Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak.

Related tags

Deep Learning DeepCreamPy
Overview

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 colors cencored 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 works on Windows, Mac, and Linux.

Censored, decensored

Features

  • 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)
  • User interface (WIP)

Limitations

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

Setup:

Usage:

Miscellaneous:

To do

  • Finish the user interface (estimated November)
  • Update model with better quality data (estimated November)
  • Add support for black and white images
  • Add error log

Follow me on Twitter @deeppomf for project updates.

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

License

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

See LICENSE.txt for more information about the license.

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 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.

See 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

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Comments
  • The prebuilt binary links are all dead

    The prebuilt binary links are all dead

    DO NOT POST ADULT CONTENT

    Describe the bug A clear and concise description of what the bug is. all of the prebuilt binary links are all dead To Reproduce Steps to reproduce the behavior: click on any of the links. they link to a user's profile that no longer exists?

    Expected behavior I'd be taken to the releases page of this project

    Screenshots DO NOT POST ADULT CONTENT. If applicable, add screenshots to help explain your problem.

    Installation method Did you install DeepCreamPy with the binary? I did not, I can't compile it myself, that's why I was looking into downloading the prebuilt Did you run DeepCreamPy's code yourself? ???

    Desktop (please complete the following information):

    • OS: win11
    • Supports AVX? yes

    Additional context Add any other context about the problem here. I have a much older build installed and I'd love to see how far the project has come, but I'm not skilled enough to build it myself

    opened by SugoiShades 0
  • Weight count mismatch for layer #0

    Weight count mismatch for layer #0

    Describe the bug I get the following error when running python decensor.py: Traceback (most recent call last): File "/home/haywire/DeepCreamPy/decensor.py", line 179, in decensor = Decensor() File "/home/haywire/DeepCreamPy/decensor.py", line 22, in init self.load_model() File "/home/haywire/DeepCreamPy/decensor.py", line 32, in load_model self.model.load( File "/home/haywire/DeepCreamPy/libs/pconv_hybrid_model.py", line 238, in load self.model.load_weights(filepath) File "/home/haywire/.local/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 67, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/haywire/.local/lib/python3.9/site-packages/keras/saving/hdf5_format.py", line 736, in load_weights_from_hdf5_group raise ValueError( ValueError: Weight count mismatch for layer #0 (named p_conv2d_16 in the current model, p_conv2d_17 in the save file). Layer expects 3 weight(s). Received 2 saved weight(s)

    I am using the default setup image.

    To Reproduce Steps to reproduce the behavior:

    1. clone the repo
    2. install requirements
    3. run python decensor.py

    Expected behavior A normal run, uncensored image

    Installation method I ran DeepCreamPy's code myself.

    Desktop (please complete the following information):

    • OS: Manjaro
    • Python 3.9
    opened by DeWolfRobin 0
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