This module is developed from 「Lobe.ai ONNX Sample」 to be able to run on IoT Edge.

While running the IoT Edge module, you can use in conjunction with Azure Video Analyzer. It can be used as an inferencing server for HTTP extension node in Azure Video Analyzer on Edge. The performance of the model inferencing server depends on the CPU power.

This module can be used with the Azure cloud native application WeDX Flow to simplify module management.

Minimum hardware requirements: Linux x64 and arm64 OS, 1GB of RAM, 850Mb of storage

Features

Inferencing server for AVA HTTP extension node - Classification inference type
The default port(Nginx proxy) of the module is 80 and binding port is 8170
Telemetry of inference results
Video stream of inference results - {SERVER IP}:8170/stream/video

Getting Started

Export ONNX model on Lobe.ai app
Check two important files in the export directory

model.onnx
signature.json

Copy two files to Lobe Model Directory (default:/var/lib/lobemodel)

Direct methods

Not available

Environment variables

Not available

Desired properties

Lobe.ai ONNX model directory (default:/var/lib/lobemodel)
- "LobeModelDirectory": "/var/lib/lobemodel"
Send telemetory of inference results (default:true)
- "SendTelemetry": true / false
Stream Video of inference results (default:true)
- "ViewVideoStream": true / false

AVA(Azure Video Analyzer) Integration

Pipeline Topology sample (HttpExtension)
- "url": "rtsp://{ModuleName}/store"
- "mode": "preserveAspectRatio"
- "width": "416"
- "height": "416"
- "@type": "#Microsoft.VideoAnalyzer.ImageFormatBmp"

Testing

/score
- Getting a list of detected objects
/annotate
- Seeing the bounding boxes overlaid on the image
/score-debug
- Getting the list of detected objects and also generate an annotated image

Lobe model HTTP Extension for AVA on Edgemotojin.com, Inc.

Lobe model HTTP Extension for AVA on Edge

motojin.com, Inc.

Lobe model HTTP Extension for AVA on Edge

motojin.com, Inc.

Lobe model HTTP Extension for AVA on Edge
motojin.com, Inc.