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 #15135 · Sep 10
#javascript#ansi#ansi_escape_codes#chalk#cli#color#commandline#console#javascript#strip_ansi#terminal#terminal_emulators Chalk is a popular Node.js tool that lets you easily add colors and styles to text in the terminal, making your console output clearer and more attractive. It supports many colors, including 256 and truecolor (millions of colors), and allows you to combine and nest styles like bold, underline, and background colors. Chalk auto-detects if your terminal supports colors and works without adding dependencies or changing built-in string behavior. You can create custom themes and use template literals for dynamic, colorful logs. This helps you highlight important information in your terminal output, improving readability and debugging. Chalk is reliable, actively maintained, and widely used in many projects. https://github.com/chalk/chalk
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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