Hi all,
I’m currently developing a project on the STM32N6 and am looking for advice on the most robust development workflow. Given the complexity of the N6, I’d like to leverage the automation of CubeMX, but I’ve encountered several hurdles. CubeMX frequently freezes and generates wrong code. Moreover, code generation seems to vary between versions, making it difficult to maintain projects over time or follow existing tutorials (such as https://community.st.com/t5/stm32-mcus/how-to-build-an-ai-application-from-scratch-on-the-nucleo-n657x0/ta-p/828502). Also tutorials recommend to change generated code to make the projects running, which goes against the purpose of automatic code generation.
I’ve noticed the ST Edge AI Model Zoo examples appear to use a hybrid approach. It looks like some functions where taken from CubeMX, but the examples itself do not rely on the .ioc file generation.
What is the best/recommended way to write software for the STM32N6? Use the firmware package: https://github.com/STMicroelectronics/STM32CubeN6 and the AI runtime from the installed Edge AI Core and build a custom project, using the provided examples as a base? Also, what is the best way to maintain long-term usability, as neural network code generated by Edge-AI core is incompatible between versions of the ll_aton library? I could tell users of my code to install specific versions of the ST-Tools, but I would prefer to stay up-to-date.
Best,
devjalx
