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Visitor II
September 7, 2026
Question

How to replace AI model in STM32N6570-DK ImageClassification sample for standalone operation

  • September 7, 2026
  • 1 reply
  • 14 views

Body:

I would like to replace the AI model in the STM32N6570-DK sample project "STM32N6-GettingStarted-ImageClassification" and run it in standalone mode.

Purpose:
My goal is simply to try running different AI models, not for development purposes. I would like to confirm operation by powering the board ON/OFF without using a debugger.

Environment:

  • Board: STM32N6570-DK
  • IDE: STM32CubeIDE 2.2.0
  • STM32CubeAI Studio

What I want to do:
I am currently trying to generate C code using STM32CubeAI Studio from the following AI model provided by STMicroelectronics, and replace the files in the sample project:

https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenetv2_a035_128/mobilenetv2_a035_128_int8.tflite

I am also interested in whether it is possible to run third-party AI models in the same way, such as models from the following repository:

https://github.com/PINTO0309/PINTO_model_zoo

Questions:

  1. What is the correct procedure to replace the C code generated by STM32CubeAI Studio into the sample project and run it in standalone mode (power ON/OFF)?
  2. Is it also possible to run third-party models that are not provided by ST in the same way?

Thank you in advance for your help.

1 reply

Associate III
September 8, 2026

Hello ​@masatake 

I don't know about STM32CubeAIstudio

but I can ensure that you can do it using STM32modelzoo

 

I already tried it and managed to deploy multiple custom image classification models  that I created using notebooks on the STM32N6DK in standalone mode

I advice you to learn about stm32modelzoo and try to install it .it may take few tries to manage to install it succesfully but once done you will be able to deploy  any ai model you want

it also uses the getting started with image classification model like you want

 

just note that wahtever method you use, your AI model should respect some conditions to be compatible with STM32N6 for example it should be TFLITE and int8 or fp32 as output

etc..…

 

 

BR

Yessine