适用于Automatic1111/stable-diffusion-webui 的Openpose Editor 插件。 功能： 直接编辑骨骼动作 从图像识别姿势 本插件实现以下操作： 「Add」：添加一个新骨骼 「Detect from image」: 从图片中识别姿势 「Add Background image」: 添加背景图片 「Load JSON」：载入JSON文件 「Sav
Detailed feature showcase with images: Original txt2img and img2img modes One click install and run script (but you still must install python and git) Outpainting Inpainting Color Sketch Prompt Matr
Simplified Chinese translation extension , Used for AUTOMATIC1111's stable diffusion webui 简体中文(Simplified Chinese) 简体中文翻译扩展，适用于 stable diffusion webui 推荐与 Bilingual Localization 共同使用 术语表 - 已知问题 w
Stable Diffusion web UI 双语对照翻译插件 Snipaste_2023-03-30_01-05-45 功能 全新实现的双语对照翻译功能，不必再担心切换翻译后找不到原始功能 兼容原生语言包扩展，无需重新导入多语言语料 支持动态title提示的翻译 额外支持作用域和正则表达式替换，翻译更加灵活 安装 以下方式选择其一，需要使用支持扩展功能的 webui (2023年之后的版本
English | 中文 由于部分无良商家销售WebUI，捆绑本插件做卖点收取智商税，本仓库的许可证已修改。 自许可证修改之日(AOE 2023.3.28)起，之后的版本禁止商业使用。 WebUI和本插件都是完全免费的，请勿上当受骗。 如果你喜欢这个项目，请给作者一个 star！ 本插件通过以下三种技术实现了在有限的显存中进行大型图像绘制： 两种 SOTA diffusion tili
日本語の文章は下のほうにあります。 Change History is moved to the bottom of the page. 更新履歴はページ末尾に移しました。 Stable Diffusion web UI now seems to support LoRA trained by sd-scripts (SD 1.x based only, except Conv2d-3x3 L
WIP) WebUI extension for ControlNet and T2I-Adapter This extension is for AUTOMATIC1111's Stable Diffusion web UI, allows the Web UI to add ControlNet to the original Stable Diffusion model to genera
Welcome to an open source implementation of OpenAI's CLIP (Contrastive Language-Image Pre-training). The goal of this repository is to enable training models with contrastive image-text supervision,
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Announcement: BLIP is now officially integrated into LAVIS - a one-stop library for language-an
Taming Transformers for High-Resolution Image Synthesis CVPR 2021 (Oral) teaser Taming Transformers for High-Resolution Image Synthesis Patrick Esser*, Robin Rombach*, Björn Ommer * equal contributio
Towards Robust Blind Face Restoration with Codebook Lookup Transformer (NeurIPS 2022) Paper | Project Page | Video google colab logo Hugging Face Replicate visitors Shangchen Zhou, Kelvin C.K. Cha
k-diffusion An implementation of Elucidating the Design Space of Diffusion-Based Generative Models (Karras et al., 2022) for PyTorch. The patching method in Improving Diffusion Model Efficiency Throug
This repository contains Stable Diffusion models trained from scratch and will be continuously updated with new checkpoints. The following list provides an overview of all currently available models.
