Python实战：OpenCV教程与实例

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"OpenCV with Python By Example.pdf" 是一本由 Prateek Joshi 所著的实用指南，专为读者提供了如何利用 OpenCV 这个强大的计算机视觉库进行实际项目开发和创建酷炫演示的教程。OpenCV 是一个广泛应用于机器学习、图像处理和计算机视觉领域的开源库，尤其在 Python 中有着广泛应用。本书以实例驱动的方式讲解，通过丰富的代码示例，帮助读者深入理解 OpenCV 的核心概念和功能。读者可以跟随书中涵盖的主题，例如图像读取与操作、图像预处理、特征检测、对象识别、人脸识别、视频分析以及深度学习应用等，从而构建出具有实际价值的计算机视觉项目。版权方面，这本书受到 Packt Publishing 的保护，所有内容未经许可不得复制、存储或以任何形式传播，除非用于学术引用。作者和出版社不对书中信息的准确性做出明示或暗示的保证，用户购买时需自行承担风险。《OpenCV with Python By Example》于2015年9月首次出版，展示了当时的技术状态，但即便如此，它仍然是学习和实践 OpenCV for Python 的宝贵资源。因为计算机视觉技术和库在不断更新，书中的一些具体函数和方法可能已经有所演变，但其基础理论和编程技巧依然适用，并且对于新手和有经验的开发者来说，都是提升技能的宝贵资料。阅读本书，读者不仅可以掌握 OpenCV 的基本操作，还能学会如何将这些技术融入到自己的项目中，从而提升人工智能和机器学习项目的性能。对于那些希望在计算机视觉领域有所建树的开发者，这是一本不可多得的参考书籍。

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Preface

Computer vision is found everywhere in modern technology. OpenCV for

Python enables us to run computer vision algorithms in real time. With the advent

of powerful machines, we are getting more processing power to work with. Using

this technology, we can seamlessly integrate our computer vision applications into

the cloud. Web developers can develop complex applications without having to

reinvent the wheel. This book is a practical tutorial that covers various examples

at different levels, teaching you about the different functions of OpenCV and their

actual implementations.

What this book covers

Chapter 1, Applying Geometric Transformations to Images, explains how to apply

geometric transformations to images. In this chapter, we will discuss afne and

projective transformations, and see how we can use them to apply cool geometric

effects to photos. The chapter will begin with the procedure to install OpenCV-

Python on multiple platforms such as Mac OS X, Linux, and Windows. We will

also learn how to manipulate an image in various ways, such as resizing, changing

color spaces, and so on.

Chapter 2, Detecting Edges and Applying Image Filters, shows how to use fundamental

image-processing operators and how we can use them to build bigger projects.

We will discuss why we need edge detection and how it can be used in various

different ways in computer vision applications. We will discuss image ltering

and how we can use it to apply various visual effects to photos.

Preface

[ viii ]

Chapter 3, Cartoonizing an Image, shows how to cartoonize a given image using image

lters and other transformations. We will see how to use the webcam to capture a

live video stream. We will discuss how to build a real-time application, where we

extract information from each frame in the stream and display the result.

Chapter 4, Detecting and Tracking Different Body Parts, shows how to detect and track

faces in a live video stream. We will discuss the face detection pipeline and see how

we can use it to detect and track different body parts, such as eyes, ears, mouth, nose,

and so on.

Chapter 5, Extracting Features from an Image, is about detecting the salient points (called

keypoints) in an image. We will discuss why these salient points are important and

how we can use them to understand the image content. We will talk about the different

techniques that can be used to detect salient points and extract features from an image.

Chapter 6, Creating a Panoramic Image, shows how to create a panoramic image by

stitching multiple images of the same scene together.

Chapter 7, Seam Carving, shows how to do content-aware image resizing. We will

discuss how to detect "interesting" parts in an image and see how we can resize a

given image without deteriorating those interesting parts.

Chapter 8, Detecting Shapes and Segmenting an Image, shows how to perform image

segmentation. We will discuss how to partition a given image into its constituent

parts in the best possible way. You will also learn how to separate the foreground

from the background in an image.

Chapter 9, Object Tracking, shows you how to track different objects in a live video

stream. At the end of this chapter, you will be able to track any object in a live video

stream that is captured through the webcam.

Chapter 10, Object Recognition, shows how to build an object recognition system.

We will discuss how to use this knowledge to build a visual search engine.

Chapter 11, Stereo Vision and 3D Reconstruction, shows how to reconstruct the depth

map using stereo images. You will learn how to achieve a 3D reconstruction of a

scene from a set of images.

Chapter 12, Augmented Reality, shows how to build an augmented reality application.

By the end of this chapter, you will be able to build a fun augmented reality project

using the webcam.

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