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

Time for action – smoothing an image


Let's work out an example where a smoothing filter will be applied to an image.

  1. Download the image file 0165_3_Before_SMOOTHING.png from the Packt website and save it as Before_SMOOTHING.png.

  2. This is a low-resolution image scanned from a developed photograph. As you can see, there is a lot of salt-and-pepper noise in the image. We will apply smoothing filter to reduce some of this noise in the image data.

  3. Add the following code in a Python file.

    import ImageFilter
    import Image
    
    img = Image.open( "C:\\images\\Before_SMOOTH.png ")
    img = img.filter(ImageFilter.SMOOTH)
    img.save( "C:\\images\\ch3\\After_SMOOTH.png")
    img.show()
  4. The highlighted line in the code is where the smoothing filter is applied to the image. The results are shown in the next illustration.

    Picture before and after smoothing:

  5. To reduce the noise further down, you can use ImageFilter.SMOOTH_MORE or try reapplying the ImageFilter.SMOOTH multiple times until you get the desired effect.

    import ImageFilter...