PHYGITAL+CREATIVE
@phygitalcreative · Post #3136 · 06/26/2023, 01:04 AM
А вот подвезли официальный код DragGAN. Интересно насколько его работа отличается от неофициальной имплементации. В основе StyleGAN3 и StyleGAN-Human. Код #image2image
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Source channel @githubtrending · Post #15000 · Jul 27
#markdown#android#bsd#cheatsheet#cheatsheets#command_line#console#documentation#examples#hacktoberfest#help#linux#macos#man_page#manpages#manual#osx#shell#terminal#tldr#windows The tldr-pages project offers simple, easy-to-understand help pages for command-line tools, focusing on practical examples rather than long, complex manuals. It’s great if you’re new to the command line or forget command options, as it shows the most useful commands clearly. You can access these pages through various clients or online without installing anything. This saves you time and frustration by giving quick, clear guidance on common tasks, making it easier to learn and use command-line tools effectively. Plus, you can contribute by adding or improving pages yourself. This helps you and others get fast, practical help with commands[1][4]. https://github.com/tldr-pages/tldr
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PHYGITAL+CREATIVE
@phygitalcreative · Post #3158 · 06/29/2023, 01:26 PM
Mixed Image Editing Playground AI выкатили редактор изображений с большинством последних достижений в этой области. #image2image#imageediting
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@githubtrending · Post #14988 · 07/23/2025, 12:00 AM
#python#deep_learning#diffusion#flax#flux#hacktoberfest#image_generation#image2image#image2video#jax#latent_diffusion_models#pytorch#score_based_generative_modeling#stable_diffusion#stable_diffusion_diffusers#text2image#text2video#video2video The Hugging Face Diffusers library is a powerful and easy-to-use tool for generating images, audio, and 3D molecular structures using advanced diffusion models. It offers ready-to-use pretrained models and flexible components like pipelines, schedulers, and model building blocks, allowing you to quickly create or customize your own diffusion-based projects. Installation is simple via pip or conda, and you can generate high-quality outputs with just a few lines of code. This library benefits you by making cutting-edge AI generation accessible, customizable, and efficient, whether you want to run models or train your own[1][2][5]. https://github.com/huggingface/diffusers