[NulledPremium com] Computer Vision with Python 3 Use the power of Python for real-time

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Book details

File Size: 9.92 MB

Format: pdf

Print Length: 208 pages

Page Numbers Source ISBN: 1788299760

Publisher: Packt Publishing; 1 edition (August 24, 2017)

Publication Date: August 24, 2017

Sold by: Amazon Digital Services LLC

Language: English

ASIN: B072LN59CJ



Key Features



Learn how to build a full-fledged image processing application using free tools and libraries

Perform basic to advanced image and video stream processing with OpenCV’s Python APIs

Understand and optimize various features of OpenCV with the help of easy-to-grasp examples



Book Description



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,ExtendingyourCapabilitiesusingOpenCV,andGettingHandson. 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.



What you will learn Working with open source libraries such Pillow, Scikit-image, and OpenCV Writing programs such as edge detection, color processing, image feature extraction, and more Implementing feature detection algorithms like LBP and ORB Tracking objects using an external camera or a video file Optical Character Recognition using Machine Learning. Understanding Convolutional Neural Networks to learn patterns in images Leveraging Cloud Infrastructure to provide Computer Vision as a Service



Table of Contents

Introduction to Image

Processing Filters and Features

Drilling Deeper into features- detecting objects

Segmentation – Understanding Images Better Integrating Machine Learning with Computer Vision

Image Classification using Neural Networks

Introduction to Computer Vision using OpenCV Object Detection using OpenCV

Video Processing using open CV Computer Vision as a Service