@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 #14677 · May 6
#typescript#android#app_framework#expo#framework#frontend#ios#javascript#mobile#native#native_apps#react#react_native#typescript#universal#web#web_framework Expo is a tool that helps you make apps for Android, iOS, and the web using React and JavaScript. It simplifies the development process by handling complex tasks, allowing you to focus on features. Expo offers fast setup, easy access to native features like the camera, and painless updates without needing store approvals. You can write one codebase and deploy it across multiple platforms, saving time and effort. Expo also has a strong community and flexible workflows, making it easier to find help and customize your app as needed. https://github.com/expo/expo
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@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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@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