docs

docs/DEMOS.md

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+[<img src="http://img.youtube.com/vi/e6q7_CPw_rk/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=e6q7_CPw_rk)
+[<img src="http://img.youtube.com/vi/FPeQ5g3WIWk/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=FPeQ5g3WIWk)
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+[<img src="http://img.youtube.com/vi/squyQYrllBg/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=squyQYrllBg)
+[<img src="http://img.youtube.com/vi/eMEd6vs47c4/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=eMEd6vs47c4)
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+[<img src="http://img.youtube.com/vi/q9Ny5XqIUKk/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=q9Ny5XqIUKk)
+[<img src="http://img.youtube.com/vi/4YpTa-gqEIw/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=4YpTa-gqEIw)
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+[<img src="http://img.youtube.com/vi/kXYsWvOB4uk/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=kXYsWvOB4uk)
+[<img src="http://img.youtube.com/vi/HVwISLRow_0/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=HVwISLRow_0)
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+[<img src="http://img.youtube.com/vi/U1CieWi--gc/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=U1CieWi--gc)
+[<img src="http://img.youtube.com/vi/HeBgWcXFQpI/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=HeBgWcXFQpI)
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+[<img src="http://img.youtube.com/vi/adgHtu4chyU/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=adgHtu4chyU)
+[<img src="http://img.youtube.com/vi/thS8VqPvuhE/0.jpg" width="400" height="300">](http://www.youtube.com/watch?v=thS8VqPvuhE)
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docs/HOME.md

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+# Welcome to the GIMP ML wiki!
+This repository introduces GIMP-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on images such as edge detection and color clustering have also been added. GIMP-ML relies on standard Python packages such as numpy, scikit-image, pillow, pytorch, open-cv, scipy. In addition, GIMP-ML also aims to bring the benefits of using deep learning networks used for computer vision tasks to routine image processing workflows. 
+
+The plugins have been tested with GIMP 2.10 on the following machines: <br>
+[1] macOS Catalina 10.15.4, Big Sur 11.0.1 <br>
+[2] ubuntu 18.04 LTS <br>
+[3] ubuntu 20.04 LTS <br>
+[4] Debian GNU/Linux 10 (buster)
+

docs/REFERENCES.md

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+# Paper References
+[1] [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://arxiv.org/abs/1609.04802) <br>
+[2] [DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better](https://arxiv.org/abs/1908.03826) <br>
+[3] [Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer](https://arxiv.org/abs/1907.01341v2) <br>
+[4] [BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation](https://arxiv.org/abs/1808.00897) <br>
+[5] [MaskGAN: Towards Diverse and Interactive Facial Image Manipulation](https://arxiv.org/abs/1907.11922) <br>
+[6] [Real-Time User-Guided Image Colorization with Learned Deep Priors](https://arxiv.org/abs/1705.02999) <br>
+[7] [Rethinking Atrous Convolution for Semantic Image Segmentation](https://arxiv.org/abs/1706.05587) <br>
+[8] [Deep Image Matting](https://openaccess.thecvf.com/content_cvpr_2017/papers/Xu_Deep_Image_Matting_CVPR_2017_paper.pdf) <br>
+[9] [AOD-Net: All-In-One Dehazing Network](https://openaccess.thecvf.com/content_ICCV_2017/papers/Li_AOD-Net_All-In-One_Dehazing_ICCV_2017_paper.pdf) <br>
+[10] [When AWGN-based Denoiser Meets Real Noises](https://arxiv.org/pdf/1904.03485.pdf)<br>
+[11] [EnlightenGAN: Deep Light Enhancement without Paired Supervision](https://arxiv.org/pdf/1906.06972.pdf)<br>
+[12] [RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation](https://arxiv.org/pdf/2011.06294.pdf)<br>
+[13] [Deep Two-Stage High-Resolution Image Inpainting](http://ceur-ws.org/Vol-2744/short18.pdf)<br>
+
+# Code References
+The following have been ported : <br>
+[1] https://github.com/switchablenorms/CelebAMask-HQ <br>
+[2] https://github.com/TAMU-VITA/DeblurGANv2 <br>
+[3] https://github.com/zllrunning/face-parsing.PyTorch <br>
+[4] https://github.com/junyanz/interactive-deep-colorization <br>
+[5] https://github.com/intel-isl/MiDaS <br>
+[6] https://github.com/twtygqyy/pytorch-SRResNet <br>
+[7] https://github.com/huochaitiantang/pytorch-deep-image-matting <br>
+[8] https://github.com/MayankSingal/PyTorch-Image-Dehazing <br>
+[9] https://github.com/yzhouas/PD-Denoising-pytorch <br>
+[10] https://github.com/VITA-Group/EnlightenGAN <br>
+[11] https://github.com/hzwer/arXiv2020-RIFE <br>
+[12] https://github.com/a-mos/High_Resolution_Image_Inpainting <br>