Learning opencv 3 computer vision with python second edition

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Computer Vision with Python 3, published by Packt

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README.md

Computer Vision with Python 3

This is the code repository for Computer Vision with Python 3, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

This book is a thorough guide for developers who want to get started with building computer vision applications using Python 3. The book is divided into five sections: The Fundamentals of Image Processing, Applied Computer Vision, Making Applications Smarter,Extending your Capabilities using OpenCV, and Getting Hands on. Throughout this book, three image processing libraries Pillow, Scikit-Image, and OpenCV will be used to implement different computer vision algorithms.

The book aims to equip readers to build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we will look at in the book are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet.

Instructions and Navigation

All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.

The code will look like the following:

private void initialiseBluetooth()

This book will guide you through the installation of all the tools that you need to follow the code samples. Code samples introduced in various chapters are for both Android and iOS platforms hence you will need to install the Android Studio and XCode IDEs. Since simulators lack Bluetooth functionality, hence you will need physical Android and iOS devices to run the code samples. In terms of hardware, you will be needing a Raspberry Pi for the Code Lab specific for Chapter 5, Beacons with Raspberry Pi. For Chapter 4, Designing a Personal Tracking System, and Chapter 6, Weather Monitoring Using BLE in Warehouses, you will be needing a very low cost iTag and the Texas Instruments Sensor Tag. All of the hardware can be easily procured online.

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Source codes of Learning OpenCV 3 Computer Vision with Python — Second Edition

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README.md

Learning OpenCV 3 with Python — Second Edition

This is the repository and reference website for Learning OpenCV 3 with Python, a book authored by Joe Minichino and Joe Howse

Code is divided in chapters reflecting the samples contained in the book, feel free to report errors either by:

• opening an issue on github
• contacting the author directly (if you don’t have a github account)

Github is my preferred way as it grants visibility to all issues reported.

I created a VM for VirtualBox which allows you to skip installation steps and jump straight into action. However, I am yet to find a free storage service where to upload the 12GB file to make it freely availalble. This is currently being addressed so check to this page constantly.

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Source codes of Learning OpenCV 3 Computer Vision with Python — Second Edition

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Learning OpenCV 3 Computer Vision with Python, 2nd Edition

Intended for novices to the world of OpenCV and computer vision, as well as OpenCV veterans that want to learn about what’s new in OpenCV 3, this book is useful as a reference for experts and a training manual for beginners, or for anybody who wants to familiarize themselves with the concepts of object classification and detection in simple and understandable terms. Basic knowledge about Python and programming concepts is required, although the book has an easy learning curve both from a theoretical and coding point of view.

What You Will Learn

• Install and familiarize yourself with OpenCV 3’s Python API
• Grasp the basics of image processing and video analysis
• Identify and recognize objects in images and videos
• Detect and recognize faces using OpenCV
• Train and use your own object classifiers
• Learn about machine learning concepts in a computer vision context
• Work with artificial neural networks using OpenCV
• Develop your own computer vision real-life application

In Detail

OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV’s API will enable the development of all sorts of real-world applications, including security and surveillance.

Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application.

Style and approach

This book is a comprehensive guide to the brand new OpenCV 3 with Python to develop real-life computer vision applications.

Table of Contents

Chapter 1. Setting Up OpenCV
Chapter 2. Handling Files, Cameras, and GUIs
Chapter 3. Processing Images with OpenCV 3
Chapter 4. Depth Estimation and Segmentation
Chapter 5. Detecting and Recognizing Faces
Chapter 6. Retrieving Images and Searching Using Image Descriptors
Chapter 7. Detecting and Recognizing Objects
Chapter 8. Tracking Objects
Chapter 9. Neural Networks with OpenCV – an Introduction

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Learning OpenCV 3 Computer Vision with Python — Second Edition

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Book description

Unleash the power of computer vision with Python using OpenCV

• Create impressive applications with OpenCV and Python
• Familiarize yourself with advanced machine learning concepts
• Harness the power of computer vision with this easy-to-follow guide

Intended for novices to the world of OpenCV and computer vision, as well as OpenCV veterans that want to learn about what’s new in OpenCV 3, this book is useful as a reference for experts and a training manual for beginners, or for anybody who wants to familiarize themselves with the concepts of object classification and detection in simple and understandable terms. Basic knowledge about Python and programming concepts is required, although the book has an easy learning curve both from a theoretical and coding point of view.

• Install and familiarize yourself with OpenCV 3’s Python API
• Grasp the basics of image processing and video analysis
• Identify and recognize objects in images and videos
• Detect and recognize faces using OpenCV
• Train and use your own object classifiers
• Learn about machine learning concepts in a computer vision context
• Work with artificial neural networks using OpenCV
• Develop your own computer vision real-life application

OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV’s API will enable the development of all sorts of real-world applications, including security and surveillance.

Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application.

This book is a comprehensive guide to the brand new OpenCV 3 with Python to develop real-life computer vision applications.

Источник

Learning OpenCV 3 Computer Vision with Python, 2nd Edition

OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV’s API will enable the development of all sorts of real-world applications, including security and surveillance.

Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application.

• Install and familiarize yourself with OpenCV 3’s Python API
• Grasp the basics of image processing and video analysis
• Identify and recognize objects in images and videos
• Detect and recognize faces using OpenCV
• Train and use your own object classifiers
• Learn about machine learning concepts in a computer vision context
• Work with artificial neural networks using OpenCV
• Develop your own computer vision real-life application

You can also get this PDF by using our Android Mobile App directly:

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