segment-anything-model

Name: segment-anything-model
Availability: InStock
Author: DifanaDAP

Segment objects in images using the Segment Anything Model.

Updated Apr 29, 2026

Search Tags:#computer vision #object detection #image segmentation #zero-shot learning #segment anything model

Ready to run

npx skills add https://github.com/DifanaDAP/hermes-backup --skill segment-anything-model-difanadap

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: segment-anything-model
Source: https://github.com/DifanaDAP/hermes-backup/tree/main/workspace/skills/mlops/models/segment-anything
Command: npx skills add https://github.com/DifanaDAP/hermes-backup --skill segment-anything-model-difanadap

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires segment-anything, transformers, torch, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill enables automatic object segmentation in images without the need for task-specific training, significantly reducing manual effort and speeding up processing.

Core Features & Use Cases

Zero-Shot Segmentation: Seamlessly segment any object in images across different domains.
Flexible Prompts: Use points, bounding boxes, or previous masks to generate accurate segmentations.
Automatic Segmentation: Generate all object masks automatically for complex scenes.
High Quality Models: Offers multiple model sizes for different accuracy and speed requirements.
ONNX Export: Deploy segmentation tasks in browsers and edge devices.
Use Case: Use this Skill to quickly and accurately segment objects in satellite imagery for land use analysis.

Quick Start

Use the segment-anything-model skill to segment all objects in the attached image 'cityscape.jpg'.

Frequently Asked Questions about segment-anything-model

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform zero-shot image segmentation without task-specific training?▼

Zero-shot image segmentation identifies and segments objects without task-specific training by utilizing the Segment Anything Model. You can automatically generate object masks across various domains using flexible prompts like points or bounding boxes.

Can I use bounding boxes or points to prompt object detection in images?▼

Yes, you can use points, bounding boxes, or previous masks as flexible prompts to generate accurate object detection and segmentation masks. This allows precise control over identifying specific objects within your images.

How do I automatically segment all objects in a complex scene?▼

Automatic segmentation generates all object masks for complex scenes without manual prompts. You can load the Segment Anything Model to automatically identify and segment every object within an image.

Do I need PyTorch and transformers to run the Segment Anything Model?▼

Yes, you need the segment-anything, transformers, and torch libraries to load and run the model. These dependencies provide the necessary framework to execute zero-shot image segmentation tasks.

Can I export image segmentation models for edge devices?▼

Yes, you can export the segmentation model to ONNX format. This allows you to deploy zero-shot image segmentation tasks directly in browsers and on edge devices.