Introduction

pypdn is a Python package for reading Paint.NET (PDN) images.

"Paint.NET is image and photo editing software for PCs that run Windows. It features an intuitive and innovative user interface with support for layers, unlimited undo, special effects, and a wide variety of useful and powerful tools. An active and growing online community provides friendly help, tutorials, and plugins."

When using Paint.NET, the default file format that the images are saved in are PDN's, which is a proprietary format Paint.NET uses. The benefit of this format over BMP, PNG, JPEG, etc is that it stores layer information and properties that are not present in traditional image formats.

You can get Paint.NET here.

Paint.NET is developed using C# (hence the .NET). Besides a basic XML header at the beginning, it primarily uses the BinaryFormatter class in C# to save the relevant classes when saving an image. This uses the NRBF protocol. A custom reader was developed to read the NRBF file and then this library essentially just parses the data from NRBF into more readable and user-friendly format. You can access the NRBF reader from the pypdn module as well in case you have any use for it.

Installing

Prerequisites

• Python 3.4+

• Dependencies:

  • numpy
  • aenum

Installing pypdn

pypdn is currently available on PyPi. The simplest way to install alone is using pip at a command line:

pip install pypdn

which installs the latest release. To install the latest code from the repository (usually stable, but may have undocumented changes or bugs):

pip install git+https://github.com/addisonElliott/pypdn.git

For developers, you can clone the pypdn repository and run the setup.py file. Use the following commands to get a copy from GitHub and install all dependencies:

git clone pip install git+https://github.com/addisonElliott/pypdn.git
cd pypdn
pip install .

or, for the last line, instead use:

pip install -e .

to install in 'develop' or 'editable' mode, where changes can be made to the local working code and Python will use the updated code.

Test and coverage

To test the code on any platform, make sure to clone the GitHub repository to get the tests and run the following from the repository directory:

python -m unittest discover -v tests

Example

For the below example, any PDN file will do. If you are looking for an example, check out the tests/data directory for some!

import pypdn
import matplotlib.pyplot as plt

layeredImage = pypdn.read('Untitled3.pdn')
print(layeredImage)
# Contains width, height, version and layers of the image within the class
# Version being the Paint.NET version that the image was saved with

# Each layer contains the name, visibility boolean, opacity (0-255), isBackground and blendMode
# From what I can tell, the isBackground property is not that useful
# The blend mode is how the layer should be blended with the layers below it
# These attributes are loaded from the PDN file but can be edited in the code as well
print(layeredImage.layers)
layer = layeredImage.layers[0]
layer.visible = True
layer.opacity = 255
layer.blendMode = pypdn.BlendType.Normal

layer = layeredImage.layers[1]
layer.visible = True
layer.opacity = 161
layer.blendMode = pypdn.BlendType.Additive

# Finally, the most useful thing is being able to combine the layers and flattn them into one image
# Call the flatten function to do so
# It will go through each layer and apply them IF the visibility is true!
# The layer opacity and blend mode will be taken into effect
#
# The flattened image is a RGBA Numpy array image
# The asByte parameter determines the data type of the flattened image
# If asByte is True, then the dtype will be uint8, otherwise it will be a float in range (0.0, 1.0)
flatImage = layeredImage.flatten(asByte=True)

plt.figure()
plt.imshow(flatImage)

# Individual layer images can be retrieved as well
# Note: This does NOT apply blending or the layer opacity
# Rather, it is the image data that is saved by Paint.NET for the layer
plt.figure()
plt.imshow(layeredImage.layers[1].image)

plt.show()

Using the Untitled3.pdn in the tests/data directory, this is the text output:

>>> print(layeredImage)
pypdn.LayeredImage(width=800, height=600, version=System_Version(Major=4, Minor=21, Build=6589, Revision=7045), layers=[pypdn.Layer(name=Background, visible=True, isBackground=True, opacity=255, blendMode=<BlendType.Normal: 0>), pypdn.Layer(name=Layer 2, visible=True, isBackground=False, opacity=161, blendMode=<BlendType.Additive: 2>)])

>>> print(layeredImage.layers)
[pypdn.Layer(name=Background, visible=True, isBackground=True, opacity=255, blendMode=<BlendType.Normal: 0>), pypdn.Layer(name=Layer 2, visible=True, isBackground=False, opacity=161, blendMode=<BlendType.Additive: 2>)]

Roadmap & Bugs

• Write docstrings and create basic documentation for NRBF and PDN classes
• Fix issue where _id and _classID are mixed up in NRBF reader
• Add support for writing NRBF files
• Write unit tests for NRBF
• Add support for writing PDN files (must complete writing NRBF files first)

Pull requests are welcome (and encouraged) for any or all issues!

License

pypdn has an MIT-based license.