  This paper introduces GIMP-ML v1.1, 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, de-hazing, matting, enlightening and coloring have been
incorporated with GIMP through Python-based plugins. Additionally, operations
on images such as k-means based color clustering have also been added. GIMP-ML
relies on standard Python packages such as numpy, pytorch, open-cv, scipy.
Apart from these, several image manipulation techniques using these plugins
have been compiled and demonstrated in the YouTube channel
(https://youtube.com/user/kritiksoman) with the objective of demonstrating the
use-cases for machine learning based image modification. 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 code and
installation procedure for configuring these plugins is available at
https://github.com/kritiksoman/GIMP-ML.
