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 #14806 · Jun 8
#other Here’s a simple summary of the most important information and its benefit to you get enough good sleep, avoid smoking, move your body every day, and eat less sugar—doing just these four can make a big difference. The text also shares tips from neuroscience, like getting sunlight in the morning to help wake up and feel better, and avoiding bright lights at night to sleep well. Eating mostly plants and fermented foods helps your gut and immune system, while timing your meals (like eating in an 8-hour window) can boost your health and even help you live longer. The text also explains how your brain’s chemicals, like dopamine, affect your mood and motivation, and how you can use simple tricks—like taking breaks, trying new things, or doing light exercise—to stay focused and happy. The benefit is that you can feel better, think clearer, and stay healthier by making small, smart changes to your daily routine. https://github.com/zijie0/HumanSystemOptimization
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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