pastiche A literary, artistic, musical, or architectural work that imitates the style of previous work.―Merriam-Webster dictionary
Update 1/20/2021: The command line usage snippets were updated in accordance with
I recently implemented pastiche, a PyTorch-based Python program for applying neural style transfer . Given a content image C and a style image S, neural style transfer (NST) synthesizes a new image I that retains the content from C and style from S. This is achieved by iteratively updating I so that relevant properties of its representation within the VGG neural network  approach the corresponding properties for C and S.
The library is available on PyPI and can be installed with pip.
$ pip3 install pastiche
The command line usage is shown below. Use
--help to access documentation for the additional options (e.g.,
--device for controlling whether to use a CPU or GPU).
$ pastiche \ --content CONTENT \ --styles STYLE [STYLE ..] \ --output OUTPUT
CONTENT is the path to the content image,
STYLE is a path to a style image, and
OUTPUT is the path to save the synthesized pastiche PNG file.
If the launcher script was not installed within a directory on your
PATH, pastiche can be launched by passing its module name to Python.
$ python3 -m pastiche \ --content CONTENT \ --styles STYLE [STYLE ..] \ --output OUTPUT
The source code is available on GitHub:
--preserve-color option can be used to retain colors from the content image.
 Gatys, Leon A., Alexander S. Ecker, and Matthias Bethge. “A Neural Algorithm of Artistic Style.” ArXiv:1508.06576 [Cs, q-Bio], August 26, 2015. http://arxiv.org/abs/1508.06576.
 Gatys, Leon A., Alexander S. Ecker, Matthias Bethge, Aaron Hertzmann, and Eli Shechtman. “Controlling Perceptual Factors in Neural Style Transfer.” ArXiv:1611.07865 [Cs], November 23, 2016. http://arxiv.org/abs/1611.07865.
 Simonyan, Karen, and Andrew Zisserman. “Very Deep Convolutional Networks for Large-Scale Image Recognition.” ArXiv:1409.1556 [Cs], September 4, 2014. http://arxiv.org/abs/1409.1556.