First let me thank you for posting.
It sounds like you are trying to run a Mobilenet V2 model on the STM32H723ZG microcontroller using STM32CubeMX, and you are encountering a memory overflow error during validation on the target device.
There are a few potential reasons why this error might be occurring:
It can be challenging to run large models like Mobilenet V2 on microcontrollers, and you may need to experiment with different approaches and configurations to find a solution that works for your application. I recommend consulting the documentation for the STM32H723ZG and STM32CubeMX, as well as any other resources you can find on running machine learning models on microcontrollers, to get more ideas on how to troubleshoot and resolve this issue.
Hello again @jeman.1
Mobilenet V2 is a machine learning model that was designed to perform image classification and object detection tasks on desktop or server-based systems. It is a relatively large model, with a size of around 17 MB, and it requires a significant amount of computing resources to run. As a result, it may not be well-suited for use on microcontrollers, which typically have limited memory and processing power compared to desktop or server systems.
Running large models like Mobilenet V2 on microcontrollers can be challenging due to the limited resources available. In general, it is best to use models that are optimized for microcontroller environments, which may be smaller in size and require less memory and processing power to run.
If you are interested in using machine learning on a microcontroller, you may want to consider using a different model that is more suitable for the limited resources available.
There are many machine learning models that are well-suited for use on microcontrollers, and the best model for your application will depend on your specific requirements and the resources available on your microcontroller. Some examples of machine learning models that may be suitable for use on microcontrollers include: