OpenCV 4 with Python Blueprints

By : Dr. Menua Gevorgyan , Michael Beyeler (USD), Mamikonyan, Michael Beyeler

5 (4)

Buy this Book

OpenCV 4 with Python Blueprints

5 (4)

By: Dr. Menua Gevorgyan , Michael Beyeler (USD), Mamikonyan, Michael Beyeler

Buy this Book

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.

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Fun with Filters

Getting started

Planning the app

Creating a black-and-white pencil sketch

Generating a warming and cooling filter

Cartoonizing an image

Putting it all together

Summary

Attributions

Free Chapter

Hand Gesture Recognition Using a Kinect Depth Sensor

Getting started

Planning the app

Setting up the app

Tracking hand gestures in real time

Understanding hand region segmentation

Performing hand shape analysis

Performing hand gesture recognition

Summary

Finding Objects via Feature Matching and Perspective Transforms

Getting started

Listing the tasks performed by the app

Planning the app

Setting up the app

Understanding the process flow

Learning feature extraction

Understanding feature matching

Learning feature tracking

Seeing the algorithm in action

Summary

Attributions

3D Scene Reconstruction Using Structure from Motion

Getting started

Planning the app

Learning about camera calibration

Setting up the app

Estimating the camera motion from a pair of images

Reconstructing the scene

Understanding 3D point cloud visualization

Learning about structure from motion

Summary

Using Computational Photography with OpenCV

Getting started

Planning the app

Understanding the 8-bit problem

Understanding high-dynamic-range imaging

Understanding panorama stitching

Summary

Planning the app

The final app must consist of the following modules and scripts:

wx_gui.py: This module is our implementation of a basic GUI using wxpython. We will make extensive use of this file throughout the book. This module includes the following layouts:
- wx_gui.BaseLayout: This is a generic layout class from which more complicated layouts can be built.
chapter1.py: This is the main script for this chapter. It contains the following functions and classes:
- chapter1.FilterLayout: This is a custom layout based on wx_gui.BaseLayout, which displays the camera feed and a row of radio buttons that allows the user to select from the available image filters to be applied to each frame of the camera feed.
- chapter1.main: This is the main routine function for starting the GUI application and accessing the webcam.
tools.py: This is a Python module and has a lot of helper functions...