Detection API is currently in Chrome Canary (M57) and can detect both faces and barcodes (and QRCodes) and because it is still experimental you have to enable it via chrome://flags/#enable-experimental-web-platform-features

The API is relatively simple to use, with the simplest form of face detection being to invoke the API with an image and get the list of faces back.

var faceDetector = new FaceDetector();
faceDetector.detect(image)
  .then(faces => faces.forEach(face => console.log(face)))
  .catch(e => {
    console.error("Boo, Face Detection failed: " + e);
  });

It takes an image object (either a CanvasImageSource, Blob, ImageData or an <img> element) and then passes that to the underlying system API and it will return an array of DetectedFace objects that implement DetectedObject which essentially gives you the bounds of each face in the image.

Miguel wrote a fuller demo (which I stole and put on JSBin) that loads an image, passes it through the detection API and then draws on the image a rectangle around each of the DetectedFace faces.

var image = document.getElementById('image');
var canvas = document.getElementById('canvas');

var ctx = canvas.getContext('2d');
var scale = 1;

image.onload = function() {
  ctx.drawImage(image,
              0, 0, image.width, image.height,
              0, 0, canvas.width, canvas.height);

  scale = canvas.width / image.width;
};

function detect() {
  if (window.FaceDetector == undefined) {
    console.error('Face Detection not supported');
    return;
  }

  var faceDetector = new FaceDetector();
  faceDetector.detect(image)
    .then(faces => {
      // Draw the faces on the <canvas>.
      var ctx = canvas.getContext('2d');
      ctx.lineWidth = 2;
      ctx.strokeStyle = 'red';
      for(let face of faces) {
        ctx.rect(Math.floor(face.x * scale),
                 Math.floor(face.y * scale),
                 Math.floor(face.width * scale),
                 Math.floor(face.height * scale));
        ctx.stroke();
      }
    })
    .catch((e) => {
      console.error("Boo, Face Detection failed: " + e);
    });
}

What Does This Enable?

There are quite a few different use-cases that are opened up a little more with the FaceDetection API, for example, you could:

  • Vastly more peformant experiences when detecting faces — we have a lot of flexibility with this API as it allows us to move the processing into a Service or Web Worker.
  • Profile picture cropping — find your face in the picture and automatically crop the image so that
  • Enable quick tagging — quickly find all the faces in a scene and create a UI that enables you to quickly tag them.
  • Optimizing facial recognition — once you have the image of the face you can then pass just those regions to your Facial Recognition tools.

Are these all possible today in the browser? Yes, but you need to plan for progressive use ahead of time.

Planning for Progressive-ness.

This is obviously a pure JS API that requires access to the underlying hardware APIs, but this can “easily” (heh) be built to be fully progressive and ensuring that users who don’t use the latest version of Chrome are still able to access your experience.

My thoughts around this follow a relatively standard approach to progressive enhancement: Server → JS (+ Web ASM maybe) → Web API but I thought I would explore this a little bit further as I do see a number of challenges.

Server

We can create a simple form that has an <input type="file"> that uploads an image to your server and you do your image detection on the server and return the results to the client.

JS

If we have JS enabled we have the ability to do facial detection inside the browser and directly in the context of the page using any one of a number of client libraries.

The Web Assembly aside:

It is incredibly hard (at least in my opinion) to do image processing and even harder to do object detection especially in a performant way. “Native platforms” have long had many libraries (Open CV for example) that are primarily written in C which can now be brought to the browser and take advantage of the rich eco-system and also be in the same order of magnitude of performance.

It would be incredibly useful if someone made a polyfil for this ShapeDetection API.

Web API

Now that we can get ubiquity across all platforms it is possible to utilize the underlying system API when it is available.

I think this is an interesting API to bring to the platform and it certainly opens up a range of possibilities, specifically for me this is about vastly increasing the performance of object detection on the web by using the underlying system as opposed to pure javascript and this is why I am looking forward to the barcode detection API as it will greatly increase the performance of my QR Scanner Web app whilst at the same time reducing the complexity of the application.

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Topics:
image ,detection ,var ,web dev

Published at DZone with permission of Paul Kinlan, DZone MVB. See the original article here.

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