kami-package-detection

A free skill by Kami SmartHome. Get notified the moment a package arrives at your door. Detects packages, parcels, and bags from RTSP camera streams using AI vision.

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Install skill "kami-package-detection" with this command: npx skills add 13681882136/kami-package-detection

Kami Package Detection

Get notified the moment a package arrives at your door.

Monitor your camera feed for packages, parcels, backpacks, handbags, and suitcases. When detected, returns the object class and bounding box as JSON — ready for automation.

Features

  • 📦 Package & parcel detection
  • 🧳 Suitcase / backpack / handbag recognition
  • 🏠 Doorstep & reception monitoring
  • ⏱ Configurable detection duration
  • 🔔 JSON output for easy integration

Scenarios

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

Installation

bash setup.sh

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

Prerequisites

  • python3 and python3-venv installed
  • yolov8s-worldv2.onnx model file in the skill directory
  • RTSP camera online and reachable

Model

The yolov8s-worldv2.onnx model file is included in the skill package. If missing, re-download this skill from ClawHub:

clawhub install kami-package-detection

Parameter Confirmation

Before running, confirm these parameters with the user:

ParameterDefaultDescription
--rtsp_urlrtsp://127.0.0.1/live/TNPUSAQ-757597-DRFMYRTSP camera URL
--conf_threshold0.25Confidence threshold (0.0–1.0)
--class_namesparcel package "delivery box" person "Cardboard box" "Packaging Box" backpack handbag suitcaseClasses to detect
--run_time60Max seconds; 0 = unlimited

Ask the user: do any parameters need to be changed?

Usage

.venv/bin/python yolo_world_onnx.py \
  --rtsp_url rtsp://your-camera-address \
  --run_time 60

Output (stdout JSON)

{
  "detections": [
    {
      "class_name": "parcel",
      "bbox": {"x1": 100, "y1": 200, "x2": 300, "y2": 400}
    }
  ]
}
FieldTypeDescription
class_namestringDetected object class
bbox.x1, y1, x2, y2intBounding box coordinates

Exit Codes

CodeMeaning
0Target detected, JSON output written
1Error (model missing, RTSP failure, runtime exception)
2Timeout, no target detected within --run_time

Troubleshooting

  • bash: .venv/bin/python: No such file or directory → Run bash setup.sh
  • Model file not found → Place yolov8s-worldv2.onnx in the skill directory
  • Cannot open video → Check camera is online and --rtsp_url is correct

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