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Grounded-Segment-Anything

Grounded-Segment-Anything is a framework that combines Grounding DINO and Segment Anything to detect and segment objects in images using text prompts. The project also incorporates other models like Stable-Diffusion, Tag2Text, and BLIP for various tasks like image generation and automatic labeling.

General
Release date	March 31, 2023
Repository	https://github.com/IDEA-Research/Grounded-Segment-Anything
Type	Image Segmentation and Detection

🔥 Highlighted Projects

Checkout the Automated Dataset Annotation and Evaluation with GroundingDINO and SAM which is an amazing tutorial on automatic labeling! Thanks a lot for Piotr Skalski and Robotflow!
Checkout the Segment Everything Everywhere All at Once demo! It supports segmenting with various types of prompts (text, point, scribble, referring image, etc.) and any combination of prompts.
Checkout the OpenSeeD for the interactive segmentation with box input to generate mask.
Visual instruction tuning with GPT-4! Please check out the multimodal model LLaVA: [Project Page] [Paper] [Demo] [Data] [Model]

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