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# GIMP-ML
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Preprint: [Link](https://arxiv.org/abs/2004.13060) <br>
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Set of Machine Learning Python plugins for GIMP.
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The plugins have been tested with GIMP 2.10 on the following machines: <br>
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[1] macOS Catalina 10.15.3 <br>
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[2] ubuntu 18.04 LTS
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# Screenshot of Menu
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![image1](https://github.com/kritiksoman/GIMP-ML/blob/master/screenshot.png)
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# Installation Steps
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[1] Install [GIMP](https://www.gimp.org/downloads/).<br>
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[2] Clone this repository: git clone https://github.com/kritiksoman/GIMP-ML.git <br>
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[3] Open GIMP and go to Preferences -> Folders -> Plug-ins, add the folder gimp-plugins and close GIMP. <br>
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[4] Download [weights.zip](https://drive.google.com/open?id=1mqzDnxtXQ75lVqlQ8tUeua68lDqUgUVe) (1.22 GB) and save it in gimp-plugins folder. <br>
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[5] Open terminal and run : <br>
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```bash installGimpML-mac.sh```
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<br>
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```bash moveWeights.sh ```<br>
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[6] Open GIMP.
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# Demo videos on YouTube
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[![](http://img.youtube.com/vi/U1CieWi--gc/0.jpg)](http://www.youtube.com/watch?v=U1CieWi--gc "") <br>
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[![](http://img.youtube.com/vi/HeBgWcXFQpI/0.jpg)](http://www.youtube.com/watch?v=HeBgWcXFQpI "") <br>
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[![](http://img.youtube.com/vi/adgHtu4chyU/0.jpg)](http://www.youtube.com/watch?v=adgHtu4chyU "") <br>
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[![](http://img.youtube.com/vi/q9Ny5XqIUKk/0.jpg)](http://www.youtube.com/watch?v=q9Ny5XqIUKk "") <br>
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[![](http://img.youtube.com/vi/thS8VqPvuhE/0.jpg)](http://www.youtube.com/watch?v=thS8VqPvuhE "") <br>
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[![](http://img.youtube.com/vi/kXYsWvOB4uk/0.jpg)](http://www.youtube.com/watch?v=kXYsWvOB4uk "") <br>
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[![](http://img.youtube.com/vi/HVwISLRow_0/0.jpg)](http://www.youtube.com/watch?v=HVwISLRow_0 "")
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# Paper References
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[1] Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (https://arxiv.org/abs/1609.04802) <br>
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[2] DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better (https://arxiv.org/abs/1908.03826) <br>
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[3] Digging into Self-Supervised Monocular Depth Prediction (https://arxiv.org/abs/1806.01260) <br>
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[4] BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation (https://arxiv.org/abs/1808.00897) <br>
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[5] MaskGAN: Towards Diverse and Interactive Facial Image Manipulation (https://arxiv.org/abs/1907.11922) <br>
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[6] Perceptual Losses for Real-Time Style Transfer and Super-Resolution (https://cs.stanford.edu/people/jcjohns/eccv16/) <br>
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[7] Rethinking Atrous Convolution for Semantic Image Segmentation (https://arxiv.org/abs/1706.05587) <br>
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# Code References
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The following have been ported : <br>
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[1] https://github.com/switchablenorms/CelebAMask-HQ <br>
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[2] https://github.com/TAMU-VITA/DeblurGANv2 <br>
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[3] https://github.com/zllrunning/face-parsing.PyTorch <br>
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[4] https://github.com/nianticlabs/monodepth2 <br>
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[5] https://github.com/richzhang/colorization <br>
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[6] https://github.com/twtygqyy/pytorch-SRResNet
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# Citation
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Please cite using the following bibtex entry:
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```
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@article{soman2020GIMPML,
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title={GIMP-ML: Python Plugins for using Computer Vision Models in GIMP},
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author={Soman, Kritik},
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journal={arXiv preprint arXiv:2004.13060},
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year={2020}
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}
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```
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