![]() The objective of demonstrating the use-cases for machine learning based image Have been compiled and demonstrated in the YouTube playlist Python packages such as numpy, scikit-image, pillow, pytorch, open-cv, scipy.Īpart from these, several image manipulation techniques using these plugins Additionally, operations on images such as edgeĭetection and color clustering have also been added. Super-resolution, de-noising and coloring have been incorporated with GIMP Semantic segmentation, mask generative adversarial networks, image Applications from deep learning such as monocular depth estimation, It enables the use of recent advances inĬomputer vision to the conventional image editing pipeline in an open-source This paper introduces GIMP-ML, a set of Python plugins for the widely popular
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