Identify capabilities of the Face service

You’ll encounter a pivotal segment concerning the capabilities of the Azure Face service.
The Face API is part of Azure’s Cognitive Services, which leverages machine learning algorithms
to encapsulate powerful AI features.

Azure Face Service

Microsoft’s Azure Face service can detect, recognize, and analyze human faces in images.
Its features are divided into four categories: face detection, face verification, finding similar faces,
and face identification.

Face Detection

Face detection dives into the particulars of detecting human faces in an image. More than just identifying
the presence of a face, it’s also key in providing face landmarks. These landmarks are the various detailed points
(such as pupil or nose tip) of a face that helps in understanding facial features better.

Face attributes such as age, gender, emotion, facial hair, and accessories can be returned using this service.
For instance, ‘FaceAttributes.emotion’ could be used to identify the emotional state (happiness, anger, surprise, etc.)
of a person in the image.

Face Verification

The Face Verification function is created to identify if two faces belong to the same person.
The main task is to compare the two faces and verify if they are from the same individual.

For instance, in the security sector, this verification ability can verify a person’s identity based on the
face data captured and compare it with the stored face data.

Finding Similar faces

Finding similar faces methodology is used to find a similar set of faces from a group of several faces.
It helps to match a face against a pre-existing set of stored faces and determine similarity.

Face Identification

Face Identification helps in identifying previously tagged people in images.
In essence, this function will match new faces against a database of known faces to generate person identities.

So if you have a database of employees and an incoming image feed, you can check to determine whether the person
in the image feed is an employee or not using Face Identification.

Face API working process

To illustrate how Face API works, consider the following steps:

1. The user uploads an image to the application.
2. The application sends this image to the Face API service.
3. Face API detects faces in the image and returns a faceId for each detected face.
4. FaceId(s) are called for the required service (like Face Verification or Face Identification) and results
   are returned and displayed back by the application.

In terms of coding, to use Azure’s Face API with Python, you’d need to install the cognitive_face Python module first.

pip install cognitive_face

Then,

import cognitive_face as CF

KEY = ‘subscription_key’ # Replace with a valid Subscription Key here.
CF.Key.set(KEY)

BASE_URL = ‘https://westus.api.cognitive.microsoft.com/face/v1.0/’ # Replace with your regional Base URL
CF.BaseUrl.set(BASE_URL)

img_url = ‘https://www.biography.com/.image/t_share/MTE5NTU2MzE2OTg0NDAyODg4/barack-obama-12782369-1-402.jpg’
result = CF.face.detect(img_url)

print (result)

The Python script above uses the detect function of cognitive_face module to detect faces in the mentioned image URL and prints returned results.

Understanding the capabilities of Azure Face Service is an essential component of your studies in preparation for the AI-900 Microsoft Azure AI Fundamentals exam. From detecting individual faces and their features in an image, to comparing, verifying, and identifying faces against an existing database, Face API provides extensive cover in facial recognition tasks.

Knowing how to manipulate these features in coding languages like Python will equip you not only for the
Azure AI-900 exam, but for real-world applications of face recognition AI.

Practice Test

True or False: Azure Face service can be used to detect human faces in an image but not in a video.

• True
• False

Answer: False

Explanation: The Azure Face service can detect, recognize, and analyze human faces in both images and videos.

Azure Face service can be used for age estimation, emotion recognition, and similar face finding.

• a) True
• b) False

Answer: a) True

Explanation: Azure Face service offers multiple capabilities including face identification, age estimation, emotion recognition, similar face finding, and more.

Which of the following capabilities are provided by Azure Face service?

• a) Facial Recognition
• b) Age Estimation
• c) Emotion Recognition
• d) All of the above

Answer: d) All of the above

Explanation: All the mentioned capabilities are offered by Azure Face service.

True or False: Azure Face Service does not support the detection of accessories like glasses, headwear, etc. on a detected face.

• True
• False

Answer: False

Explanation: Azure Face service does support the detection of various facial accessories including glasses, headwear, etc.

Azure Face Service cannot identify faces across a large group of people.

• a) True
• b) False

Answer: b) False

Explanation: Azure Face service’s large-scale identification feature allows the identification of faces across a large group of people.

True or False: Azure Face service can recognize and identify celebrities.

• True
• False

Answer: True

Explanation: Azure Face service has a pre-built celebrity recognition module, which can recognize and identify media personalities.

Which of the following are attributes that Azure Face Service can return?

• a) Face landmarks
• b) Gender
• c) Ear placement
• d) Both a & b

Answer: d) Both a & b

Explanation: Azure Face service can return an extensive array of face attributes including face landmarks and gender. However, it does not return ear placement.

Azure Face service can detect and compare face attributes in real-time.

• a) True
• b) False

Answer: a) True

Explanation: The Face API uses machine learning algorithms for real-time identification and comparison of faces.

The Azure Face service does not support group face identification.

• a) True
• b) False

Answer: b) False

Explanation: Azure Face service provides a large-scale identification feature that groups similar faces together, aiding in more efficient face identification.

True or False: Facial Hair Recognition is not possible with Azure Face Service.

• True
• False

Answer: False

Explanation: Along with other face attributes, Azure Face service can also detect and recognize presence of facial hair.

Azure Face Service provides 100% accurate emotion detection every time.

• a) True
• b) False

Answer: b) False

Explanation: While Azure Face service is highly accurate, it does not guarantee 100% accuracy every time due to a variety of factors like lighting, quality of the image, or even the subject’s expression.

In Azure Face Service, each detected face gets a persistently stored faceId.

• a) True
• b) False

Answer: a) True

Explanation: A detected face is associated with a persistently stored faceId for tracking purposes.

Azure Face service can only detect one face at a time in an image.

• a) True
• b) False

Answer: b) False

Explanation: Azure Face service can detect multiple faces in a single image.

Azure Face service cannot recognize make-up patterns.

• a) True
• b) False

Answer: b) False

Explanation: Azure Face service is capable of detecting and recognizing make-up patterns.

Azure Face service can be used for medical purposes.

• a) True
• b) False

Answer: b) False

Explanation: As per Microsoft’s policy, Azure Face service should not be used for any medical or health related application.

Interview Questions

What is Microsoft Azure Face service?

Microsoft Azure Face service is a cloud-based service that provides the most advanced face algorithms. It includes capabilities for face detection, face verification, face recognition, facial feature identification and facial emotion recognition.

Can Azure Face Service identify age and gender?

Yes, Azure Face Service has the capability to identify both age and gender.

What other features can Azure Face service detect apart from age and gender?

Apart from age and gender, Azure Face service can also detect facial hair, emotion, hairstyle, glasses, makeup, and accessories.

Is Microsoft Azure Face service able to detect faces in an image and identify previously tagged people in that same image?

Yes, Azure Face service’s face identification feature allows it to pick out previously tagged individuals in an image.

What is the maximum number of faces that can be detected in an image using Azure Face API?

Azure Face API can detect up to 64 faces in an image.

Can the Azure Face service recognize the emotions of the people in the images?

Yes, Azure Face Service has the capability to recognize the emotions of people in the images.

How does Azure Face Service enable face recognition?

Azure Face Service enables face recognition by comparing faces in the image with a database of known faces and providing the best possible matches.

What is a “person group” in Azure Face Service?

A person group in Azure Face Service is a way of organizing faces into named groups in preparation for face identification.

What is the benefit of using Face API in Azure AI services?

Face API in Azure AI services allows developers to integrate human face recognition in their applications for tasks like person identification, emotion recognition, age estimation, gender identification, etc.

What are the primary operations that Azure Face service can perform?

Azure Face service can perform face detection, face verification, face identification, face grouping, and face recognition.

Does Azure Face Service offer support for training a model?

Yes, in Azure Face Service, you can train a model using the Train API, after which it can be used for face identification.

Can Azure Face service detect the head pose of a face in an image?

Yes, Azure Face service can estimate the head pose of a face in an image based on the roll, yaw, and pitch of the head.

What types of input does Azure Face API accept?

Azure Face API accepts input as an image file or URL.

Can the Azure Face API determine expected gender?

While the Azure Face API can estimate gender, it is worth noting that its analysis is based on appearance and not biological or self-identified gender. It should not be used for making decisions about gender identity.

What file types are supported by the Azure Face API for face detection?

The Azure Face API supports JPEG, PNG, GIF, and BMP file formats for face detection.