FaceAI Web SDK v2.0

FaceAI Web SDK; the fastest, lightest and complete Facial Expression Analysis and Emotion Recognition AI; that works on the Client End Point / device within any HTML5 Web-browser on Mobile or Desktop. FaceAI SDK works right on Client End, none of your personal data goes to a Server.

Download FaceAI Web SDK v2.1

Released: September 25, 2020

Table of Contents

How to use FaceAI Web SDK?

  • Download the SDK and extra the archive. You will find the following .js file.
    • EnxFaceAI.js – This is a standard Java Script library.
  • Now, you may use the EnxFaceAI.js file in your HTML file to make use of the SDK.
<html>
<head>
<script language="javascript" src="path/EnxFaceAI.js"></script>
</head>
<body></body>
</html>

Note: You must enable FaceAI while defining a Room for Facial Expression Analysis to work. Use “{ "settings": { "facex": true; }} to define a room.

Initialize FaceAI

FaceAI analyses Video Streams within an ongoing EnableX Video Session. To get started with analysis, you must bind the FaceAI Object with the Room in which Video Session is on.

Method: EnxFaceAI.init(connectedRoomInfo, stream, callback) – To start analysis on given Stream

Parameters:

  • connectedRoomInfo – JSON Object. Pass the Response-JSON returned as Callback of EnxRtc.joinRoom() or EnxRoom.connect() method.
  • stream – The Stream Object which will be analyzed. You may analyze Local Stream Object or Remote Stream Object (Stream Reference may be bound in Active Talkers List)
  • callback: Callback to know if the room is enabled for FaceAI Analysis an that the client point is connected to an active session

Example: 

localStream = EnxRtc.joinRoom(token, config, (response, error) => {
	if (error && error != null) { }

	if (response && response != null) {
		const FaceAI  = new EnxFaceAI(); // Construct the Object
		FaceAI.init(response, localStream, function (event) {
			// event.result == 0 - All Ok to process	
		})
	}
})

Face Detector

This is to detect how many faces are there in a Video Stream. The Event Listener keeps getting data in JSON as the detector tries to detect faces in the changing video frame.

Method: EnxFaceAI.startFaceDetector(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Detector would analyze.
    • maxInputFrameSize – Number. Default 160 (pixel). Input Frame Size in pixels for Face Detection.
    • fullFrameDetection – A boolean. It is true when detection was full-frame and multiple faces can be returned, false otherwise.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-detector – This event notifies repeatedly with Face Detection analysis report with JSON Object. JSON Object Reference appended below:
{
    faces: Array(n)
    rects: Array(n)
    status: string
}

JSON Object Explanation:

  • faces: Array. The detected faces in form of ImageData objects (zero or one; or multiple faces, if fullFrameDetection is true)
  • rects: Array of objects. Describes the bounding boxes (zero or one; or multiple rects, if fullFrameDetection is true)
    • x: Upper left point x coordinate
    • y: Upper left point y coordinate
    • width: Width of the bounding box
    • height: Height of the bounding box
  • status: String. Its status of the face tracker
    • INIT: Detector initializing; zero or many faces could be returned
    • TRACK_OK: Detector is correctly tracking one face; one face is returned
    • RECOVERING: Detector lost a face and attempting to recover and continue tracking; zero faces are returned

Method: EnxFaceAI.stopFaceDetector(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	maxInputFrameSize: 200,
	fullFrameDetection: true
}; 

// Start Face Detector
faceAI.startFaceDetector(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-detector", (evt) => {
			console.log(evt.detail, "face-detector");
		});
	}
});

// Stop Face Detector
faceAI.stopFaceDetector((res) => {
	if (res.result === 0) {	}
});

Face Pose

This is to analyze face rotation and position in a Video Stream. The Event Listener keeps getting data in JSON as FaceAI keeps detecting face rotation in the video stream. Face Rotation angle data is represented in terms of radiants as Pitch, Roll and Yaw.

Method: EnxFaceAI.startFacePose(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Pose would be analyzed.
    • smoothness: Number. Default 0.65. Range 0-1. A value closer to 1 provides greater smoothing and slower response time. Lower values provide less smoothing but faster response time. Set it to 0 (zero) if you need the raw signal.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-pose – This event notifies repeatedly with Face Rotation & Position analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		pose: {
			pitch: Number, 
			roll: Number, 
			yaw: Number
		}
	}
}

JSON Object Explanation:

  • output: Face Rotation & Position Report
    • pose: Filtered (smoothened) pose rotation angles expressed in radiants as pitch, roll and yaw.

Method: EnxFaceAI.stopFacePose(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	smoothness: 0.65
};

// Start Face Pose
faceAI.startFacePose(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-pose", (evt) => {
			console.log(evt.detail, "face-pose");
		});
	}
});

// Stop Face Pose
faceAI.stopFacePose((res) => {
	if (res.result === 0) {	}
});

Face Age

This is to analyze and predict face age in a Video Stream. Face Age predicts within a age-range. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face age. If the prediction quality is poor, the event is not fired.

Method: EnxFaceAI.startFaceAge(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Age would be analyzed.
    • Currently EnableX doesn’t have any parameter. Therefore, you need to keep it empty while calling this method.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-age – This event notifies repeatedly with Face AGE analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		age: {
			-18: Number, 
			18-35: Number, 
			35-51: Number, 
			51-: Number
		}, 
		numericAge: Number
	}
}

JSON Object Explanation:

  • output: Face Age Analysis Report
    • age: Filtered (smoothened) age prediction:
      • -18: Probability Weightage suggesting less than 18 years old.
      • 18-35: Probability Weightage suggesting between 18 to 35 years old.
      • 35-51: Probability Weightage suggesting between 18 35 years old.
      • 51-: Probability Weightage suggesting equal or greater than 51 years old.
    • numericAge: Numeric. Estimated Age

Method: EnxFaceAI.stopFaceAge(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {};

// Start Face Age
faceAI.startFaceAge(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-age", (evt) => {
			console.log(evt.detail, "face-age");
		});
	}
});

// Stop Face Age
faceAI.stopFaceAge((res) => {
	if (res.result === 0) {	}
});

Face Gender

This is to analyze face gender in a Video Stream. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face gender.

Method: EnxFaceAI.startFaceGender(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Gender would be analyzed.
    • smoothness: Number. Default 0.95. Range 0-1. A value closer to 1 provides greater smoothing and slower response time. Lower values provide less smoothing but faster response time. Set it to 0 (zero) if you need the raw signal.
    • threshold: Number. Default 0.70. Range 0.5-1. It controls the minimum value of confidence for which mostConfident output returns the predicted gender name instead of undefined.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-gender– This event notifies repeatedly with Face Gender analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		gender: {
			Female: Number, 
			Male: Number
		}, 
		mostConfident: String
	}
}

JSON Object Explanation:

  • output: Face Gender Report
    • gender: Filtered (smoothened) probabilities of the gender prediction:
      • Female: Probability weightage for gender is female
      • Male: Probability weightage for gender is male
    • mostConfident: Gender name of the most likely result if its smoothened probability is above the threshold, otherwise it is undefined.

Method: EnxFaceAI.stopFaceGender(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	smoothness: 0.95,
	threshold: 0.70
};

// Start Face Gender
faceAI.startFaceGender(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-gender", (evt) => {
			console.log(evt.detail, "face-gender");
		});
	}
});

// Stop Face Gender
faceAI.stopFaceGender((res) => {
	if (res.result === 0) {	}
});

Face Emotion

This is to analyze face emotions in Video Stream. It analyses basic 8 emotions in a human face, viz. Angry, Disgust, Fear, Happy, Sad, Surprise, Neutral. It also returns most dominate emotion on face. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face emotion.

Method: EnxFaceAI.startFaceEmotion(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Gender would be analyzed.
    • smoothness: Number. Default 0.95. Range 0-1. A value closer to 1 provides greater smoothing and slower response time. Lower values provide less smoothing but faster response time. Set it to 0 (zero) if you need the raw signal.
    • threshold: Number. Default 0.70. Range 0.5-1. It controls the minimum value of confidence for which mostConfident output returns the predicted gender name instead of undefined.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-emotion – This event notifies repeatedly with Face Gender analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		dominantEmotion: String,
		emotion: {
			Angry: Number, 
			Disgust: Number, 
			Fear: Number, 
			Happy: Number, 
			Neutral: Number, 
			Sad: Number, 
			Surprise: Number
		}
	}
}

JSON Object Explanation:

  • output: Face Emotion Report
    • dominantEmotion: Name of Dominant Emotion if present, otherwise it is undefined.
    • emotion: Filtered (smoothened) values of the probability distribution of emotions. The sum of all the probabilities is always 1, each probability in the distribution has a value between 0 and 1.
      • Angry: Probability for Angry.
      • Disgust: Probability for Disgust.
      • Fear: Probability for Fear.
      • Happy: Probability for Happy.
      • Sad: Probability for Sad.
      • Surprise: Probability for Surprise.
      • Neutral: Probability for Neutral.

Method: EnxFaceAI.stopFaceEmotion(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	smoothness: 0.95,
	threshold: 0.70
};

// Start Face Emotion
faceAI.startFaceEmotion(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-emotion", (evt) => {
			console.log(evt.detail, "face-emotion");
		});
	}
});

// Stop Face Emotion
faceAI.stopFaceEmotion((res) => {
	if (res.result === 0) {	}
});

Face Features

This is to analyze face features in a Video Stream. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face features.

Method: EnxFaceAI.startFaceFeatures(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Features would be analyzed.
    • smoothness: Number. Default 0.90. Range 0-1. Value closer to 1 provides greater smoothing and slower response time. Lower values provide lesser smoothing but faster response time. Set it to 0 (zero) if you need the raw signal.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-features – This event notifies repeatedly with Face Features analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		features: {
			ArchedEyebrows: Number, 
			Attractive: Number,
			....
			....
		}
	}
}

JSON Object Explanation:

  • output: Face Features Report
    • features: Filtered (smoothened) probabilities of each face independent feature in range 0.0 – 1.0. The following features are evaluated:
      • Arched Eyebrows
      • Attractive
      • Bags Under Eyes
      • Bald
      • Bangs
      • Beard 5 O’Clock Shadow
      • Big Lips
      • Big Nose
      • Black Hair
      • Blond Hair
      • Brown Hair
      • Chubby
      • Double Chin
      • Earrings
      • Eyebrows Bushy
      • Eyeglasses
      • Goatee
      • Gray Hair
      • Hat
      • Heavy Makeup
      • High Cheekbones
      • Lipstick
      • Mouth Slightly Open
      • Mustache
      • Narrow Eyes
      • Necklace
      • Necktie
      • No Beard
      • Oval Face
      • Pale Skin
      • Pointy Nose
      • Receding Hairline
      • Rosy Cheeks
      • Sideburns
      • Straight Hair
      • Wavy Hair

Method: EnxFaceAI.stopFaceFeatures(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	smoothness: 0.90 
};

// Start Face Features
faceAI.startFaceFeatures(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-features", (evt) => {
			console.log(evt.detail, "face-features");
		});
	}
});

// Stop Face Features
faceAI.stopFaceFeatures((res) => {
	if (res.result === 0) {	}
});

Face Arousal Valence

This is to analyze face arousal valence in a Video Stream. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face arousal valence.

Method: EnxFaceAI.startFaceArousalValence(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Arousal Valence would be analyzed.
    • smoothness: Number. Default 0.70. Range 0-1. Value closer to 1 provides greater smoothing and slower response time. Lower values provide lesser smoothing but faster response time. Set it to 0 (zero) if you need the raw signal.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-arousal-valence – This event notifies repeatedly with Face Arousal Valence analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		arousalvalence: {
			arousal: Number, 
			valence: Number
		}
	}
}

JSON Object Explanation:

  • output: Face Arousal Valence Report
    • arousalvalence: Filtered (smoothened) values.
      • arousal: Range 1.0 to 1.0. It represents the degree of engagement (positive arousal), or disengagement (negative arousal).
      • valence: Range -1.0 to 1.0. It represents the degree of pleasantness (positive valence), or unpleasantness (negative valence).

Method: EnxFaceAI.stopFaceArousalValence(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	smoothness: 0.70 
};

// Start Face Arousal Valence
faceAI.startFaceArousalValence(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-arousal-valence", (evt) => {
			console.log(evt.detail, "face-arousal-valence");
		});
	}
});

// Stop Face Arousal Valence
faceAI.stopFaceArousalValence((res) => {
	if (res.result === 0) {	}
});

Face Attention

This is to analyze face attention in a Video Stream. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face attention.

Method: EnxFaceAI.startFaceAttention(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Attention would be analyzed.
    • smoothness: Number. Default 0.83. Range 0-1. Value closer to 1 provides greater smoothing and slower response time. Lower values provide lesser smoothing but faster response time. Set it to 0 (zero) if you need the raw signal.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-attention – This event notifies repeatedly with Face Attention analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		attention: Number
	}
}

JSON Object Explanation:

  • output: Face Attention Report
    • attention: Filtered value (smoothened) in range [0.0, 1.0]. A value close to 1.0 represents attention, a value close to 0.0 represents distraction.

Method: EnxFaceAI.stopFaceAttention(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example: 

config = {
	smoothness: 0.85
};

// Start Face Attention
faceAI.startFaceAttention(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-attention", (evt) => {
			console.log(evt.detail, "face-attention");
		});
	}
});

// Stop Face Attention
faceAI.stopFaceAttention((res) => {
	if (res.result === 0) {	}
});

Face Wish

This is to analyze face wish in a Video Stream. The Event Listener keeps getting data in JSON as FaceAI keeps analyzing face wish.

Method: EnxFaceAI.startFaceWish(config, callback) – To start analysis

Parameters:

  • config – JSON Object. This is to configure or customize parameter using which the Face Wish would be analyzed.
    • smoothness: Number. Default 0.80. Range 0-1. Value closer to 1 provides greater smoothing and slower response time. Lower values provide lesser smoothing but faster response time.
  • callback: Callback to know that processing request has been accepted.

Event Listener:

  • face-wish – This event notifies repeatedly with Face Wish analysis report with JSON Object. JSON Object Reference appended below:
{	output: {
		wish: Number
	}
}

JSON Object Explanation:

  • output: Face Wish Report
    • wish: Filtered value (smoothened) in range [0, 1.0]. A value closer to 0 represents a lower wish, a value closer to 1.0 represents a higher wish.

Method: EnxFaceAI.stopFaceWish(callback) – – To stop analysis

Parameters:

  • callback: Callback to know that request has been accepted.

Example:

config = {
	smoothness: 0.80
};

// Start Face Wish
faceAI.startFaceWish(config, (res) => {
	if (res.result === 0) {
		window.addEventListener("face-wish", (evt) => {
			console.log(evt.detail, "face-wish");
		});
	}
});

// Stop Face Wish
faceAI.stopFaceWish((res) => {
	if (res.result === 0) {	}
});