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 #3036 · 8 févr.
🔻ONEPLUS NORD N10 COMPATIBILE CON ARCORE🔻 #OP#NORD#N10 Nelle ultime ore, il mediogamma di OnePlus è entrato a far parte dei telefoni compatibili con Google Play Services for AR (ex ARCore). Da questo momento sarà quindi possibile usare le app che richiedono tale framework semplicemente scaricandolo dal Play Store. Nessuna notizia per quanto riguarda invece il fratello minore N100. Pierre — 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