OpenCV 3 Computer Vision with Python Cookbook

Alexey Spizhevoy, Aleksandr Rybnikov

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商品描述

Key Features

  • Build computer vision applications with OpenCV functionality via Python API
  • Get your hands dirty with image processing, image/video analysis, multiple view geometry, and machine learning
  • Learn how to use state-of-the-art deep learning models for image classification, object detection, and face recognition

Book Description

OpenCV 3 is a native cross-platform library for computer vision, machine learning, and image processing. OpenCV's convenient high-level APIs hide very powerful internals designed for computational efficiency and with a strong focus on real-time applications that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems by providing number of recipes that you can improvise in your existing applications.

In this book, you will learn how to process an image by manipulating pixels and analyze an image using histograms. It will guide you on how to segment images into homogeous regions and extract meaningful objects. Then you will learn how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. Techniques to achieve camera calibration and perform multiple-view analysis will also be explained. You will be presented with various recipes on how to reconstruct a 3D scene from images. Later you will work on conversion of low level pixel information to high level concepts for applications such as object detection and recognition and scene monitoring and you'll discover how to process video from files or cameras, as well as how to detect and track moving objects. Finally, you'll also get acquainted with recent approaches in deep learning, object classification, and neural networks.

By the end of the book, you will be able to apply skills in OpenCV to create and explore computer vision applications in various domains.

What you will learn

  • Build OpenCV from sources with Python API support
  • Get familiar with low-level image processing methods
  • Learn common linear algebra tools needed in computer vision
  • Implement camera models and epipolar geometry tools
  • Find out how to detect interesting points in images and compare them
  • Binarize images and common image masks functionality
  • Detect objects and track them in video
  • Apply state-of-the-art deep learning models for image classification, object detection, and face recognition

商品描述(中文翻譯)

《OpenCV 3 计算机视觉项目实战》

主要特点



  • 通过 Python API 利用 OpenCV 功能构建计算机视觉应用程序

  • 深入了解图像处理、图像/视频分析、多视角几何和机器学习

  • 学习如何使用最先进的深度学习模型进行图像分类、目标检测和人脸识别

书籍简介


OpenCV 3 是一个原生跨平台的计算机视觉、机器学习和图像处理库。OpenCV 提供了方便的高级 API,隐藏了非常强大的内部功能,旨在提高计算效率,并专注于能够利用多核和 GPU 处理的实时应用程序。本书将通过提供一系列的示例,帮助您解决越来越具有挑战性的计算机视觉问题,并在现有应用程序中进行改进。

在本书中,您将学习如何通过操作像素来处理图像,并使用直方图分析图像。本书将指导您如何将图像分割为同质区域并提取有意义的对象。然后,您将学习如何应用图像滤波器来增强图像内容,并利用图像几何来呈现图片场景的不同视角。本书还将解释实现相机校准和进行多视角分析的技术。您将了解如何通过图像重建来实现三维场景。随后,您将处理从低级像素信息到高级概念的转换,用于目标检测和识别以及场景监控,并了解如何处理来自文件或摄像头的视频,以及如何检测和跟踪移动物体。最后,您还将了解深度学习、目标分类和神经网络的最新方法。

通过阅读本书,您将能够运用 OpenCV 的技能,在各个领域创建和探索计算机视觉应用程序。

您将学到什么



  • 使用 Python API 支持构建 OpenCV

  • 熟悉低级图像处理方法

  • 学习计算机视觉所需的常见线性代数工具

  • 实现相机模型和极线几何工具

  • 了解如何检测图像中的有趣点并进行比较

  • 对图像进行二值化和常见图像掩模功能

  • 检测并跟踪视频中的对象

  • 应用最先进的深度学习模型进行图像分类、目标检测和人脸识别