How to run inference using the STAI MPU Python API

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.

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 Reference.

2. STAI MPU Python API[edit source]

STAI MPU is a cross STM32MPx platforms machine learning and computer vision inferencing API with a flexible interface to run several deep learning models formats such as TFLite, ONNX and NBG. If you wish to learn more about the API structure please refer to STAI MPU: AI unified API for STM32MPUs. In the next section we explore, with a basic image-classification example, how to inference your models on the board using the STAI MPU Python API whether you are running a TFLite, an ONNX or an NBG model on either STM32MP1x or STM32MP2x.

Important

The STM32MP1 based platforms come with no AI hardware acceleration chip. Therefore, inferencing an NBG model on these platforms will reslt in an error.

3. Running an inference using the STAI MPU C++ API[edit source]

3.1. Install runtime prerequisites on the target[edit source]

After having configured the AI OpenSTLinux package, you can install the X-LINUX-AI components and the packages needed to run the example. First, we start by installing main packages needed for image processing which are Python Numpy, Python OpenCV.

Board $> apt-get install python3-numpy python3-opencv

Then, we will need to install the API plugins required during runtime depending on the model format used for the inference:

If you are using a TFLite™ model, please run the following command:

 x-linux-ai -i  stai-mpu-tflite

If you are using an ONNX™ model, please run the following command:

 x-linux-ai -i  stai-mpu-ort

If you are running your model on an STM32MP2 board and running and NBG model, please run the following command:

 x-linux-ai -i  stai-mpu-ovx

Information

It is important to mention that the package stai-mpu-ovx is not available on STM32MP1x boards and the TFLite™ and ONNX™ runtimes supported by the API are running exclusively on CPU.

Warning

The software package is provided AS IS, and by downloading it, you agree to be bound to the terms of the software license agreement (SLA0048). The detailed content licenses can be found here.