Sam3 Segmentation

Sam3 Segmentation is an AI agent skill that outlines, masks, and counts objects in photos using Meta's SAM 3 model.

Sam3 Segmentation is an agent skill that allows coding agents to outline, mask, and count objects in photos using Meta's SAM 3 model. It runs on a local NVIDIA GPU and provides tools for quick calls or detailed workflows with overlapping close-up crops, raw candidate saving, score checks, review sheets, boundary refinement, and a zoomable viewer. The product exports masks in PNG and COCO RLE formats while explicitly reporting outputs as model proposals rather than verified ground truth. It is designed for developers using coding agents like Claude Code, Codex, and Cursor who need to process images locally. The skill requires Linux or Windows WSL2 with an NVIDIA GPU, uv, disk space, and Hugging Face access, and offers a non-GPU demo mode with generated shapes.

Sam3 Segmentation at a glance

Best for: Software engineer
Runs on: Linux, Windows, self-hosted, open source, CLI
Pricing: Free and open source under the MIT licence
Released: October 2026
Category: AI agent tool
Website: github.com/lillyguisnet/sam3-segmentation

Key features

Outline objects using Meta's SAM 3 model
Run workflows with overlapping close-up crops
Save raw candidates and perform score checks
Review sheets and flags with reversible decisions
Refine boundaries and export to PNG and COCO RLE
View results in a zoomable viewer
Integrate with coding agents via specific commands

Use it for

Outline every kernel in a photo of corn
Cut out specific objects like dogs or insects
Count small objects or parts in an image
Generate object masks for review and export

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