Find similar content

Source channel @githubtrending · Post #15316 · Dec 7

#lua OTClient Redemption is a flexible and complete alternative client for the game Tibia, designed to work with OTServ servers. It uses LUA scripting and CSS-like syntax for easy customization of the game interface, allowing you to create new mods and extend features. Written in modern C++20, it supports advanced graphics, sound, multi-language, and mobile platforms through OpenGL. It offers many features like shaders, animated textures, transparency, and an in-game LUA terminal. This client improves performance with multi-threading and garbage collection, and adapts smoothly to server latency for better gameplay. You benefit by having a customizable, high-performance client that enhances your Tibia experience and supports modding and mobile use. https://github.com/mehah/otclient

Hashtags

#lua

Results

3 similar posts found

Search: #image2image

当前筛选 #image2image清除筛选

PHYGITAL+CREATIVE

@phygitalcreative · Post #3136 · 06/26/2023, 01:04 AM

Find similar View

А вот подвезли официальный код DragGAN. Интересно насколько его работа отличается от неофициальной имплементации. В основе StyleGAN3 и StyleGAN-Human. Код #image2image

Hashtags

#image2image

PHYGITAL+CREATIVE

@phygitalcreative · Post #3158 · 06/29/2023, 01:26 PM

Find similar View

Mixed Image Editing Playground AI выкатили редактор изображений с большинством последних достижений в этой области. #image2image#imageediting

Hashtags

#image2image #imageediting

GitHub Trends

@githubtrending · Post #14988 · 07/23/2025, 12:00 AM

Find similar View

#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

Hashtags