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 #15099 · Aug 27
#python#audiobooks#epub#kokoro#python#tts You can easily turn e-books in .epub format into high-quality audiobooks using Audiblez, a free tool that uses Kokoro's natural-sounding text-to-speech voices in many languages. It works on Windows, Mac, and Linux, with options for command line or a simple graphical interface. You can choose different voices, adjust reading speed, and even pick specific chapters to convert. Using a GPU speeds up the process significantly. The final audiobook is saved as an .m4b file, playable on most audiobook apps. This saves you time and money compared to hiring narrators and lets you listen to books hands-free anywhere. https://github.com/santinic/audiblez
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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