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    Computer Vision with Python 3

    Posted By: AlenMiler
    Computer Vision with Python 3

    Computer Vision with Python 3 by Saurabh Kapur
    English | 24 Aug. 2017 | ISBN: 1788299760 | ASIN: B072LN59CJ | 206 Pages | AZW3 | 6.53 MB

    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,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.

    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

    About the Author

    Saurabh Kapur is a computer science student at Indraprastha Institute of Information Technology, Delhi.

    His interests are in computer vision, numerical analysis, and algorithm design. He often spends time solving competitive programming questions. Saurabh also enjoys working on IoT applications and tinkering with hardware.

    He likes to spend his free time playing or watching cricket. He can be reached at saurabhkapur96@gmail.com.

    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