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Last Commit
May. 22, 2019
Feb. 9, 2018


Decensoring Hentai with Deep Neural Networks.

DeepCreamPyV2 coming in Summer 2019

GitHub release GitHub downloads GitHub downloads GitHub issues Donate with PayPal Project license Twitter Follow

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

The user colors censored regions green in an image editing program like GIMP or Photoshop. A neural network fills in the censored regions.

DeepCreamPy has a pre-built binary for Windows 64-bit available here. DeepCreamPy's code works on Windows, Mac, and Linux.

Please before you open a new issue check closed issues and check the table of contents.


  • Decensoring images of ANY size
  • Decensoring of ANY shaped censor (e.g. black lines, pink hearts, etc.)
  • Higher quality decensors
  • Support for mosaic decensors (WIP)


The decensorship is for color hentai images that have minor to moderate censorship of the penis or vagina. If a vagina or penis is completely censored out, decensoring will be ineffective.

It does NOT work with:

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

Table of Contents




To do

  • Switch to Deepfillv2 model
  • Enhance data collection and extraction
  • Use new training techniques
  • Resolve all Tensorflow compatibility problems
  • Finish the user interface
  • Add support for black and white images
  • Add error log

Follow me on Twitter @deeppomf (NSFW Tweets) for project updates.

Contributions are welcome! Special thanks to ccppoo, IAmTheRedSpy, 0xb8, deniszh, Smethan, mrmajik45, harjitmoe, itsVale, StartleStars, and SoftArmpit!


This project is licensed under GNU Affero General Public License v3.0.

See LICENSE.txt for more information about the license.


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 MathiasGruber's project Partial Convolutions for Image Inpainting using Keras, which is an unofficial implementation of the paper Image Inpainting for Irregular Holes Using Partial Convolutions. Partial Convolutions for Image Inpainting using Keras is licensed under the MIT license.

User interface code is modified from Packt's project Tkinter GUI Application Development Blueprints - Second Edition. Tkinter GUI Application Development Blueprints - Second Edition is licensed under the MIT license.

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

See for full license text of these projects.


If you like the work I do, you can donate to me via Paypal. The funds will mainly go towards purchasing better GPUs to accelerate training. Donate

Latest Releases
v1.3.0-beta win64
 Nov. 10 2018
v1.2.3-beta win64
 Nov. 4 2018
v1.2.2-beta win64
 Nov. 2 2018
v1.2.1-beta win64
 Oct. 26 2018
v1.2.0-beta win64
 Oct. 22 2018