OpenCV Computer Vision with Python

Book Description

Learn to capture videos, manipulate images, and track objects with Python using the OpenCV Library

Overview

• Set up OpenCV, its Python bindings, and optional Kinect drivers on Windows, Mac or Ubuntu
• Create an application that tracks and manipulates faces
• Identify face regions using normal color images and depth images

In Detail

Computer Vision can reach consumers in various contexts via webcams, camera phones and gaming sensors like Kinect. OpenCV’s Python bindings can help developers meet these consumer demands for applications that capture images, change their appearance and extract information from them, in a high-level language and in a standardized data format that is interoperable with scientific libraries such as NumPy and SciPy.

“OpenCV Computer Vision with Python” is a practical, hands-on guide that covers the fundamental tasks of computer vision—capturing, filtering and analyzing images—with step-by-step instructions for writing both an application and reusable library classes.

“OpenCV Computer Vision with Python” shows you how to use the Python bindings for OpenCV. By following clear and concise examples you will develop a computer vision application that tracks faces in live video and applies special effects to them. If you have always wanted to learn which version of these bindings to use, how to integrate with cross-platform Kinect drivers and and how to efficiently process image data with NumPy and SciPy then this book is for you.

What you will learn from this book

• Install OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect—all on Windows, Mac or Ubuntu
• Capture, display, and save photos and real-time videos
• Handle window events and input events using OpenCV’s HighGui module or Pygame
• Understand OpenCV’s image format and how to perform efficient operations on OpenCV images with NumPy and SciPy
• Apply “curves” and other color transformations to simulate the look of old photos, movies or video games
• Apply an effect only to edges in an image
• Copy and resize segments of an image
• Apply an effect only to certain depths in an image by using data from a depth sensor such as Kinect
• Track faces, eyes, noses and mouths by using prebuilt datasets
• Track arbitrary objects by creating original datasets

Approach

A practical, project-based tutorial for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python.

Who this book is written for

OpenCV Computer Vision with Python is written for Python developers who are new to computer vision and want a practical guide to teach them the essentials. Some understanding of image data (for example, pixels and color channels) would be beneficial. At a minimum you will need access to at least one webcam. Certain exercises require additional hardware like a second webcam, a Microsoft Kinect or an OpenNI-compliant depth sensor such as the Asus Xtion PRO.

Table of Contents

Preface
Chapter 1: Setting up OpenCV
Chapter 2: Handling Files, Cameras, and GUIs
Chapter 3: Filtering Images
Chapter 4: Tracking Faces with Haar Cascades
Chapter 5: Detecting Foreground/Background Regions and Depth
Appendix A: Integrating with Pygame
Appendix B: Generating Haar Cascades for Custom Targets

中文：

书名：OpenCV Computer Vision with Python

了解如何使用OpenCV库通过Python捕获视频、操作图像和追踪对象

概述

• 在Windows、Mac或Ubuntu上设置OpenCV、其Python绑定和可选的Kinect驱动程序
• 创建跟踪和操控人脸的应用程序
• 利用正常彩色图像和深度图像识别人脸区域

详细地说

计算机视觉可以通过网络摄像头、照相手机和Kinect等游戏传感器在不同的环境中接触到消费者。OpenCV的Python绑定可以帮助开发人员满足这些消费者对应用程序的需求，这些应用程序以高级语言和标准化数据格式捕获图像、更改图像外观并从中提取信息，该数据格式可与NumPy和SciPy等科学库互操作。

OpenCV Computer Vision with Python&#8221；是一本实用的动手指南，涵盖了计算机视觉的基本任务-捕获、过滤和分析图像-以及编写应用程序和可重用库类的分步说明。

&#8220；OpenCV Computer Vision&#8221；向您展示了如何使用OpenCV的Python绑定。通过遵循清晰和简洁的示例，您将开发一个计算机视觉应用程序，该应用程序跟踪实时视频中的人脸并对其应用特殊效果。如果你一直想了解这些绑定的哪个版本，如何与跨平台的Kinect驱动程序集成，以及如何使用NumPy和SciPy高效地处理图像数据，那么这本书是为你准备的。

你将从这本书中学到什么

• 在Windows、Mac或Ubuntu上安装OpenCV和相关软件，如Python、NumPy、SciPy、OpenNI和SensorKinect
• 捕获、显示和保存照片和实时视频
• 使用OpenCV的HighGui模块或PyGame处理窗口事件和输入事件
• 了解OpenCV的图像格式，以及如何使用NumPy和SciPy对OpenCV图像执行高效操作
• 应用曲线和其他颜色变换来模拟旧照片、电影或视频游戏的外观
• Apply an effect only to edges in an image
• 复制图像段并调整其大小
• 通过使用来自深度传感器(如Kinect)的数据，仅将效果应用于图像中的特定深度
• 使用预置的数据集跟踪人脸、眼睛、鼻子和嘴巴
• 通过创建原始数据集追踪任意对象

方法

这是一个实用的、基于项目的教程，适用于想要开始使用OpenCV和Python进行计算机视觉的Python开发人员和爱好者。

这本书是为谁写的

OpenCV Computer Vision with Python是为那些刚接触计算机视觉并想要一个实用指南来教他们基本知识的Python开发人员编写的。了解一些图像数据(例如，像素和颜色通道)将是有益的。您至少需要访问一个网络摄像头。某些练习需要额外的硬件，如第二个网络摄像头、微软Kinect或符合OpenNI标准的深度传感器，如华硕Xtion Pro。

目录表

前言
第1章：设置OpenCV
Chapter 2: Handling Files, Cameras, and GUIs
Chapter 3: Filtering Images
第4章：使用Haar Cascade跟踪人脸
Chapter 5: Detecting Foreground/Background Regions and Depth
附录A：与PyGame集成
附录B：为自定义目标生成Haar级联