A sketch extractor for anime/illustration.

Overview

Anime2Sketch

Anime2Sketch: A sketch extractor for illustration, anime art, manga

By Xiaoyu Xiang

teaser demo

Updates

  • 2021.5.2: Upload more example results of anime video.
  • 2021.4.30: Upload the test scripts. Now our repo is ready to run!
  • 2021.4.11: Upload the pretrained weights, and more test results.
  • 2021.4.8: Create the repo.

Introduction

The repository contains the testing codes and pretrained weights for Anime2Sketch.

Anime2Sketch is a sketch extractor that works well on illustration, anime art, and manga. It is an application based on the paper "Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis".

Prerequisites

Get Started

Installation

Install the required packages: pip install -r requirements.txt

Download Pretrained Weights

Please download the weights from GoogleDrive, and put it into the weights/ folder.

Test

python3 test.py --dataroot /your_input/dir --load_size 512 --output_dir /your_output/dir

The above command includes three arguments:

  • dataroot: your test file or directory
  • load_size: due to the memory limit, we need to resize the input image before processing. By default, we resize it to 512x512.
  • output_dir: path of the output directory

Run our example:

python3 test.py --dataroot test_samples/madoka.jpg --load_size 512 --output_dir results/

Train

This project is a sub-branch of AODA. Please check it for the training instructions.

More Results

Our model works well on illustration arts: madoka demo demo1 Turn handrawn photos to clean linearts: demo2 Simplify freehand sketches: demo3 And more anime results: demo4 demo5

Contact

Xiaoyu Xiang.

You can also leave your questions as issues in the repository. I will be glad to answer them!

License

This project is released under the MIT License.

Citations

@misc{Anime2Sketch,
  author = {Xiaoyu Xiang, Ding Liu, Xiao Yang, Yiheng Zhu, Xiaohui Shen},
  title = {Anime2Sketch: A Sketch Extractor for Anime Arts with Deep Networks},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/Mukosame/Anime2Sketch}}
}

@misc{xiang2021adversarial,
      title={Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis}, 
      author={Xiang, Xiaoyu and Liu, Ding and Yang, Xiao and Zhu, Yiheng and Shen, Xiaohui and Allebach, Jan P},
      year={2021},
      eprint={2104.05703},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
Owner
Xiaoyu Xiang
Ph.D. candidate at Purdue University.
Xiaoyu Xiang
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