Book Image

OpenCV 4 with Python Blueprints - Second Edition

By : Dr. Menua Gevorgyan, Arsen Mamikonyan, Michael Beyeler
Book Image

OpenCV 4 with Python Blueprints - Second Edition

By: Dr. Menua Gevorgyan, Arsen Mamikonyan, Michael Beyeler

Overview of this book

OpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks. You’ll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you’ll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you’ll understand how to align images, and detect and track objects using neural networks. By the end of this OpenCV Python book, you’ll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs.
Table of Contents (14 chapters)
Profiling and Accelerating Your Apps
Setting Up a Docker Container

Fun with Filters

The goal of this chapter is to develop a number of image processing filters and then apply them to the video stream of a webcam in real time. These filters will rely on various OpenCV functions to manipulate matrices through splitting, merging, arithmetic operations, and applying lookup tables for complex functions.

We will cover the following three effects, which will help familiarize you with OpenCV, and we will build on these effects in future chapters of this book:

  • Warming and cooling filters: We will implement our own curve filters using a lookup table.
  • Black-and-white pencil sketch: We will make use of two image-blending techniques, known as dodging and burning.
  • Cartoonizer: We will combine a bilateral filter, a median filter, and adaptive thresholding.

OpenCV is an advanced toolchain. It often raises the question, that is, not how to implement something...