Stable Diffusion web UI
- deep-learning
- diffusion
- image-generation
- image2image
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Stable Diffusion web UI
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. The fastest local inference engine in the world.
Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.
A community-maintained Python framework for creating mathematical animations.
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Translated⚡️HivisionIDPhotos: a lightweight and efficient AI ID photos tools. A lightweight AI algorithm for making ID photos.
Image augmentation for machine learning experiments.
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Streamlined interface for generating images with AI in Krita. Inpaint and outpaint with optional text prompt, no tweaking required.
Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/ https://greasyfork.org/en/scripts/437569-cotrans-manga-image-translator-regular-edition
Blender addons to make the bridge between Blender and geographic data
Stable Diffusion built-in to Blender
Stable Diffusion web UI
TranslatedOpen-source manuscript of 《深入理解 AI Infra:量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
SD.Next: All-in-one WebUI for AI generative image and video creation, captioning and processing
A User-Focused Photo & File Management System
ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
Remove visible and invisible AI watermarks from images and video, and AI provenance metadata from images, video, and audio. Python library, CLI, and agent skill for SynthID, C2PA, EXIF, IPTC, XMP, and common generative-AI marks. By Victor Kuznetsov.
Amagine3D: From hardware requirements to editable 3D designs
A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
Image augmentation library in Python for machine learning.