# DeepCreamPy *Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak.* A deep learning-based tool to automatically replace censored artwork in hentai with plausible reconstructions. The user specifies the censored regions in each image by coloring those regions green in a separate image editing program like GIMP or Photoshop. A neural network handles the hard part of filling in the censored regions. DeepCreamPy has a pre-built binary for Windows 64-bit. DeepCreamPy works on Windows, Mac, and Linux. ![Censored, decensored](/readme_images/mermaid_collage.png) ## What's New? - Decensoring images of ANY size - Decensoring censors of ANY shape (e.g. bunch of black lines, pink hearts, etc.) - Higher quality decensors - Support for mosaic decensors (still a WIP and not very usable) - User interface (not usable) ## Limitations The decensorship is intended to work on 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 containing screentones (e.g. printed hentai) - Real life porn - Censorship of nipples - Censorship of anus - Animated gifs/videos ## Table of Contents Setup: * [Installation](INSTALLATION.md) Usage: * [Decensoring Tutorial](USAGE.md) * [Troubleshooting for poor quality decensors](TROUBLESHOOTING.md). Miscellaneous: * [FAQ](FAQ.md) ## To do - Finish the user interface (sometime in November) - Update model with better quality data (sometime in November) - Add support for black and white images - Add error log Contributions are welcome! Special thanks to StartleStars for contributing code for mosaic decensorship and SoftArmpit for greatly simplifying decensoring! ## License This project is licensed under GNU Affero General Public License v3.0. See [LICENSE.txt](LICENSE.txt) for more information about the license. ## Acknowledgements Example mermaid image by Shurajo & AVALANCHE Game Studio under [CC BY 3.0 License](https://creativecommons.org/licenses/by/3.0/). The example image is modified from the original, which can be found [here](https://opengameart.org/content/mermaid). Neural network code is modified from MathiasGruber's project [Partial Convolutions for Image Inpainting using Keras](https://github.com/MathiasGruber/PConv-Keras), which is an unofficial implementation of the paper [Image Inpainting for Irregular Holes Using Partial Convolutions](https://arxiv.org/abs/1804.07723). [Partial Convolutions for Image Inpainting using Keras](https://github.com/MathiasGruber/PConv-Keras) is licensed under the MIT license. User interface code is modified from Packt's project [Tkinter GUI Application Development Blueprints - Second Edition](https://github.com/PacktPublishing/Tkinter-GUI-Application-Development-Blueprints-Second-Edition). [Tkinter GUI Application Development Blueprints - Second Edition](https://github.com/PacktPublishing/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](https://www.gwern.net/Danbooru2017). See [ACKNOWLEDGEMENTS.md](ACKNOWLEDGEMENTS.md) for full license text of these projects. ## Donations If you like the work I do, you can donate to me via Paypal: [![Donate](https://img.shields.io/badge/Donate-PayPal-green.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=SAM6C6DQRDBAE)