Building on the scipy.interp1d function, we have implemented a collection of curve filters that are efficient (due to the use of lookup arrays) and easily extensible (due to an object-oriented design). Our work has included special-purpose curve filters that can make digital images look more like film shots. These filters can be readily integrated into an application such as Cameo, as demonstrated by the use of our Portra film emulation filter in Chapter 3, Processing Images with OpenCV.
Learning OpenCV 4 Computer Vision with Python 3 - Third Edition
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Learning OpenCV 4 Computer Vision with Python 3 - Third Edition
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Overview of this book
Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3.
You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age.
By the end of this book, you’ll have the skills you need to execute real-world computer vision projects.
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Current Title:
Learning OpenCV 4 Computer Vision with Python 3 - Third Edition
Table of Contents (13 chapters)
Preface
Setting Up OpenCV
Free Chapter
Handling Files, Cameras, and GUIs
Processing Images with OpenCV
Depth Estimation and Segmentation
Detecting and Recognizing Faces
Retrieving Images and Searching Using Image Descriptors
Building Custom Object Detectors
Tracking Objects
Camera Models and Augmented Reality
Introduction to Neural Networks with OpenCV
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Appendix A: Bending Color Space with the Curves Filter
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