SAM2 Interactive Segmentation

SkillDev tools

Lets your agent segment objects in video frames with a click using Segment Anything 2.

Then ask your AI: use the SAM2 Interactive Segmentation skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.

No other account needed.

Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.

About this skill

Interactive click-to-segment using Segment Anything 2, AI-assisted labeling for Annotation Studio

What this skill tells your AI

The instructions your AI receives, as published by sharpai/deepcamera in skills/segmentation/sam2-segmentation/SKILL.md and read by Ahel’s review.

Click anywhere on a video frame to segment objects using Meta's Segment Anything 2. Generates pixel-perfect masks for annotation, tracking, and dataset creation.

What You Get

Click-to-segment — click on any object to get its mask
Point & box prompts — positive/negative points and bounding box selection
Video tracking — segment in one frame, propagate across the clip
Annotation Studio — full integration with sidebar Annotation Studio

Protocol

Communicates via JSON lines over stdin/stdout.

Aegis → Skill (stdin)

{"event": "frame", "frame_path": "/tmp/frame.jpg", "frame_id": "frame_1", "request_id": "req_001"}
{"command": "segment", "points": [{"x": 450, "y": 320, "label": 1}], "request_id": "req_002"}
{"command": "track", "frame_path": "/tmp/frame2.jpg", "frame_id": "frame_2", "request_id": "req_003"}
{"command": "stop"}

Skill → Aegis (stdout)

{"event": "segmentation", "type": "ready", "request_id": "", "data": {"model": "sam2-small", "device": "mps"}}
{"event": "segmentation", "type": "encoded", "request_id": "req_001", "data": {"frame_id": "frame_1", "width": 1920, "height": 1080}}
{"event": "segmentation", "type": "segmented", "request_id": "req_002", "data": {"mask_path": "/tmp/mask.png", "mask_b64": "...", "score": 0.95, "bbox": [100, 50, 350, 420]}}
{"event": "segmentation", "type": "tracked", "request_id": "req_003", "data": {"frame_id": "frame_2", "mask_path": "/tmp/track.png", "score": 0.93}}

Installation

The deploy.sh bootstrapper handles everything — Python environment, GPU detection, dependency installation, and model download. No manual setup required.

./deploy.sh

Signals

GitHub stars: 3k
Forks: 488
Last commit: Sep 2026

Advanced

Item type: skill
Key: segmentation-sam2
Source: github.com/sharpai/deepcamera

github.com/sharpai/deepcamera