M.3 Detect Faces

Face Detection

With ML Kit's face detection API, you can detect faces in an image, identify key facial features, and get the contours of detected faces.

With face detection, you can get the information you need to perform tasks like embellishing selfies and portraits, or generating avatars from a user's photo. Because ML Kit can perform face detection in real time, you can use it in applications like video chat or games that respond to the player's expressions.

NOTICE: This is a beta release of ML Kit for Firebase. This API might be changed in backward-incompatible ways and is not subject to any SLA or deprecation policy.

Create a VisionImage first:

import com.myflashlab.air.extensions.firebase.mlkit.*;

// initialize ML Kit AFTER FirebaseCore is successfully started
Mlkit.init();

/*
    You can create VisionImage instance from BitmapData, File or ByteArray

    Mlkit.createVisionImageFromBitmapData
    Mlkit.createVisionImageFromFile
    Mlkit.createVisionImageFromBytes
*/

var image:File = File.applicationDirectory.resolvePath("img.jpg");

// This is beta version and for some reason, creating vision 
// images from file is not working! instead you may use 
// BitmapData for now!

var loader:Loader = new Loader();
loader.load(new URLRequest(image.url));
loader.contentLoaderInfo.addEventListener(Event.COMPLETE, function loaderComplete(e:Event):void
{
	var bm:Bitmap = e.target.content as Bitmap;

	// create a VisionImage
	var visionImg:VisionImage = Mlkit.createVisionImageFromBitmapData(bm.bitmapData);
				
	trace("visionImg.id = " + visionImg.id);
});

Extract information from the image

// (Optional) initialize an instance of FaceDetectorOptions
//var options:FaceDetectorOptions = new FaceDetectorOptions();
//options.performanceMod = 
//options.minFaceSize = 
//options.landmarkMode = 
//...

var detector:FaceDetector = Mlkit.initFaceDetector(options);
detector.process(visionImg, null, function ($faces:Vector.<VisionFace>, $error:Error):void
{
	if($error) trace($error.message);
	
	if($faces)
	{
		trace("--------- VisionFace ------");
		for(var i:int=0; i < $faces.length; i++)
		{
			var face:VisionFace = $faces[i];
			trace("\t" + face.toString());
		}
		trace("---------------------------");
	}
				
	detector.close();
});