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STYLE2PAINTS

ZhiHu BiliBili GithubPage

Temp demo: https://style2paints.github.io/

The AI can paint on a sketch accroding to a given specific color style.

web_preview

web_preview2

Example 1 (Google Search results test)

google

A content sketch (the first google image search result of key word 'anime sketch') and some style images:

. . .

Results:

. . . .

. . . .

. . . .

Example 2 (western sketch)

A western content sketch and 2 style images:

. . . .

Example 3 (messy sketch)

A messy content sketch and 2 style images:

. . . .

. . .

Example 4 (detailed sketch)

A detailed content sketch and 2 style images:

. . . .

. . .

Example 5 (simple sketch)

A simple content sketch without shadow rendering and 2 style images:

. . . .

. . .

CPU Server for Beginner

you need a python 3 environment.

pip install tensorflow
pip install keras
pip install chainer
pip install bottle
pip install gevent
pip install h5py
pip install opencv-python
git clone https://github.com/lllyasviel/style2paints.git
(then download all pretrained models from 'release' page and then put them in 'style2paints/server')
cd style2paints/server
python server.py cpu

GPU Server for Reseachers

you need a CUDA python 3.6 environment.

pip install tensorflow_gpu
pip install keras
pip install chainer
pip install cupy
pip install bottle
pip install gevent
pip install h5py
pip install opencv-python
git clone https://github.com/lllyasviel/style2paints.git
(then download all pretrained models from 'release' page and then put them in 'style2paints/server')
cd style2paints/server
python server.py

Model

Models are avaliable in 'release' page.

  1. base_generator.net -> all rights reserved 2017 style2paints
  2. style2paints.net -> all rights reserved 2017 style2paints
  3. google_net.net -> from nico-opendata

Training Datasets

  1. The recommended training dataset of illustrations is the 400k images from nico-opendata

  2. The recommended training sketches is from sketchKeras

Community

QQ Group ID: 184467946

Acknowledgements

Thanks a lot to TaiZan. This project could not be achieved without his great help.

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sketch + style = paints !

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  • JavaScript 50.0%
  • Python 35.7%
  • CSS 10.3%
  • HTML 4.0%