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2 changes: 0 additions & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -70,8 +70,6 @@ Each skill is a self-contained module with its own model, parameters, and [commu
|----------|-------|--------------|:------:|
| **Detection** | [`yolo-detection-2026`](skills/detection/yolo-detection-2026/) | Real-time 80+ class detection — auto-accelerated via TensorRT / CoreML / OpenVINO / ONNX | ✅|
| **Analysis** | [`home-security-benchmark`](skills/analysis/home-security-benchmark/) | [143-test evaluation suite](#-homesec-bench--how-secure-is-your-local-ai) for LLM & VLM security performance | ✅ |
| | [`smarthome-bench`](skills/analysis/smarthome-bench/) | Video anomaly detection benchmark — 105 clips across 7 smart home categories | ✅ |
| | [`homesafe-bench`](skills/analysis/homesafe-bench/) | Indoor safety hazard detection — 40 tests across 5 categories | ✅ |
| | [`sam2-segmentation`](skills/analysis/sam2-segmentation/) | Click-to-segment with pixel-perfect masks | 📐 |
| **Transformation** | [`depth-estimation`](skills/transformation/depth-estimation/) | Monocular depth maps with Depth Anything v2 | 📐 |
| **Annotation** | [`dataset-annotation`](skills/annotation/dataset-annotation/) | AI-assisted labeling → COCO export | 📐 |
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74 changes: 19 additions & 55 deletions skills.json
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Expand Up @@ -98,19 +98,23 @@
]
},
{
"id": "smarthome-bench",
"name": "SmartHome Video Anomaly Benchmark",
"description": "VLM evaluation suite for video anomaly detection in smart home camera footage — 7 categories, 105 curated clips from SmartHome-Bench.",
"version": "1.0.0",
"category": "analysis",
"path": "skills/analysis/smarthome-bench",
"tags": [
"benchmark",
"vlm",
"video",
"anomaly-detection",
"smart-home"
"id": "camera-claw",
"name": "Camera Claw",
"description": "Security camera for your AI agent — sandbox, record, and monitor OpenClaw activity.",
"version": "1.1.0",
"category": "integrations",
"repo_url": "https://github.com/SharpAI/CameraClaw",
"code_structure": [
{ "path": "SKILL.md", "desc": "Aegis skill manifest (11 params)" },
{ "path": "package.json", "desc": "Node.js dependencies" },
{ "path": "config.yaml", "desc": "Default params" },
{ "path": "deploy.sh", "desc": "Node.js + Docker bootstrapper" },
{ "path": "deploy.bat", "desc": "Windows bootstrapper" },
{ "path": "scripts/monitor.js", "desc": "Main entry — Docker orchestrator + JSONL protocol" },
{ "path": "scripts/health-check.js", "desc": "Container health checker" },
{ "path": "docs/aegis_openclaw_note.md", "desc": "Aegis integration requirements" }
],
"tags": ["security", "sandbox", "monitoring", "openclaw"],
"platforms": [
"linux-x64",
"linux-arm64",
Expand All @@ -119,51 +123,11 @@
"win-x64"
],
"requirements": {
"node": ">=18",
"ram_gb": 2,
"system_deps": [
"yt-dlp",
"ffmpeg"
]
"docker": true
},
"capabilities": [
"benchmark",
"report_generation"
],
"ui_unlocks": [
"benchmark_report"
]
},
{
"id": "homesafe-bench",
"name": "HomeSafe Indoor Safety Benchmark",
"description": "VLM evaluation suite for indoor home safety hazard detection — 40 tests across 5 categories: fire/smoke, electrical, trip/fall, child safety, falling objects.",
"version": "1.0.0",
"category": "analysis",
"path": "skills/analysis/homesafe-bench",
"tags": [
"benchmark",
"vlm",
"safety",
"hazard",
"indoor"
],
"platforms": [
"linux-x64",
"linux-arm64",
"darwin-arm64",
"darwin-x64",
"win-x64"
],
"requirements": {
"node": ">=18",
"ram_gb": 2
},
"capabilities": [
"benchmark"
],
"ui_unlocks": [
"benchmark_report"
"monitoring",
"recording"
]
}
]
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