https://store-images.s-microsoft.com/image/apps.51514.21ad7645-3675-4a56-8222-9ab3f493b386.b6210d79-f862-45f7-a647-f14731164142.9c6a70b6-d0e8-41a2-9285-3c40cbfea279

WeDX on IoT Edge

motojin.com, Inc.

WeDX on IoT Edge

motojin.com, Inc.

Building Edge AI Pipelines with No-Code and Open Source

This module starts as a module with without GUI.

WeDX is an open-source utility built with Python3 and Dear PyGui. The app provides a platform for building intelligent video applications with the capability to capture, record, and analyze videos. After that, you can publish the video and insights from video to your local computer or the cloud. You can define a pipeline(flow) with no-code while checking in real-time so that you can combine the three types of nodes (source, processor, and sink) in the node editor, infer the video source with the AI model, and provide the result to the service or application.

Pipeline handling can be operated by integrating with Azure IoT (Azure IoT Hub, Azure IoT Hub DPS, Azure IoT Central, Azure IoT Edge, Azure Percept) other than locally, so it can be used as a PoC for business scenarios. Recently, we have also integrated Flask and Streamlit to work with web apps.

It supports x64 Windows, macOS, Linux, and ARM (arm64v8) Linux container without GUI.

WeDX was featured on Dear PyGui's Showcase page.

Minimum hardware requirements: Linux x64 OS, 4GB of RAM, 3GB of storage

Key Features

  • Linux AMD64
  • Linux ARM64 - not supported yet in the marketplace
  • No-code experience to easily build Edge AI pipeline.
  • Simple pipeline, Easy to understand code.
  • Support x64 Windows, macOS and Linux OS.
  • Support container for arm64v8 and amd64 architecture without GUI.
  • Import and export node configuration.
  • Asynchronous processing of frame refresh.
  • Netron integration for visualizing neural network models.
  • Controllable by Azure IoT Edge device. (Azure IoT Edge, Azure IoT Edge DPS, Azure Percept, Azure IoT Central)
  • Controllable by Azure IoT device. (Azure IoT Hub, Azure IoT Hub DPS, Azure IoT Central)
  • Controllable by Web API using Flask.
  • Integrated Streamlit for Web App.
  • Controllable Logging Level.
  • Three steps in Edge AI pipeline : Source, Process, and Sink.

Supported Architectures

  • Linux AMD64
  • Linux ARM64 - not supported yet in the marketplace

Supported Hardware Acceleration

  • CPU
  • CUDA - not supported yet in the marketplace

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https://store-images.s-microsoft.com/image/apps.53853.21ad7645-3675-4a56-8222-9ab3f493b386.b6210d79-f862-45f7-a647-f14731164142.422311c5-d7f7-433c-a8e1-0200834e54da
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