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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
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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

AWS Serverless (Fargate, Lambda) and AWS SAM

As mentioned, the reason why we are focusing on Lambda functions is their serverless nature.

Serverless clearly does not mean “without servers”, more “without the need of provisioning and managing servers”. Which, if you ask me, is a great selling point for all computer vision developers out there who want to put their code to production in a web context without having to learn more than simple basics of web development (really, just how to handle a web request).

This idea of developing applications without having to provision the underlying ressources isn’t new, but the flexibility and stability provided by containers pushes this aspect of development and deployment into another level.

Moreover, even in existing products that encapsulate your application in an environment which makes deployment easy, scalability remains an issue.

AWS Fargate and AWS Lambda instead are resolving exactly this problem. They...

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