OpenCV 3 Computer Vision with Python Cookbook
OpenCV 3 is a native cross-platform library for computer vision, machine learning, and image processing. OpenCV's convenient high-level APIs hide very powerful internals designed for computational efficiency that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems by providing a number of recipes that you can use to improve your applications.
In this book, you will learn how to process an image by manipulating pixels and analyze an image using histograms. Then, we'll show you how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. We’ll explore techniques to achieve camera calibration and perform a multiple-view analysis.
Later, you’ll work on reconstructing a 3D scene from images, converting low-level pixel information to high-level concepts for applications such as object detection and recognition. You’ll also discover how to process video from files or cameras and how to detect and track moving objects. Finally, you'll get acquainted with recent approaches in deep learning and neural networks.
By the end of the book, you’ll be able to apply your skills in OpenCV to create computer vision applications in various domains.
|Course Length||9 hours 10 minutes|
|Date Of Publication||23 Mar 2018|
|Reading images from files|
|Simple image transformations—resizing and flipping|
|Saving images using lossy and lossless compression|
|Showing images in an OpenCV window|
|Working with UI elements, such as buttons and trackbars, in an OpenCV window|
|Drawing 2D primitives—markers, lines, ellipses, rectangles, and text|
|Handling user input from a keyboard|
|Making your app interactive through handling user input from a mouse|
|Capturing and showing frames from a camera|
|Playing frame stream from video|
|Obtaining a frame stream properties|
|Writing a frame stream into video|
|Jumping between frames in video files|