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Source channel @githubtrending · Post #14734 · May 21

#c_lang Windows Subsystem for Linux 2 (WSL2) lets you run Linux on Windows using a lightweight virtual machine. This means you can use Linux tools and apps directly from Windows, which is great for developers. WSL2 is faster and more efficient than its predecessor, WSL1, because it uses a complete Linux kernel. This setup allows for better performance and compatibility with Linux applications. Users can also customize their WSL2 kernel by building it from source, which can be useful for adding specific features or fixing issues. https://github.com/microsoft/WSL2-Linux-Kernel

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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