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Tools to convert Pov-Ray DF3 files to set of images and vice versa

Project description

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Command-line tools to convert POV-Ray density files (DF3) to a bunch of images and vice versa.


The easiest way to install is via standard Python package manager:

pip install df3tools

Optionally, you may clone package’s repository, and run script:

git clone
cd df3tools
python install


After successful installation, two tools will be available at command-line: df3split and df3combine.

The former, by default, splits density file to a bunch of images and saves them into layerNNN.tga files in current directory:

df3split path-to-original-density-file.df3

The latter, by default, combines all layer* files in current directory into a single density file. Image format is auto-detected:

df3combine path-to-new-density-file.df3

You may also pass an images’ prefix like -p data/layer. See the full list of options below.


Split POV-Ray .df3 density file to a series of separate images.


df3split [-h] [-t {tga,png}] [-p PREFIX] [-s] df3file

Positional arguments:

df3file    Filename of density file to split.

Optional arguments:

-h, --help                        Show help message and exit.
-t {tga,png}, --format {tga,png}  Output files format.
-p PREFIX, --prefix PREFIX        Output files prefix.
-s, --silent                      Suppress output.


Combine a series of separate images into POV-Ray .df3 density file.


df3combine [-h] [-p PREFIX] [-s] df3file

Positional arguments:

df3file    Filename of density file to combine images into.

Optional arguments:

-h, --help                        Show help message and exit.
-p PREFIX, --prefix PREFIX        Input files prefix.
-s, --silent                      Suppress output.

Note, images format is autodetected. You may combine any type of images, supported by Pillow.


To run full test suite for all supported Python versions, install tox package, and run it from project’s top directory, containing

pip install tox

Optionally, you can run tests only for your current Python version by typing:

python -m unittest discover -s tests


Thanks to Yury Poberezhny for the idea and motivation to create this package.

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