PHYGITAL+CREATIVE
@phygitalcreative · Post #3136 · 26/06/2023 01:04
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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Chaîne source @OnePlusGuide · Post #2723 · 15 août
🔻OXYGENOS 10 VS OXYGENOS 11🔻 #ONEPLUS#OXYGENOS#OXYGENOS11 La nuova versione dell'OS firmato OnePlus è in lavorazione e non da poco. In un nostro post precedente vi abbiamo segnalato alcuni dettagli forniti da persone che stavano già testando OOS 11. Oggi voglio arricchire la quantità di dettagli segnalandovi un post di XDA di Max Winebach, membro dello staff di XDA, che fa un pagarone side-to-side tra OOS 10 e OOS 11 su OP8 Pro evidenziandone i cambiamenti (per la maggior parte relativi alla UI). ▪️ OOS 10 vs OOS 11 - XDA Voi che ne pensate? Vi piace oppure preferite la versione attuale di OxygenOS? Fatecelo sapere nei nostri gruppi! Pit — Il nostro canale 👉🏻@oneplusguide I nostri gruppi 👉🏻@oneplusitcommunity
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PHYGITAL+CREATIVE
@phygitalcreative · Post #3158 · 29/06/2023 13:26
Mixed Image Editing Playground AI выкатили редактор изображений с большинством последних достижений в этой области. #image2image#imageediting
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@githubtrending · Post #14988 · 23/07/2025 00:00
#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