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Learning OpenCV 5 Computer Vision with Python

You're reading from   Learning OpenCV 5 Computer Vision with Python Tackle computer vision and machine learning with the newest tools, techniques and algorithms

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Product type Paperback
Published in Jul 2025
Publisher Packt
ISBN-13 9781803230221
Length
Edition 4th Edition
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
Author Profile Icon Joseph Howse
Joseph Howse
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Table of Contents (12) Chapters Close

1. Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning FREE CHAPTER
2. Setting Up OpenCV 3. Handling Files, Cameras, and GUIs 4. Processing Images with OpenCV 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. OpenCV Applications at Scale Appendix A: Bending Color Space with the Curves Filter

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In this chapter we will take OpenCV to the cloud, by exploring technologies and methodologies that will allow you to package your application and deploy it on AWS so it can be made available to the public even at large scale, without having to learn lengthy and complex technologies to maintain such applications.

We will provide a brief introduction to containers and containerization tools like Docker, an overview of the AWS cloud provider and AWS Lambda, and finally we will demonstrate how to develop a simple application and deploy it.

NOTE: even if you don’t want to use AWS, the knowledge you will acquire about containerization should seamlessly transfer to other cloud providers or cloud-agnostic solutions such as Kubernetes (which can be deployed on any cloud).

IMPORTANT NOTE: to follow the examples in this chapter you will need an AWS account. While you have to provide credit card credentials, if you follow...

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