Bidirectional Translation

Pytorch implementation for multimodal comic-to-manga translation.

Note: The current software works well with PyTorch 1.6.0+.

Prerequisites

Linux
Python 3
CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

Clone this repo:

git clone https://github.com/msxie/ScreenStyle.git
cd ScreenStyle/MangaScreening

Install PyTorch and dependencies from http://pytorch.org
Install python libraries tensorboardX
Install other libraries For pip users:

pip install -r requirements.txt

Data praperation

The training requires paired data (including manga image, western image and their line drawings). The line drawing can be extracted using MangaLineExtraction.

${DATASET} 
|-- color2manga 
|   |-- val 
|   |   |-- ${FOLDER}
|   |   |   |-- imgs
|   |   |   |   |-- 0001.png 
|   |   |   |   |-- ...
|   |   |   |-- line
|   |   |   |   |-- 0001.png 
|   |   |   |   |-- ...

Use a Pre-trained Model

Download the pre-trained ScreenVAE model and place under checkpoints/ScreenVAE/ folder.
Download the pre-trained color2manga model and place under checkpoints/color2manga/ folder.
Generate results with the model

bash ./scripts/test_western2manga.sh

Copyright and License

You are granted with the LICENSE for both academic and commercial usages.

Citation

If you find the code helpful in your resarch or work, please cite the following papers.

@article{xie-2020-manga,
        author   = {Minshan Xie and Chengze Li and Xueting Liu and Tien-Tsin Wong},
        title    = {Manga Filling Style Conversion with Screentone Variational Autoencoder},
        journal  = {ACM Transactions on Graphics (SIGGRAPH Asia 2020 issue)},
        month    = {December},
        year     = {2020},
        volume   = {39},
        number   = {6},
        pages    = {226:1--226:15}
    }

Acknowledgements

This code borrows heavily from the pytorch-CycleGAN-and-pix2pix repository.