MSG-Net Style Transfer Example¶

We provide PyTorh Implementation of MSG-Net and Neural Style in the GitHub repo. We also provide Torch and MXNet implementations.

Tabe of content¶

Real-time Style Transfer using MSG-Net
- Stylize Images using Pre-trained Model
- Train Your Own MSG-Net Model
Neural Style

MSG-Net¶

Note

Hang Zhang, and Kristin Dana. “Multi-style Generative Network for Real-time Transfer.”:

@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}
}

Stylize Images Using Pre-trained Model¶

Clone the repo and download the pre-trained model:

git clone git@github.com:zhanghang1989/PyTorch-Style-Transfer.git
cd PyTorch-Style-Transfer/experiments
bash models/download_model.sh

Camera Demo:

python camera_demo.py demo --model models/9styles.model

Test the model:
```
python main.py eval --content-image images/content/venice-boat.jpg --style-image images/9styles/candy.jpg --model models/9styles.model --content-size 1024
```
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.

Train Your Own MSG-Net Model¶

Download the 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.

Neural Style¶

Image Style Transfer Using Convolutional Neural Networks by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge:

python main.py optim --content-image images/content/venice-boat.jpg --style-image images/9styles/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.