Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.
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Updated
Aug 7, 2024 - Python
Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.
GroundedSAM Base Model plugin for Autodistill
This project focuses on generating a diverse and realistic dataset for computer vision training using ChatGPT and a realistic vision image generation model. The process involves dynamically creating prompts, utilizing ChatGPT to generate image descriptions, and generating images based on those descriptions.
Prompt based automatic annotation
A Cross-Frame Multimodal Retrieval Augmented Generation (CFM-RAG) for Video Intelligence. It retrieves the most relevant multimodal evidence and empowers LLMs to deliver context-rich answers.
Optimized ROS1 integration package for FoundationPose with Grounded SAM. Provides ROS1 wrapper nodes for real-time 6D object pose estimation with open-vocabulary segmentation. Includes timestamp synchronization and temporal filtering optimizations for Human Support Robot (HSR). FoundationPose and Grounded SAM are external dependencies.
AI image masker with Grounded SAM using a Python GUI desktop app.
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