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GitHub - deeppomf/DeepCreamPy: Decensoring Hentai with Deep Neural Networks
Глубина анала: какая максимальная глубина проникновения?
NipSlips (@legitchickss) | Твиттер
deeppomf
Update requirements-cpu.txt
Added .gitignores to avoid accidentally commiting test files
Added .gitignores to avoid accidentally commiting test files
Added .gitignores to avoid accidentally commiting test files
added ignore in models and changes argument names not to confuse
added ignore in models and changes argument names not to confuse
check missing file for non-binary users
add/remove signals that are/aren't used
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About
Decensoring Hentai with Deep Neural Networks.
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.
You can download the latest release for Windows 64-bit here .
For users interested in compiling DeepCreamPy themselves, DeepCreamPy can run on Windows, Mac, and Linux.
Please before you open a new issue check closed issues and check the table of contents .
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.
Follow me on Twitter @deeppomf (NSFW Tweets) for project updates.
If you want to make a pull request to DeepCreamPy, you must first sign our Contributor License Agreement (the "CLA"). Then I can accept your pull requests.
Special thanks to ccppoo, IAmTheRedSpy, 0xb8, deniszh, Smethan, harjitmoe, itsVale, StartleStars, and SoftArmpit for their contributions!
Source code and official releases/binaries are distributed under the GNU Affero General Public License v3.0 .
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.
See ACKNOWLEDGEMENTS.md for full license text of these projects.
If you like the work I do, you can donate to me via Paypal. The funds go towards keeping me alive.
Decensoring Hentai with Deep Neural Networks
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