Python pixel glitcher -- disturbs image data to create cool effects
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testfilter.txt

README.md

PPG

Python Pixel Glitcher -- Disturbs image data to create cool effects

Overview

PPG mostly consists of a set of filters for buliding image-glitching pipelines. It consists of a C module which implements the actual filters, and some Python bindings that allow them to easily be stitched together.

While image glitching is usually performed by manipulating the compressed binary data of an image file, PPG takes a different approach. PPG applies transforms to actual decoded images, then introduces errors to the transformed data before reversing the transform to obtain an altered image. Some more information about the philosophy behind PPG can be found at: http://lo.calho.st/projects/adventures-in-image-glitching/

Building the C module

A Makefile is provided for convenience. If you have the necessary Python development packages, then the Makefile should take care of everything else for you and produce the required ppgfilter.so.

Using the Python module

The dependencies of the Python module are listed in requirements.txt. It is written for Python 2.7 but might also work in Python 3 with a few changes...

Your main interface to PPG's functionality is through the "filter" module. All of the image transformations are implemented here.

PPG's filters operate on images represented as Numpy arrays. An image is essentially a three-dimensional array -- two dimensions are the dimensions of the actual image, and the third separates the R/G/B (and sometimes A) color channels. A convenience module, "codec," is provided to allow images to be imported in this format (and exported from it).

To create glitch effects in an image, you must combine a transforming filter with a corrupting filter. Currently, the following transforming filters are supported:

  • SubFilter
  • UpFilter
  • PaethFilter
  • BrokenPaethFilter
  • AverageFilter
  • BrokenAverageFilter
  • RandomLineFilter

And a single corrupting filter, the UniformGlitchFilter.

Each of these filters has its own documentation if you want to learn about how they work.

To combine filters and obtain interesting effects, you can utilize the FilterStack and FilterChain classes; these act the same as any other filter, and you can actually combine them arbitrarily. FilterStack and FilterChain differ in their orderings of the encode (transform) and decode (reverse transform) operations. A FilterChain will execute each filter in the chain by running encode, then running decode consecutively. However, a FilterStack will run the encode operations for all of the filters it contains, then run the decode operations in the reverse order.

FilterStacks are necessary to allow the effects of a corrupting filter to propagate; first, a transform must be applied, then the corruption, then a reverse transform -- the FilterStack facilitates this. On the other hand, FilterChains allow additional layers of glitches to be added.

For an example of the usage of FilterChains and FilterStacks, take a look at example.py.

Plaintext filter representations

The ppg.parser module defines a language suitable for defining filter pipelines without actually writing Python code.

In this language, you can define FilterChains, FilterStacks, and regular filters, and pass configuration parameters as required.

To create a FilterChain, simply wrap the contents of the chain in ( regular parenthesis ). To create a FilterStack, wrap its contents in [ square brackets ]. The contents should be comma-separated in both cases.

To instantiate a regular Filter, simply state its name. To pass key-value pairs of configuration arguments to this filter, create add a configuration object after the filter's name. A configuration object is surrounded by { curly braces } and contains a comma-separated list of key-value pairs, where each pair is in the format "key=value".

A value in a configuration object may be a list, in which case it should be wrapped in [ square brackets ] and comma-separated in the normal way. String literals in the configurations do not need to be put in quotes (though the quotes will be silently ignored if included).

For an example of a filter chain defined in this format, refer to testfilter.txt.

Using the example script

Two example scripts are included in this repository. One uses the Python module directly, and the other uses the plaintext filter definition language.

example1.py contains a hardcoded filter chain suitable for producing decent glitch effects on most images. It takes four command line parameters: input filename, output filename, glitch multiplier (optional), and quiet (optional). The glitch multiplier is a float scalar. The quiet param will suppress the performance output if its value is "quiet" or "q".

For example (default behavior):

 $ python example.py input.jpg output.jpg
 [+] FilterChain starting
    [+] FilterStack starting
        [+] Encoded with RandomLineFilter in 0.003s.
        [+] Encoded with UniformGlitchFilter in 0.001s.
        [-] Decoded with UniformGlitchFilter in 0.000s.
        [-] Decoded with RandomLineFilter in 0.002s.
    [+] Encoded with FilterStack in 0.006s.
    [-] Decoded with FilterStack in 0.000s.
    [+] FilterStack starting
        [+] Encoded with BrokenPaethFilter in 0.007s.
        [+] Encoded with UniformGlitchFilter in 0.002s.
        [-] Decoded with UniformGlitchFilter in 0.000s.
        [-] Decoded with BrokenPaethFilter in 0.008s.
    [+] Encoded with FilterStack in 0.016s.
    [-] Decoded with FilterStack in 0.000s.
    [+] FilterStack starting
        [+] Encoded with BrokenAverageFilter in 0.002s.
        [+] Encoded with UniformGlitchFilter in 0.001s.
        [-] Decoded with UniformGlitchFilter in 0.000s.
        [-] Decoded with BrokenAverageFilter in 0.002s.
    [+] Encoded with FilterStack in 0.005s.
    [-] Decoded with FilterStack in 0.000s.
[+] FilterChain finished in 0.028s.

For example (50% glitchiness, quiet):

 $ python example.py input.jpg output.jpg 0.5 quiet

For example (200% glitchiness, quiet):

 $ python example.py input.jpg output.jpg 2.0 quiet

example2.py allows a plaintext filter chain definition to be loaded from a file. The arguments to this script are: input image filename, output image filename, filter definition (optional), and quiet (optional). The input/output filenames and the quiet option behave the same as they do in example1.py. The default filter definition file, if one is not specified, is testfilter.txt.

Documentation

Docstrings are included for this entire package. There is also a convenience method in the Makefile to compile the documentation: make docs. The convenience method requires pdoc to be installed.