Book Image

Mastering openFrameworks: Creative Coding Demystified

By : Denis Perevalov
Book Image

Mastering openFrameworks: Creative Coding Demystified

By: Denis Perevalov

Overview of this book

openFrameworks is a powerful programming toolkit and library designed to assist the creative process through simplicity and intuitiveness. It's a very handy software library written in C++ to reduce the software development process, helping you to kick-start creative coding. With the help of C++ and shaders support, openFrameworks allows for the processing of all kinds of media information with your custom-developed algorithms at the lowest possible level, with the fastest speed. "Mastering openFrameworks: Creative Coding Demystified" will introduce you to a world of creative coding projects, including interactive installations, audio-visual, and sound art projects. You will learn how to make your own projects using openFrameworks. This book focuses on low-level data processing, which allows you to create really unique and cutting-edge installations and projects. "Mastering openFrameworks: Creative Coding Demystified" provides a complete introduction to openFrameworks, including installation, core capabilities, and addons. Advanced topics like shaders, computer vision, and depth cameras are also covered. We start off by discussing the basic topics such as image and video loading, rendering and processing, playing sound samples, and synthesizing new sounds. We then move on to cover 3D graphics, computer vision, and depth cameras. You will also learn a number of advanced topics such as video mapping, interactive floors and walls, video morphing, networking, and using geometry shaders. You will learn everything you need to know in order to create your own projects; create projects of all levels, ranging from simple creative-code experiments, to big interactive systems consisting of a number of computers, depth cameras, and projectors.
Table of Contents (22 chapters)
Mastering openFrameworks: Creative Coding Demystified
About the Author
About the Reviewers

Getting spectral data from sound

PCM sound representation is good for sound storage and playing. It lets us operate sound samples like a piece of magnetic tape—to cut, shuffle its parts, reverse, and glue back together. Also it lets us change and measure the overall volume of the sound. But PCM is inadequate for more advanced sound analysis and processing. The reason being that humans cannot hear separate audio samples, only frequencies in sound in short time intervals. The collection of amplitudes of each frequency in a short time interval is called spectrum of the sound. Therefore, sound processing methods should work using frequencies-spectrum language. This differs sound processing from image and video processing as they work well with pixels independently.

In this section, we will not dip into the mathematical aspects of spectrum computing, but will learn how to compute it using the openFrameworks functions and use it in projects.

The spectrum in openFrameworks is calculated for sound...