eIQ for Glow Neural Network compiler is now available with the release of the 2.8.0 MCUXpresso SDK. The attached labs provide a step-by-step guide on how to use this new neural network compiler tool by using a handwritten digit recognition model example. This new compiler tool turns a model into an machine executable binary for a targeted device. Both the model and the inference engine are compiled into a binary that is generated, which can decrease both inference time and memory usage. That binary can then be integrated into an MCUXpresso SDK software project.
The eIQ Glow for RT1060 Lab.pdf can be used with the RT1060, RT1050, or with a few minor modifications, the RT1064.
The eIQ Glow for RT685 Lab.pdf can be used with the RT685.
Also attached is a simple image conversion script needed by the lab. It can also be found in the RT1060 and RT1050 SDKs at \middleware\eiq\glow\examples\common\glow_process_image.py