Computer Vision with Python 3

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