This repo has been included in official MXNet repo, which provides the implementations of MSG-Net and Neural Style Transfer. We also provide PyTorch and Torch implementations.
Tabe of content
A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge.
python main.py optim --content-image images/content/venice-boat.jpg --style-image images/styles/candy.jpg--content-image: path to content image.--style-image: path to style image.--output-image: path for saving the output image.--content-size: the content image size to test on.--style-size: the style image size to test on.--cuda: set it to 1 for running on GPU, 0 for CPU.
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Multi-style Generative Network for Real-time Transfer [arXiv] [project] Hang Zhang, Kristin Dana @article{zhang2017multistyle,
title={Multi-style Generative Network for Real-time Transfer},
author={Zhang, Hang and Dana, Kristin},
journal={arXiv preprint arXiv:1703.06953},
year={2017}
}
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- Download the pre-trained model
python models/download_model.py
- Test the model
python main.py eval --content-image images/content/venice-boat.jpg --style-image images/styles/candy.jpg --model models/21styles.params --content-size 1024
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If you don't have a GPU, simply set
--cuda=0. For a different style, set--style-image path/to/style. If you would to stylize your own photo, change the--content-image path/to/your/photo. More options:--content-image: path to content image you want to stylize.--style-image: path to style image (typically covered during the training).--model: path to the pre-trained model to be used for stylizing the image.--output-image: path for saving the output image.--content-size: the content image size to test on.--cuda: set it to 1 for running on GPU, 0 for CPU.
- Download the COCO dataset
bash dataset/download_dataset.sh
- Train the model
python main.py train --epochs 4
- If you would like to customize styles, set
--style-folder path/to/your/styles. More options:--style-folder: path to the folder style images.--vgg-model-dir: path to folder where the vgg model will be downloaded.--save-model-dir: path to folder where trained model will be saved.--cuda: set it to 1 for running on GPU, 0 for CPU.
The code is mainly modified from PyTorch-Style-Transfer.