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{{WarningMessage|text=This technical note was validated against specific versions of hardware and software. It may not work with other versions.}}
|-
|1.0.0
|Ocotber October 2019
|First public release
|}
==Introduction==
Nowadays, Machine Learning (ML) and Deep Learning (DL) technologies are getting popular in the embedded world as well. Several different approaches are available to deploy such technologies on embedded devices. This Technical Note (TN) describes such an approach, which makes use of a Tensor Flow model generated with [https://www.customvision.ai Microsoft Azure Custom Vision service].
==Testbed basic configuration==
2019-10-25 11:17:21,594 - DEBUG - Exiting ...
</pre>
The image was classified as a "Red Apple" because the probability associated with this class was by far the highest (almost 97%).
[[File:Red-apple.jpg|thumb|center|300px|The image shown in the previous example]]
During the execution of the test application, the status of the processes and the ARM cores was observed with the help of the <code>htop</code> tool.
[[File:SBCX-image-classifier-1.png|thumb|center|600px|<code>htop</code> during the execution of the test application]]
<pre class="board-terminal">
root@sbcx:~# cat /sys/devices/system/cpu/cpu0/cpufreq/scaling_governor
