The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines"

Last update: Jan 02, 2023

Overview

MangaLineExtraction_PyTorch

The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines"

Usage

model_torch.py [source folder] [output folder]

Example:

model_torch.py ./pytorchTestCases/ ./pytorchResults/

The model weights (erika.pth)

Please refer to the release section of this repo. Alternatively, you may use this link:

https://www.dropbox.com/s/y8pulix3zs73y62/erika.pth?dl=0

Requirement

Python3
PyTorch (tested on version 1.9)
Python-opencv

How the model is prepared

The PyTorch weights are exactly the same as the theano(!) model. I make some efforts to convert the original weights to the new model and ensure the overall error is less than 1e-3 over the image range from 0-255.

Moreover, the functional PyTorch interface allows easier fine-tuning of this model. You can also take the whole model as a sub-module for your own work (e.g., use the on-the-fly extraction of lines as a structural constraint).

About model training

I really don't want to admit it, but the legacy code looks like some artworks by a two-years old. I will try my best to recover the code to py3 and share the screentone dataset. This won't take long, so please stay tuned.

Go beyond manga

Surprisingly, this model works quite well on color cartoons and other nijigen-like images. Simply load the image as grayscale(by default) and check out the results!

Gallery

I'm glad to share some of the results of this model. Some of the images are copyrighted, I will list the original sources below the images. Feel free to share your creaions with me in the issues section.

©IWAYUU, from the fc2 blog.

BibTeX:

@article{li-2017-deep,
    author   = {Chengze Li and Xueting Liu and Tien-Tsin Wong},
    title    = {Deep Extraction of Manga Structural Lines},
    journal  = {ACM Transactions on Graphics (SIGGRAPH 2017 issue)},
    month    = {July},
    year     = {2017},
    volume   = {36},
    number   = {4},
    pages    = {117:1--117:12},
}

Credit:

Xueting Liu and Tien-Tsin Wong, who contributed this work
Wenliang Wu, who inspired me to port this great thing to PyTorch
Toda Erika, where the project name comes from

Comments

Slow extraction

Hi,

How to speed up the line extraction? Could you elaborate on how to use the on-the-fly extraction?

I'm a bit new to all of this, please patient with me. Thank you!

opened by austin2209 7
'Toda Erika, where the project name comes from'

Maybe this is not something like an issue but is this Toda Erika the Japanese actress? If so, I wonder why this project name comes from her(Just a little curious about this because it seems that the name is not so special. If this question is impolite I apologize first).

opened by MayuOshima 2

Releases(v1)

v1(Sep 5, 2021)

Place this model weight in the root folder of this project to make it work.
Source code(tar.gz)
Source code(zip)
erika.pth(164.78 MB)

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The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines"

Related tags

Overview

MangaLineExtraction_PyTorch

Usage

The model weights (erika.pth)

Requirement

How the model is prepared

About model training

Go beyond manga

Gallery

BibTeX:

Credit:

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Comments

Slow extraction

'Toda Erika, where the project name comes from'

Releases(v1)

v1(Sep 5, 2021)

Owner

Miaomiao Li

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