Getting Started with OpenCV
Computer vision applications are interesting and useful, but the underlying algorithms are computationally intensive. With the advent of cloud computing, we are getting more processing power to work with.
The OpenCV library enables us to run computer vision algorithms efficiently in real time. It has been around for many years and has become the standard library in this field. One of the main advantages of OpenCV is that it is highly optimized and available on almost all platforms.
This book will cover the various algorithms we will be using, why we are using them, and how to implement them in OpenCV.
In this chapter, we are going to learn how to install OpenCV on various operating systems. We will discuss what OpenCV offers out of the box, and the various things that we can do using the inbuilt functions.
By the end of this chapter, you will be able to answer the following questions:
- How do humans process visual data, and how do they understand image content?
- What can we do with OpenCV, and what are the various modules available in OpenCV that can be used to achieve those things?
- How do we install OpenCV on Windows, Linux, and Mac OS X?
- 我們都是數(shù)據(jù)控:用大數(shù)據(jù)改變商業(yè)、生活和思維方式
- Hands-On Machine Learning with Microsoft Excel 2019
- Test-Driven Development with Mockito
- SQL Server入門經(jīng)典
- Sybase數(shù)據(jù)庫在UNIX、Windows上的實施和管理
- Remote Usability Testing
- 一個64位操作系統(tǒng)的設(shè)計與實現(xiàn)
- 網(wǎng)站數(shù)據(jù)庫技術(shù)
- 一本書講透Elasticsearch:原理、進階與工程實踐
- 活用數(shù)據(jù):驅(qū)動業(yè)務(wù)的數(shù)據(jù)分析實戰(zhàn)
- Expert Python Programming(Third Edition)
- Oracle 11g數(shù)據(jù)庫管理員指南
- Practical Convolutional Neural Networks
- 數(shù)據(jù)庫基礎(chǔ)與應(yīng)用
- Flume日志收集與MapReduce模式