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Source channel @githubtrending · Post #14638 · Apr 27

#swift#i3#i3wm#mac#macos#tiling#tiling_window_manager#window_manager AeroSpace is a tiling window manager for macOS that helps organize windows in a grid, making all windows visible at once. It offers fast workspace switching without animations, which can be faster than macOS's native Spaces. AeroSpace uses its own workspaces instead of macOS Spaces, allowing for more efficient management. It supports multiple monitors and doesn't require disabling System Integrity Protection. Users can configure it using plain text files, making it friendly for advanced users and developers. This setup helps users work more efficiently by keeping everything organized and easily accessible. https://github.com/nikitabobko/AeroSpace

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@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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@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