What makes kami-package-detection notable?

1.5K downloads. Trust evidence available

How should kami-package-detection be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

kami-package-detection

A free skill by Kami SmartHome. Continuously monitors RTSP camera streams for packages, parcels, and bags using YOLO-World ONNX. Smart deduplication only triggers alerts when a genuinely new or moved package appears.

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.5k

Updated

Oct 10, 2026

Version

1.1.6

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.5K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.5K downloadsadoption · observed Oct 10, 2026
Latest release: 1.1.6release · observed Jun 10, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s170wja1qf8kmkzj5brvhsj1r185a522:kami-package-detection

Install using `clawhub skill install s170wja1qf8kmkzj5brvhsj1r185a522:kami-package-detection` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/13681882136/kami-package-detection before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-13681882136-kami-package-detection/snapshot"

Documentation

CLAWHUB

150,162 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: kami-package-detection
description: A free skill by Kami SmartHome. Continuously monitors RTSP camera streams for packages, parcels, and bags using YOLO-World ONNX. Smart deduplication only triggers alerts when a genuinely new or moved package appears.
version: 1.1.0
author: kami-smarthome
tags:
  - smart-home
  - kami
  - home-assistant
  - smarthome
  - detect
  - object-detection
  - yolo
  - package-detection
  - parcel-detection
  - iot
  - camera
  - rtsp
  - onnx
  - edge-ai
  - delivery
  - monitoring
  - notification
triggers:
  - smart home
  - kami
  - home assistant
  - detect
  - detect packages
  - detect parcels
  - kami package
  - kami smart home
  - home assistant package
  - smart home delivery
  - check doorstep
  - delivery notification
  - check for deliveries
  - package detection
  - is there a package
  - monitor packages
  - check camera for packages
  - any deliveries at the door
  - parcel alert
metadata:
  openclaw:
    requires:
      bins:
        - python3.10
      hardware:
        cpu: "2+ cores (x86_64 / ARM64)"
        memory: "2 GB+"
        storage: "2 GB+"
        gpu: "optional (speeds up ONNX inference)"
      network:
        - "RTSP camera access (LAN)"
        - "Internet (KamiClaw API)"
      devices:
        - "RTSP IP camera"
    emoji: "📦"
---

# Kami Package Detection

> Continuously monitors your camera and sends instant notifications when a new package arrives.

Continuously monitors RTSP camera streams for packages, parcels, backpacks, and suitcases. People and handbags are recognized by the model but suppressed at the alert layer to cut down on false alarms. When a **new** package is detected (position/size significantly different from the last alert), sends push notifications. Static frames are automatically skipped to save compute.

### Features

- 📦 Continuous package & parcel monitoring (not one-shot)
- 🔔 Push notifications via Feishu / Telegram / Discord
- 🧠 Smart deduplication — only alerts for new or moved packages (IoU + area change), with a **24-hour tracking window** to silence repeated alerts on the same parcel
- ⚡ Static frame filtering — skips inference when camera scene is unchanged
- 📷 Multi-camera support with independent background processes
- 🧳 Suitcase / backpack recognition
- 🏠 Doorstep & reception monitoring

### Scenarios

- Doorstep delivery waiting
- Office reception package management
- Warehouse cargo monitoring
- Temporary item watch

## Installation

```bash
bash setup.sh
```

Creates `.venv/` and installs `onnxruntime`, `opencv-python-headless`, `numpy`, `requests`. Idempotent.

## Prerequisites

- `python3` and `python3-venv` installed
- RTSP camera(s) online and reachable
- Internet access on first run (to download `yolov8s-worldv2.pt` if not bundled)

### Model

The `yolov8s-worldv2.onnx` model file is auto-prepared by `setup.sh` using a download-f

README.md

# 📦 Kami Package Detection

> A free skill by **Kami SmartHome** — get notified the moment a package arrives at your door.

Monitor your RTSP camera feed for packages, parcels, backpacks, and suitcases using YOLOv8-World ONNX inference. People and handbags are recognized by the model but suppressed at the alert layer (so a person carrying their bag past the door does **not** trigger an alarm). When a delivery target is detected, outputs the object class and bounding box as structured JSON to stdout.

### Features

- 📦 Package & parcel detection
- 🧳 Suitcase / backpack recognition
- 🏠 Doorstep & reception monitoring
- ⏱ Configurable detection duration
- 🔔 JSON output for easy integration
- 🖥 CPU-only inference via `onnxruntime` — no GPU required
- 🐍 Isolated `.venv` — zero impact on system Python

### Scenarios

- Doorstep delivery waiting
- Office reception package management
- Warehouse cargo monitoring
- Temporary item watch

## Quick Start

```bash
# 1. Run setup (one-time)
bash setup.sh

# 2. Place your ONNX model file
cp /path/to/yolov8s-worldv2.onnx .

# 3a. Foreground single-run (exits on first detection or timeout)
.venv/bin/python yolo_world_onnx.py \
  --rtsp_url rtsp://192.168.1.100/live/camera01 \
  --conf_threshold 0.25 \
  --class_names parcel package "delivery box" person "Cardboard box" "Packaging Box" backpack handbag suitcase \
  --run_time 120

# 3b. Background daemon for one or more cameras (uses config.json)
.venv/bin/python yolo_world_onnx.py --start-detect
.venv/bin/python yolo_world_onnx.py --status
.venv/bin/python yolo_world_onnx.py --stop-detect
```

## Installation

```bash
bash setup.sh
```

The setup script automatically:
1. Detects system Python (`python3` or `python`), exits with error if not found
2. Creates an isolated virtual environment at `.venv/`
3. Installs Python dependencies from `requirements.txt`

> Idempotent — safe to run multiple times. Won't reinstall existing dependencies.

### Requirements

| Dependency | Version | Purpose |
|------------|---------|---------|
| `onnxruntime` | latest | ONNX model inference engine |
| `opencv-python-headless` | latest | Video capture and image processing |
| `numpy` | latest | Array operations |

### System Prerequisites

- **Python 3.8+** and **python3-venv** (`sudo apt install python3 python3-venv`)
- **ONNX model file**: `yolov8s-worldv2.onnx` in the skill directory
- **RTSP camera**: online and network-reachable

## Usage

### Basic Detection

Parameters can be supplied via either `config.json` (recommended) or command-line flags. CLI flags > `config.json` > built-in defaults.

```bash
# Option 1: Edit config.json once, then just run
.venv/bin/python yolo_world_onnx.py

# Option 2: Override via CLI
.venv/bin/python yolo_world_onnx.py \
  --rtsp_url rtsp://127.0.0.1/live/TNPUSAQ-757597-DRFMY \
  --conf_threshold 0.25 \
  --class_names parcel package "delivery box" person

_meta.json

{
  "ownerId": "kn7e9156e1awf00v1sas2wkdfd85a4zh",
  "slug": "kami-package-detection",
  "version": "1.1.6",
  "publishedAt": 1781073130954
}

skill-card.md

## Description: <br>
Kami Package Detection continuously monitors RTSP camera streams for packages, parcels, and bags with YOLO-World ONNX and alerts only when a new or moved package appears. <br>

This skill is ready for commercial/non-commercial use. <br>

## Publisher: <br>
[13681882136](https://clawhub.ai/user/13681882136) <br>

### License/Terms of Use: <br>
MIT-0 <br>


## Use Case: <br>
External users and smart-home operators use this skill to monitor configured RTSP camera feeds for package deliveries, doorway parcels, reception items, or warehouse cargo. The skill can run foreground checks or background monitoring and emits structured detection results for integration with notifications or other automations. <br>

### Deployment Geography for Use: <br>
Global <br>

## Known Risks and Mitigations: <br>
Risk: Continuous camera monitoring may process sensitive household, office, or warehouse footage. <br>
Mitigation: Use only cameras and locations where monitoring is authorized, keep RTSP access scoped to the intended device, and stop the background detector when monitoring is not needed. <br>
Risk: Alert snapshots and logs can retain local paths, camera URLs, and image evidence after a detection. <br>
Mitigation: Restrict permissions on the skill directory, avoid embedding RTSP passwords in URLs where possible, and clear snapshots and logs on a regular schedule. <br>
Risk: Notification integrations can send alert data and possibly snapshot images to external services. <br>
Mitigation: Configure Feishu, Telegram, or Discord credentials only when required, verify the destination channels, and remove unused webhook or bot tokens from config. <br>
Risk: Setup downloads a model archive and may install additional packages during fallback export. <br>
Mitigation: Review installer behavior before execution, run setup in an isolated environment, and verify downloaded model files when operating in sensitive deployments. <br>


## Reference(s): <br>
- [ClawHub package page](https://clawhub.ai/13681882136/kami-package-detection) <br>
- [Pre-built ONNX archive](https://publicfiles.xiaoyi.com/kami-package-detection.zip) <br>
- [Kami skill privacy policy](https://kamiclaw-skill.kamihome.com/privacy) <br>


## Skill Output: <br>
**Output Type(s):** [text, markdown, shell commands, configuration, code, JSON] <br>
**Output Format:** [Markdown guidance with shell commands and JSON alarm output from the detection script] <br>
**Output Parameters:** [1D] <br>
**Other Properties Related to Output:** [Alarm JSON may include detected class, confidence, camera name, frame number, snapshot path, and bounding boxes; setup and runtime commands may create local files such as a virtual environment, model files, logs, and snapshots.] <br>

## Skill Version(s): <br>
1.1.6 (source: server release metadata; artifact frontmatter reports 1.1.0) <br>

## Ethical Considerations: <br>
Users should evaluate whether this skill is appropriate for their environment, review any gene

config.json

{
  "cameras": [
    {
      "rtsp_url": "rtsp://admin:[email protected]/stream1",
      "device_id": "camera1"
    },
    {
      "rtsp_url": "rtsp://admin:[email protected]/stream1",
      "device_id": "camera2"
    }
  ],
  "conf_threshold": 0.25,
  "run_time": 0,
  "alarm_cooldown": 60,
  "feishu_webhook_url": "",
  "feishu_app_id": "",
  "feishu_app_secret": "",
  "telegram_bot_token": "",
  "telegram_chat_id": "",
  "discord_webhook_url": "",
  "discord_bot_token": "",
  "discord_channel_id": ""
}

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