# Zero-shot segmentation

Seg-Zero-7B is an image segmentation model based on reasoning chain guidance, featuring a decoupled architecture that includes a reasoning model and a segmentation model. It achieves zero-shot generalization capabilities through GRPO reinforcement learning training.

SAM2 is the state-of-the-art mask generation model released by Meta. This repository contains its base variant.

SAM2 is Meta's state-of-the-art mask generation model, and this repository contains its large variant.

SAM is a visual model capable of generating high-quality object masks from input points or bounding boxes, with zero-shot transfer capability.

SAM is a vision model capable of generating high-quality object masks from input prompts (such as points or boxes), supporting zero-shot segmentation tasks

SAM is a vision model capable of generating high-quality object masks based on input prompts, supporting zero-shot transfer to new tasks