Awesome
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
<div align=center><img src="https://github.com/SwordHolderSH/Mang2Vec/blob/main/image/demo1.jpg" width="1000" /></div> <div align=center><img src="https://github.com/SwordHolderSH/Mang2Vec/blob/main/image/demo2.jpg" width="1000" /></div> <div align=center><img src="https://github.com/SwordHolderSH/Mang2Vec/blob/main/image/demo3.jpg" width="1000" /></div>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.pklfrom 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.