OpenCV 3.x with Python By Example, 2/e

Gabriel Garrido, Prateek Joshi



Key Features

  • Learn how to apply complex visual effects to images with OpenCV 3 and Python
  • Extract features from an image and use them to develop advanced applications
  • Build algorithms to help you understand image content and perform visual searches

Book Description

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we are getting more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. This book will walk you through all the building blocks needed to build amazing computer vision applications with ease.

We start off by applying geometric transformations to images. We then discuss affine and projective transformations and see how we can use them to apply cool geometric effects to photos. We will then cover techniques used for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications. The book also covers popular OpenCV libraries with the help of examples. You will also learn about camera calibration and how to apply machine learning with artificial neural networks.

The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.

What you will learn

  • Detect shapes and edges from images and videos
  • How to apply filters on images and videos
  • Use different techniques to manipulate and improve images
  • Extract and manipulate particular parts of images and videos
  • Track objects or colors from videos
  • Recognize specific object or faces from images and videos
  • How to create Augmented Reality applications
  • Apply artificial neural networks and machine learning to improve object recognition