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Revert. Add some warnings

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deeppomf 2018-02-11 23:29:10 -05:00
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@ -3,7 +3,7 @@
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. 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.
# **THIS REPO IS NOT YET IN A USABLE STATE. PLEASE WAIT FOR THIS NOTICE TO BE REMOVED BEFORE DOWNLOADING/FORKING.** # **THIS PROJECT IS STILL IN DEVELOPMENT. DO NOT BE DISAPPOINTED IF THE RESULTS AREN'T AS GOOD AS YOU EXPECT.**
![Censored, decensored](/readme_images/collage.png) ![Censored, decensored](/readme_images/collage.png)
@ -36,12 +36,12 @@ Embarrassingly, because the neural network was trained to decensor horizontally
- matplotlib (only for running test.py) - matplotlib (only for running test.py)
# Model # Model
The pretrained model can be downloaded from **Model temporarily removed.**. The pretrained model can be downloaded from https://drive.google.com/open?id=1mWHYSj0LDSbJQQxjR4hUMykQkVve2U3Q.
Unzip the contents into the /models/ folder. Unzip the contents into the /models/ folder.
# Usage # Usage
o
## I. Decensoring hentai ## I. Decensoring hentai
![Guide](/readme_images/guide.png) ![Guide](/readme_images/guide.png)