🦜🔗 Build context-aware reasoning applications

A latent text-to-image diffusion model

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

High-Resolution Image Synthesis with Latent Diffusion Models

LAVIS - A One-stop Library for Language-Vision Intelligence

OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image genera…

CoTracker is a model for tracking any point (pixel) on a video.

Segment Anything in Medical Images

An Open-Source Python3 tool with SMALL models for recognizing layouts, tables, math formulas (LaTeX), and text in images, converting them into Markdown format. A free alternative to Mathpix, empowe…

Official implementation of Diffusion Autoencoders

Lightweight Stable Diffusion v 2.1 web UI: txt2img, img2img, depth2img, inpaint and upscale4x.

Official implementation of the paper “Inversion-Based Style Transfer with Diffusion Models” (CVPR 2023)

Official implementation of the paper "ProSpect: Prompt Spectrum for Attribute-Aware Personalization of Diffusion Models"(SIGGRAPH Asia 2023)