Bureaucrats, dave_user, Administrators
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Changes
→Testbed
|January 2020
|First public release
|-
|1.0.1
|March 2020
|Added more details about the software configuration
|}
==Introduction==
According to [https://community.nxp.com/docs/DOC-343798 NXP documentation], ''eIQ Machine Learning Software is a collection of software and development tools for NXP microprocessors and microcontrollers to do inference of neural network AI models on embedded systems.''
==Testbed==
With regards regard to the hardware, the testbed consists of the same platform described [[MISC-TN-008:_Running_Debian_Buster_(armbian)_on_Mito8M |here]].
Concerning the software, the following combination was used:
* U-Boot 2018.03 retrieved from the standard Mito8M Yocto-based Board Support Package (BSP)
* Device tree retrieved from the standard Mito8M Yocto-based BSP
* Linux kernel imx8qmmek 4.14.98-imx_4.14.98_2.0.0(built with the Linux L4.14.98 GA Yocto BSP release for i.MX 8 family of devices with support for NXP eIQ software)* eIQ-enabled YocotYocto-based root file system(built with the Linux L4.14.98 GA Yocto BSP release for i.MX 8 family of devices with support for NXP eIQ software); as such, this root file system includes the following packages:**OpenCV 4.0.1**Arm Compute Library 19.02**Arm NN 19.02**ONNX runtime 0.3.0**TensorFlow 1.12**TensorFlow Lite 1.12.
For more information about the kernel and the root file system, please refer to the following section.
==Building NXP eIQ software==
NXP document [https://www.nxp.com/docs/en/nxp/user-guides/UM11226.pdf UM11226Rev. 2, 06/2019] illustrates how to build eIQ software support using Yocto Project tools. Even though the official procedure was tested against Ubuntu 16.04, the build was completed successfully on the host running Ubuntu 18.04 as well.
The build process produces several artifacts:
==Configuring the target==
The procedure described by NXP makes use of an SD card to store all the software. For convenience, a different approach was followed to test eIQ with Mito8M. While the internal eMMC was used to store U-Boot, the device tree and the Linux kernel image were retrieved via TFTP over the Ethernet connection. Also, the board was configured to mount the root file system via NFS. The resulting configuration reminds the one described [[Deploying_Embedded_Linux_Systems#The_development_environment|here]].
For a detailed dump of the full bootstrap process, please refer to the following section.
===Bootstrap process===
Please click on ''Expand'' on the top right corner to open the box.
<pre class="board-terminal mw-collapsible mw-collapsed">
U-Boot SPL 2018.03-08018-g59e59e6f85-dirty (Nov 29 2019 - 12:42:16 +0100)
imx8qmmek login:
</pre>
==Running TensorFlow and TensorFlow Lite examples==
