segment-anything-model

Segment objects in images using point, box, or automatic prompts.

9|Updated Jul 1, 2026

Search Tags:#multimodal #image processing #computer vision #segmentation #zero-shot #sam

Ready to run

npx skills add https://github.com/Cyapstaye/Adame_ver.open --skill segment-anything-model-cyapstaye

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: segment-anything-model
Source: https://github.com/Cyapstaye/Adame_ver.open/tree/main/skills/mlops/models/segment-anything
Command: npx skills add https://github.com/Cyapstaye/Adame_ver.open --skill segment-anything-model-cyapstaye

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires segment-anything, transformers, torch, opencv-python, pycocotools, matplotlib, and includes references (resource) components.

What problem does it solve?

This Skill solves the challenge of segmenting objects in images without the need for task-specific training or fine-tuning, enabling rapid object isolation and annotation.

Core Features & Use Cases

Zero-Shot Segmentation: Segment any object in an image using point, box, or mask prompts.
Automatic Mask Generation: Automatically detect and segment all objects within an image.
Use Case: Use this tool to quickly generate high-quality training data for other vision models or to isolate specific objects for creative editing and medical image analysis.

Quick Start

Use the segment-anything-model skill to generate masks for all objects in the provided image file.

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 isolates objects using Meta AI's SAM architecture without fine-tuning. You can generate high-precision masks via point, box, or automatic prompts to extract targets across diverse image domains.

Can I automatically segment all objects in an image using computer vision?▼

Automatic mask generation detects and segments all objects within an image instantly. This computer vision process outputs high-precision masks, suitable for generating training data or isolating elements for creative editing.

Does zero-shot segmentation work with medical imaging and satellite analysis?▼

Zero-shot segmentation supports diverse domains including medical imaging and satellite analysis. It uses multimodal prompts to isolate specific objects, enabling high-precision mask generation across varied visual data without requiring domain-specific training.

Do I need PyTorch and OpenCV to generate object masks?▼

Generating object masks requires PyTorch, transformers, and OpenCV to execute high-precision mask generation. These dependencies support the SAM architecture in processing image files and extracting isolated objects effectively.

What is the best way to isolate objects in an image for annotation workflows?▼

The best way to isolate objects for interactive annotation workflows is using zero-shot segmentation with point or box prompts. This rapidly generates high-quality training data for other vision models without manual tracing.