@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 #15237 · Oct 19
#python#text_to_speech#tts#voice_clone#zero_shot_tts OpenVoice is a free, open-source tool that lets you clone any voice using just a short audio sample, then generate speech in that voice across many languages and accents[1][5][8]. You can fine-tune how the voice sounds—adjusting emotion, accent, rhythm, pauses, and intonation—to match your needs[1][3][5]. A major benefit is “zero-shot” cloning: you can make the cloned voice speak languages it was never trained on, which is rare in voice AI[1][3][4]. The latest version, OpenVoice V2, offers even better sound quality, supports six major languages natively, and is free for both personal and commercial use[1]. This makes it easy and affordable for anyone to create realistic, customizable voice content without needing technical expertise or expensive software. https://github.com/myshell-ai/OpenVoice
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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