How to run inference using the STAI MPU Python API

Revision as of 08:24, 13 September 2024 by Registered User (Created page with "{{ApplicableFor |MPUs list=STM32MP13x, STM32MP15x, STM32MP25x |MPUs checklist=STM32MP13x, STM32MP15x, STM32MP25x }} <noinclude></noinclude> == Article purpose == This article describes how to run an inference on the STM32MPx using the STAI MPU Python API. It is an example based on an image classification application. The unified architecture of the API allows deploying the same application on all the STM32MPx platforms using several model formats. {{Info| This article...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Applicable for STM32MP13x lines, STM32MP15x lines, STM32MP25x lines


1. Article purpose[edit source]

This article describes how to run an inference on the STM32MPx using the STAI MPU Python API. It is an example based on an image classification application. The unified architecture of the API allows deploying the same application on all the STM32MPx platforms using several model formats.

Info white.png Information
This article provides a simple inferencing example using the STAI MPU Python API. If you wish to explore more of the functions provided by the API, please refer to the STAI MPU Python API.