Semantics for GNU Image Manipulation Program

⭐ ⭐ ⭐ ⭐ are welcome. New tools will be added and existing will be improved with time.

Updates:
[October 31] Use super-resolution as a filter for medium/large images. (Existing users should be able to update.)
[October 17] Added image enlightening.
[September 27] Added Force CPU use button and minor bug fixes.
[August 28] Added deep learning based dehazing and denoising.
[August 25] Simplified installation and updating method.
[August 2] Added deep matting and k-means.
[July 17] MonoDepth and Colorization models have been updated.

Screenshot of Menu

Installation Steps

[1] Install GIMP 2.10.
[2] Clone this repository: git clone https://github.com/kritiksoman/GIMP-ML.git
[3] Open terminal, go to GIMP-ML/gimp-plugins and run :
bash installGimpML.sh
[4] Open GIMP and go to Preferences -> Folders -> Plug-ins, add the folder gimp-plugins and restart GIMP.
[5] Go to Layer->GIMP-ML->update, click on ok with "update weights" set to yes and restart GIMP. (Weights ~ 1.5GB will be downloaded)
Manual install description if above is not working: Link

Update Steps

[1] Go to Layer->GIMP-ML->update, click on ok with "update weights" set to NO and restart GIMP.
[2] Go to Layer->GIMP-ML->update, click on ok with "update weights" set to YES and restart GIMP.

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}
}

Tools

Name	License	Dataset
facegen	CC BY-NC-SA 4.0	CelebAMask-HQ
deblur	BSD 3-clause	GoPro
faceparse	MIT	CelebAMask-HQ
deepcolor	MIT	ImageNet
monodepth	MIT	Multiple
super-resolution	MIT	ImageNet
deepmatting	Non-commercial purposes	Adobe Deep Image Matting
semantic-segmentation	MIT	COCO
kmeans	BSD	-
deep-dehazing	MIT	Custom
deep-denoising	GPL3	BSD68
enlighten	BSD	Custom