Machine Learning Guide¶
Introduction¶
Our newest QSXP-ML81 CoM with the NXP i.MX8M Plus processor comes with a Machine-Learning-Unit (MLU) on-board.
There are different Machine Learning demos you can run on the processor’s NPU.
Further information can be read at the i.MX Machine Learning User’s Guide
Demo Video¶
Precompiled Images¶
Module | Precompiled Image | Description |
---|---|---|
QSXP-ML81 | qsxp-ml81-ml in Download Area | Machine Learning Demo Image. |
TX8P-ML81 | tx8p-ml81-ml in Download Area | Machine Learning Demo Image. |
QSXP-ML81 | qsxp-ml81-basler in Download Area | Machine Learning Demo Image with Basler Camera support. |
Yocto Setup¶
For creating the neccessary RootFS, a complete Yocto build environment is required.
Depending on your module choose the correct guide - if not already set up.
Note
QSXP, TX8P use NXP Yocto BSP Guide
- Setup the Yocto build-directory as described in the Yocto guide for your machine. Use the following values:
DISTRO=karo-xwayland
MACHINE=<desired-machine>
- Compile the image.
bitbake karo-image-ml
Tip
If you want to compile the image with basler camera support, follow the additional steps described at Basler Camera.
Then compile:
bitbake karo-image-basler
Demos¶
We recommnd using PyeIQ.
PyeIQ is written on top of eIQ™ ML Software Development Environment and provides a set of Python classes allowing the user to run Machine Learning applications in a simplified and efficiently way without spending time on cross-compilations, deployments or reading extensive guides.
Note
Follow the instructions on the PyeIQ webpage to install and run it on your target.