@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
Hashtags
TGINSIGHT SIMILAR POSTS
Chaîne source @OnePlusGuide · Post #2129 · 18 mai
~ Nuove apps di OxygenOS 9.5 ~ #OXYGEN#PIE#MOD Grazie alla community, sono state esportate alcune tra le funzionalità più accattivanti della nuova OxygenOS 9.5 di OnePlus 7 Pro. Sono installabili da tutti su qualunque OxygenOS basata su Android 9 Pie • Registratore Schermo: Finalmente anche la OxygenOS ha un registatore schermo tutto suo. Potete regolare risoluzione, fonte audio e bitrate. Una volta installata l'app, troverete il tile nei quick settings • Zen Mode: Anche il benessere digitale di OnePlus è ora installabile da tutti. Come prima, troverete il tile nei quick settings una volta installata. Alcuni utenti segnalano un bug che consente di sfruttare ugualmente tutte le apps Trovate i download nei bottoni Pierre
Recherche : #image2image
@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
Hashtags
@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
Hashtags
@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