This paper enables the use of recent advances in computer vision to the conventional image editing pipeline in an open-source setting. This paper introduces GIMP-ML, a set of Python plugins that enabled the use of deep learning models in GIMP via Pytorch for various applications.

GIMP-ML relies on standard Python packages such as numpy, scikit-image, pillow, pytorch, open-cv, scipy. 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. Therefore it has been shown that several manual and time-consuming image processing tasks can be simplified by the use of deep learning models, which makes it convenient for the users of image processing software to perform such tasks.

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

Github: https://github.com/kritiksoman/GIMP-ML

Paper: https://arxiv.org/pdf/2004.13060v1.pdf