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Source channel @githubtrending · Post #14891 · Jul 1

#other#beginner#contribution#contributions_welcome#css#frontend#hacktoberfest#html#javascript#open_source#opensource#php#projects#python#react You can find a well-organized collection of coding project ideas divided into three skill levels: beginner, intermediate, and advanced. Each project includes clear goals, user stories, optional bonus features, and helpful resources, making it easier for you to build and extend your projects. This helps you improve coding skills, experiment with new technologies, and create impressive portfolio pieces to attract employers or clients. The list covers various technologies like JavaScript, Python, React, MERN stack, and blockchain, with tutorials and design resources included. You can also contribute ideas and examples to grow the collection and get community support. This resource saves you time and inspires your learning journey. https://github.com/The-Cool-Coders/Project-Ideas-And-Resources

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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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@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