Book Image

Azure Serverless Computing Cookbook - Third Edition

By : Praveen Kumar Sreeram
Book Image

Azure Serverless Computing Cookbook - Third Edition

By: Praveen Kumar Sreeram

Overview of this book

This third edition of Azure Serverless Computing Cookbook guides you through the development of a basic back-end web API that performs simple operations, helping you understand how to persist data in Azure Storage services. You'll cover the integration of Azure Functions with other cloud services, such as notifications (SendGrid and Twilio), Cognitive Services (computer vision), and Logic Apps, to build simple workflow-based applications. With the help of this book, you'll be able to leverage Visual Studio tools to develop, build, test, and deploy Azure functions quickly. It also covers a variety of tools and methods for testing the functionality of Azure functions locally in the developer's workstation and in the cloud environment. Once you're familiar with the core features, you'll explore advanced concepts such as durable functions, starting with a "hello world" example, and learn about the scalable bulk upload use case, which uses durable function patterns, function chaining, and fan-out/fan-in. By the end of this Azure book, you'll have gained the knowledge and practical experience needed to be able to create and deploy Azure applications on serverless architectures efficiently.
Table of Contents (14 chapters)
13
Index

Using Cognitive Services to locate faces in images

Microsoft offers Cognitive Services, which helps developers to leverage AI features in their applications.

In this recipe, you'll learn how to use the Computer Vision API (Cognitive Service) to detect faces within an image. We will be locating faces, capturing their coordinates, and saving them in different areas of Azure Table storage based on gender.

Cognitive Services apply AI algorithms, so they might not always be accurate. The accuracy returned by Cognitive Services is always between 0 and 1, where 1 means 100% accurate. You can always use the accuracy value returned by Cognitive Services and implement your custom requirements based on the accuracy.

Getting ready

To get started, we need to create a Computer Vision API and configure its API keys so that Azure Functions (or any other program) can access it programmatically.

Make sure that you have Azure Storage Explorer installed and configured to access the...