MSG-Net Style Transfer Example

../_images/figure1.jpg

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

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
    
../_images/myimage.gif
  • 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.