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Revert. Add some warnings
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This project applies an implementation of [Globally and Locally Consistent Image Completion](http://hi.cs.waseda.ac.jp/%7Eiizuka/projects/completion/data/completion_sig2017.pdf) 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.
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# **THIS REPO IS NOT YET IN A USABLE STATE. PLEASE WAIT FOR THIS NOTICE TO BE REMOVED BEFORE DOWNLOADING/FORKING.**
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# **THIS PROJECT IS STILL IN DEVELOPMENT. DO NOT BE DISAPPOINTED IF THE RESULTS AREN'T AS GOOD AS YOU EXPECT.**
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![Censored, decensored](/readme_images/collage.png)
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@ -36,12 +36,12 @@ Embarrassingly, because the neural network was trained to decensor horizontally
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- matplotlib (only for running test.py)
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# Model
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The pretrained model can be downloaded from **Model temporarily removed.**.
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The pretrained model can be downloaded from https://drive.google.com/open?id=1mWHYSj0LDSbJQQxjR4hUMykQkVve2U3Q.
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Unzip the contents into the /models/ folder.
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# Usage
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o
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## I. Decensoring hentai
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![Guide](/readme_images/guide.png)
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