View source for MISC-TN-011: Running an Azure-generated TensorFlow Lite model on Mito8M SoM using NXP eIQ

==Introduction==
In [[SBCX-TN-005: Using TensorFlow to implement a Deep Learning image classifier based on Azure Custom Vision-generated model|this Technical Note]] (TN for short), a simple image classifier was implemented on the [[:Category:AxelLite|Axel Lite SoM]].

In [[MISC-TN-010: Using NXP eIQ Machine Learning Development Environment with Mito8M SoM|this other document]], it is illustrated how to run [https://www.nxp.com/design/software/development-software/eiq-ml-development-environment:EIQ NXP eIQ Machine Learning software] on i.MX8M-powered [[:Category:Mito8M|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 C++ imaging classification application running on Mito8M SoM, which makes use of the eIQ software stack. In terms of hardware and software, the testbed used is the same described [[MISC-TN-010: Using NXP eIQ Machine Learning Development Environment with Mito8M SoM|here]].