/DeepCreamPyLab

Decensoring Hentai with Deep Neural Networks on Google Colab.

Primary LanguagePythonGNU Affero General Public License v3.0AGPL-3.0

DeepCreamPyLab

Decensoring Hentai with Deep Neural Networks on Google Colab.

Open In Colab

A deep learning-based tool to automatically replace censored artwork in hentai with plausible reconstructions.

Before DeepCreamPy can be used, the user must color censored regions in their hentai green with an image editing program like GIMP or Photoshop. DeepCreamPy takes the green colored images as input, and a neural network automatically fills in the censored regions.

Features

  • Decensoring images of any size
  • Decensoring of ANY shaped censor (e.g. black lines, pink hearts, etc.)
  • Decensoring of mosaic decensors
  • Limited support for decensoring black and white/monochrome images
  • Generate multiple variations of decensors from the same image

Limitations

The decensorship is for color hentai images that have minor to moderate censorship of the pen-s or vag-na. If a vag-na or pen-s is completely censored out, decensoring will be ineffective.

It does NOT work with:

  • Hentai with screentones (e.g. printed hentai)
  • Real life porn
  • Censorship of nipples
  • Censorship of anus
  • Animated gifs/videos

Usage:

Miscellaneous:

Special thanks to deeppomf, style00dollar, ccppoo, IAmTheRedSpy, 0xb8, deniszh, Smethan, harjitmoe, itsVale, StartleStars, and SoftArmpit for their contributions!

License

Source code and official releases/binaries are distributed under the GNU Affero General Public License v3.0.

Acknowledgements

Example mermaid image by Shurajo & AVALANCHE Game Studio under CC BY 3.0 License. The example image is modified from the original, which can be found here.

Neural network code is modified from Forty-lock's project PEPSI, which is the official implementation of the paper PEPSI : Fast Image Inpainting With Parallel Decoding Network. PEPSI is licensed under the MIT license.

Training data is modified from gwern's project Danbooru2017: A Large-Scale Crowdsourced and Tagged Anime Illustration Dataset and other sources.

See ACKNOWLEDGEMENTS.md for full license text of these projects.