Nx AI Manager Documentation
  • Nx AI Manager plugin v4.4
  • Nx AI Manager
    • Get started with the NX AI Manager plugin
    • 1. Install Network Optix
    • 2. Install Nx AI Manager Plugin
    • 3. Configure the Nx AI Manager plugin
      • 3.1 Model Settings
      • 3.2 Model pipeline selection and configuration
      • 3.3 Model pipelines on multiple devices
    • 4. Other Network Optix Plugin Settings
    • 5. Manual Plugin Installation
    • 6. Removing the Nx AI Manager
    • 7. Advanced configuration
      • 7.1 Nx AI Manager Manual Installation
      • 7.2 External Post-processing
      • 7.3 External Pre-processing
      • 7.4 Training Loop
      • 7.5 Enable ini settings
  • Nx AI Cloud
    • Introduction
    • Registration and log-in
    • Deployment and device management
    • Upload your model
      • Normalization
    • Use your model
    • API Documentation
  • SUPPORT & TROUBLESHOOTING
    • How to get support
    • Troubleshooting
      • Plugin checks
      • OS checks
      • System checks
      • Things to try
      • Controlling the server and the plugin
      • Q&A
  • Videos
    • Howto videos
  • AI Accelerators Support
    • Introduction
    • Supported AI accelerators
    • Nvidia Support
    • OpenVino Support
    • Hailo Support
  • For Data Scientists
    • Introduction
    • About ONNX
    • Custom model creation
    • ONNX requirements
    • Importing models
      • From Edge Impulse
      • From Nota AI
      • From Teachable Machine
      • From Hugging Face
      • From Ultralytics
      • From PyTorch
      • From TensorFlow / TFLite
      • From Scikit-learn
      • Common Models
  • Miscellaneous
    • Nx AI Certification Test
    • Nx AI Manager on SCAiLX
    • Privacy policy
    • Support
    • End user license agreement
    • Nx cloud cookie statement
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  1. For Data Scientists

Introduction

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This section of our documentation describes how to create vision models that can be easily deployed to your edge devices running Nx Meta Server.

This section of the docs focuses on creating models. Once you have a model ready in ONNX format, you .

High-level process

Our standard process for creating and uploading your models to the Nx AI Cloud is to:

  1. Create a model using your favorite training tools. You can create an or import a model using one of the training tools we integrate with.

    1. If you create your ONNX from scratch, ensure the .

  2. Once you have your model ready, you can upload it to the Nx AI Cloud platform; we will automatically convert it to several different device-type optimized versions and ensure that it can be deployed to any edge device running the Nx AI manager efficiently.

In this section of the docs, you can find the following:

  • General .

  • Details on how to and how to check your ONNX graph.

  • Details on how to import models that have been .

can find instructions on uploading it to the Nx Cloud platform here
ONNX model/pipeline from scratch
resulting ONNX graph is proper
information and resources regarding ONNX
generate your own ONNX graphs
exported from various model training platforms