Book Image

Computer Vision on AWS

By : Lauren Mullennex, Nate Bachmeier, Jay Rao
Book Image

Computer Vision on AWS

By: Lauren Mullennex, Nate Bachmeier, Jay Rao

Overview of this book

Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models. You’ll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that’ll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads. By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.
Table of Contents (21 chapters)
Part 1: Introduction to CV on AWS and Amazon Rekognition
Part 2: Applying CV to Real-World Use Cases
Part 3: CV at the edge
Part 4: Building CV Solutions with Amazon SageMaker
Part 5: Best Practices for Production-Ready CV Workloads

Using IP cameras

After confirming that the RTSP endpoint(s) are accessible, it is time to connect using the open source computer vision library OpenCV. OpenCV for Python is a collection of tools and capabilities for interacting with image and video content. It contains a ton of functionality, enough to fill multiple books. However, we’ll only scratch the surface and use it to collect frames from our cameras.

Installing OpenCV

OpenCV’s Python installation has several platform-dependent binaries, so you must be mindful of where the Python code will execute. This chapter uses an x86 64bit Amazon Linux 2 machine:

$ yum -y update && yum -y install \ 
  mesa-libGL.x86_64 \
  opencv-python.x86_64 \

Suppose you’re using an Apple M1 or Amazon Graviton processor. In that case, you must specify the ARM64 platform:

$ yum -y update && yum -y install \
  mesa-libGL.arm64 \