Book Image

Python Multimedia

By : Ninad Sathaye
Book Image

Python Multimedia

By: Ninad Sathaye

Overview of this book

Multimedia applications are used by a range of industries to enhance the visual appeal of a product. This book will teach the reader how to perform multimedia processing using Python. This step-by-step guide gives you hands-on experience for developing exciting multimedia applications using Python. This book will help you to build applications for processing images, creating 2D animations and processing audio and video. Writing applications that work with images, videos, and other sensory effects is great. Not every application gets to make full use of audio/visual effects, but a certain amount of multimedia makes any application a lot more appealing. There are numerous multimedia libraries for which Python bindings are available. These libraries enable working with different kinds of media, such as images, audio, video, games, and so on. This book introduces the reader to the most widely used open source libraries through several exciting, real world projects. Popular multimedia frameworks and libraries such as GStreamer,Pyglet, QT Phonon, and Python Imaging library are used to develop various multimedia applications.
Table of Contents (13 chapters)
Python Multimedia Beginner's Guide
Credits
About the Author
About the Reviewers
Preface

Blending


Have you ever wished to see yourself in a family photo, taken at a time when you were not around? Or what if you just want to see yourself at the top of Mount Everest at least in a picture? Well, it is possible to do this digitally, using the functionality provided in PIL such as blending, composite image processing, and so on.

In this section, we will learn how to blend images together. As the name suggests, blending means mixing two compatible images to create a new image. The blend functionality in PIL creates a new image using two input images of the same size and mode. Internally, the two input images are interpolated using a constant value of alpha.

In the PIL documentation, it is formulated as:

blended_image = in_image1 * (1.0 - alpha) + in_image2 * alpha

Looking at this formula, it is clear that alpha = 1.0 will make the blended image the same as 'n_image2 whereas alpha = 0.0 returns in_image1 as the blended image.