Gimp-ML – Machine Learning Python plugins for GIMP

GIMP-ML

Preprint: Link

Set of Machine Learning Python plugins for GIMP.

The plugins have been tested with GIMP 2.10 on the following machines:

[1] macOS Catalina 10.15.3

[2] ubuntu 18.04 LTS

Screenshot of Menu

Installation Steps

Demo videos on YouTube

Paper References

[1] Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network ( https://arxiv.org/abs/1609.04802 )

[2] DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better ( https://arxiv.org/abs/1908.03826 )

[3] Digging into Self-Supervised Monocular Depth Prediction ( https://arxiv.org/abs/1806.01260 )

[4] BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation ( https://arxiv.org/abs/1808.00897 )

[5] MaskGAN: Towards Diverse and Interactive Facial Image Manipulation ( https://arxiv.org/abs/1907.11922 )

[6] Perceptual Losses for Real-Time Style Transfer and Super-Resolution ( https://cs.stanford.edu/people/jcjohns/eccv16/ )

[7] Rethinking Atrous Convolution for Semantic Image Segmentation ( https://arxiv.org/abs/1706.05587 )

Code References

The following have been ported :

[1] https://github.com/switchablenorms/CelebAMask-HQ

[2] https://github.com/TAMU-VITA/DeblurGANv2

[3] https://github.com/zllrunning/face-parsing.PyTorch

[4] https://github.com/nianticlabs/monodepth2

[5] https://github.com/richzhang/colorization

[6] https://github.com/twtygqyy/pytorch-SRResNet

Citation

Please cite using the following bibtex entry:

@article{soman2020GIMPML,
  title={GIMP-ML: Python Plugins for using Computer Vision Models in GIMP},
  author={Soman, Kritik},
  journal={arXiv preprint arXiv:2004.13060},
  year={2020}
}