Difference between revisions of "MISC-TN-011: Running an Azure-generated TensorFlow Lite model on Mito8M SoM using NXP eIQ"

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Revision as of 08:51, 25 March 2020

Info Box
DMI-Mito-top.png Applies to Mito8M
NeuralNetwork.png Applies to Machine Learning
Warning-icon.png This technical note was validated against specific versions of hardware and software. What is described here may not work with other versions. Warning-icon.png

History[edit | edit source]

Version Date Notes
1.0.0 March 2020 First public release

Introduction[edit | edit source]

In this Technical Note (SBCX-TN-005) (TN for short), a simple image classifier was implemented on the Axel Lite SoM.

In this TN (MISC-TN-010), it is illustrated how to run NXP eIQ Machine Learning software on i.MX8M-powered Mito8M SoM.

This article combines the results shown in the TN's just mentioned. In other words, it describes how to run the same image classifier used in SBCX-TN-005 with the eIQ software stack. The outcome is an optimized imaging classification application written in C++ running on Mito8M SoM and that makes use of eIQ software stack.