MARVEL: Raster Gray-level Manga Vectorization via Primitive-wise Deep Reinforcement Learning

A PyTorch implementation of "MARVEL: Raster Gray-level Manga Vectorization via Primitive-wise Deep Reinforcement Learning". If the paper or code is useful for your research, please cite

 @article{su2023marvel,
  title={MARVEL: Raster Gray-level Manga Vectorization via Primitive-wise Deep Reinforcement Learning},
  author={Su, Hao and Liu, Xuefeng and Niu, Jianwei and Cui, Jiahe and Wan, Ji and Wu, Xinghao and Wang, Nana},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2023},
  publisher={IEEE}
}

or

@article{su2021vectorization,
  title={Vectorization of Raster Manga by Deep Reinforcement Learning},
  author={Su, Hao and Niu, Jianwei and Liu, Xuefeng and Cui, Jiahe and Wan, Ji},
  journal={arXiv preprint arXiv:2110.04830},
  year={2021}
}

Demos

Prerequisites

• Linux or Windows
• CPU or NVIDIA GPU + CUDA CuDNN
• Python 3
• Pytorch 1.7.0

Getting Started

Installation

• Clone this repo:

    git clone https://github.com/SwordHolderSH/Mang2Vec.git
    cd Mang2Vec

• Install PyTorch and other dependencies.
• Download actor.pkl from Google Drive to path './model/'.

Quick Start

• Get detailed information about all parameters using

    python main.py -h

• Generate your customized vectorized mangas:

    python main.py --img=./image/Naruto.png --actor=./model/actor.pkl  --max_step=40 --divide=32

Acknowledge

Thanks for the reference codes of ICCV2019-LearningToPaint.