SVGStud.ioSVGStud.io (https://svgstud.io) is an AI-based tool for searching and generating Scalable Vector Graphics (SVG) files. SVG files are a popular format in graphic design and can be used in a variety of ways, for example as logos and icons or for cutters and plotters. SVG files can be easily edited and imported into a variety of applications. SVGStud.io offers the following core functionalities: * An SVG gallery in which pre-generated SVG bundles can be browsed. * A semantic SVG search, in which SVG files are found that match a search term or a sample image as closely as possible. * An AI-based SVG generator. In this SVG generator, new SVGs can be generated based on a textual description and (optionally) an example image. SVGs can also be refined iteratively. During the preview phase, the use of SVGStud.io is free of charge. All SVGs in SVGStud.io are licenced under CC-BY-SA 4.0, can be converted to other formats such as .dxf and .eps, and can be downloaded at any time. SVGStud.io is the perfect AI-based partner for creatives who want to quickly generate or find SVG to use in their graphic design projects.
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SUPIRSUPIR Intelligent Image Restoration, created by XPixel Group, is a large-scale AI tool designed to reimagine and restore images by blending the power of AI with creativity. The major focus of SUPIR is to give a new life to every image; it is capable of improving image quality considerably whether the images are landscapes, portraits, animal photos, gaming images, cinematic classics, or even vintage photos. Its high-fidelity general image restoration model is based on a large-scale diffusion generative prior, significantly enhancing the details and clarity of each image. In the specific case of facial images, SUPIR reveals true expressions and enhances every detail for a lifelike clarity. For landscape photos, it highlights the natural beauty; for animal images, it brings fur and charm to life; in gaming images, it creates stunning clarity and detail; and for classic and vintage images, it restores and revives them in a way to make them look pristine and vivid. The tool is built with a future online demo and its documentation can be found on GitHub.
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