Neural style transfer (NST) refers to a class of software algorithms that manipulate digital images, or videos, in order to adopt the appearance or visual style of another image. NST algorithms are characterized by their use of deep neural networks for the sake of image transformation. Common uses for NST are the creation of artificial artwork from photographs, for example by transferring the appearance of famous paintings to user-supplied photographs.
This is a pytorch implementation of A Neural Algorithm of Artistic Style.
Code is developed under following library dependencies
python 3.7
torch 1.12.0
torchtext 0.13
torchvision 0.13
Start with creating a virtual environment then open your terminal and follow the following steps:
git clone "https://github.com/zaghlol94/neural-style-transfer-pytorch"
cd neural-style-transfer-pytorch
pip install -r requirements.txt
python nst.py -o "original image path" -s "style image path"
@misc{https://doi.org/10.48550/arxiv.1508.06576,
doi = {10.48550/ARXIV.1508.06576},
url = {https://arxiv.org/abs/1508.06576},
author = {Gatys, Leon A. and Ecker, Alexander S. and Bethge, Matthias},
keywords = {Computer Vision and Pattern Recognition (cs.CV), Neural and Evolutionary Computing (cs.NE), Neurons and Cognition (q-bio.NC), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Biological sciences, FOS: Biological sciences},
title = {A Neural Algorithm of Artistic Style},
publisher = {arXiv},
year = {2015},
copyright = {arXiv.org perpetual, non-exclusive license}
}