Segmentation Sam2
Interactive click-to-segment using Segment Anything 2 — AI-assisted labeling for Annotation Studio
Install
$ agentstack add skill-sharpai-deepcamera-sam2-segmentation ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-sharpai-deepcamera-sam2-segmentation) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
SAM2 Interactive Segmentation
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.shSource & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: SharpAI
- Source: SharpAI/DeepCamera
- License: MIT
- Homepage: http://www.sharpai.org
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.