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OpenCV 4 Computer Vision Application Programming Cookbook

OpenCV 4 Computer Vision Application Programming Cookbook

By : Millán Escrivá, Robert Laganiere
5 (1)
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OpenCV 4 Computer Vision Application Programming Cookbook

OpenCV 4 Computer Vision Application Programming Cookbook

5 (1)
By: Millán Escrivá, Robert Laganiere

Overview of this book

OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work with recipes to implement a variety of tasks. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by guiding you through setting up OpenCV, and explaining how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of this book, you'll have the skills you need to confidently implement a range of computer vision algorithms to meet the technical requirements of your complex CV projects.
Table of Contents (17 chapters)
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OpenCV Advanced Features

Deep learning is a subfield of machine learning, based on traditional neural networks and convolutional neural networks. It's state-of-the-art pattern recognition. Deep learning is reaching the best accuracy in fields such as speech recognition, text recognition, and image classification. Actually, OpenCV adds the deep learning module as a basic module in its core algorithms and is making big efforts to increase its performance using CPUs and GPUs.

In this chapter of advanced features, we are going to cover how to enable Halide, a new language that OpenCV is using to improve the performance of deep learning inferences.

Finally, we are going to explore the new possibilities of using OpenCV in a web browser as a JavaScript library, which allows us to use computer vision in a web client without installing anything on the client computer.

In this chapter...

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