DeepMindBreak

Decensoring Hentai with Deep Neural Networks

This project applies an implementation of Image Inpainting for Irregular Holes Using Partial Convolutions to the problem of hentai decensorship. Using a deep fully convolutional neural network, DeepMindBreak can replace censored artwork in hentai with plausible reconstructions. The user needs to only specify the censored regions.

What's New?

• Decensoring images of ANY size
• Higher quality decensors
• Support for mosaic decensors (still a WIP)
• User interface (still a WIP and not very usable)

Limitations

The decensorship is intended to ONLY work on color hentai images that have minor to moderate bar censorship of the penis or vagina.

It does NOT work with:

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

In particular, if a vagina or penis is completely censored out, decensoring will be ineffective.

Dependencies

• Python 3
• TensorFlow 1.10
• Pillow
• argparse

No GPU required! Tested on Ubuntu 16.04 and Windows. (Tensorflow on Windows is compatible with Python 3 and not Python 2.)

Tensorflow, Pillow, and argparse can all be installed with pip.

Model

Pretrained models can be downloaded from https://drive.google.com/open?id=1byrmn6wp0r27lSXcT9MC4j-RQ2R04P1Z.

Unzip the file into the /models/ folder.

Usage

For each image you want to decensor, using image editing software like Photoshop or GIMP to paint the areas you want to decensor the green color (0,255,0), which is a very bright green color.

BE SURE TO TURN OFF ANTI-ALIASING on the tool you are using.

I personally use the wand selection tool with anti-aliasing turned off to select the censored regions. I then expand the selections slightly, pick the color (0,255,0), and use the paint bucket tool on the selection regions.

To expand selections in Photoshop, do Selection > Modify > Expand or Contract. To expand selections in GIMP, do Select > Grow.

Save these images in the PNG format to the "decensor_input" folder. Decensor the images by running

$ python decensor.py

Decensored images will be saved to the "decensor_output" folder.

To do

• Finish the user interface

Contributions are welcome! Special thanks to StartleStars for contributing code for mosaic decensorship and SoftArmpit for greatly simplifying decensoring!

License

This work (the code and the model) is under my exclusive copyright. The only right I grant to users is using this work for personal use to decensor hentai. Copying, distribution, and modification is prohibited. Commercial use is prohibited. (Modification of the 6 values of the arguments in config.py is allowed.) I will likely change the license to be more permissive in the future, but I make no guarantees.

Example 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.

User interface code is modified from Packt's project Tkinter GUI Application Development Blueprints - Second Edition.

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