Last edited 4 months ago

X-LINUX-AI Developer package: Difference between revisions


Revision as of 13:49, 14 May 2024



1. Developer package : build AI application from the X-LINUX-AI add-on SDK[edit | edit source]

In order to easily develop and build an AI application without using the Yocto build system, X-LINUX-AI comes with a SDK add-on extending the OpenSTLinux SDK with AI functionality. To install and use the X-LINUX-AI SDK Add-on please refer to the following steps.

2. Prerequisites[edit | edit source]

2.1. Install the OpenSTLinux SDK[edit | edit source]

First of all, you must download and install the OpenSTLinux SDK, which contains all the basis needed for the X-LINUX-AI add-on. To do this, follow instructions given in STM32MP2 Developer Package : Installing the SDK chapter. Once this has been done, you should have a directory containing the OpenSTLinux SDK.

3. X-LINUX-AI SDK add-on installation[edit | edit source]

3.1. Download the X-LINUX-AI SDK add-on[edit | edit source]

To add the Artificial Intelligence part into the OpenSTLinux SDK, you must download and install the X-LINUX-AI SDK add-on. The add-on is delivered through a tarball file that can be downloaded here:

  • For beta:
To download the archive, Follow instructions given in the downloading instructions page, if you didn't retrieve yet the files and download the SDK-x86_64-stm32mp25-openstlinux-6.1-yocto-mickledore-mp2-v23.12.06-addon-x-linux-ai-STM32MP25-beta.tar.gz archive.

3.2. Install the X-LINUX-AI SDK add-on[edit | edit source]

Once the X-LINUX-AI SDK add-on is downloaded, uncompress the add-on:

  cd  ~/Downloads/
  tar xzf  SDK-x86_64-stm32mp25-openstlinux-6.1-yocto-mickledore-mp2-v23.12.06-addon-x-linux-ai-STM32MP25-beta.tar.gz

Then, copy the .sh script to your OpenSTLinux SDK directory:

  cp stm32mp25-openstlinux-6.1-yocto-mickledore-mp2-v23.12.06-addon-x-linux-ai-STM32MP25-beta/st-image-ai-openstlinux-weston-stm32mp25-x86_64-toolchain-4.2.2-openstlinux-6.1-yocto-mickledore-mp2-v23.12.06-addon-x-linux-ai-STM32MP25-beta.sh $HOME/STM32MPU_workspace/STM32MPU-Ecosystem-v5.0.2.BETA/Developer-Package/SDK

Finally, run the script contained in the tarball:

  cd $HOME/STM32MPU_workspace/STM32MPU-Ecosystem-v5.0.2.BETA/Developer-Package/SDK
  ./st-image-ai-openstlinux-weston-stm32mp25-x86_64-toolchain-4.2.2-openstlinux-6.1-yocto-mickledore-mp2-v23.12.06-addon-x-linux-ai-STM32MP25-beta.sh

Optionally, once the script is executed, you can delete it.

  rm *.sh

3.3. Start the SDK[edit | edit source]

The add-on is now installed into the OpenSTLinux SDK. You can start the SDK. Go to your OpenSTLinux SDK directory and source the environment:

  cd $HOME/STM32MPU_workspace/STM32MPU-Ecosystem-v5.0.2.BETA/Developer-Package/SDK
  source environment-setup-cortexa35-ostl-linux

Check that the SDK is properly installed:

  x-linux-ai -v
 X-LINUX-AI version: STM32MP25-beta

4. Use the SDK[edit | edit source]

4.1. Build an application with the SDK[edit | edit source]

Once the SDK is correctly set up, the applications can be built easily. In this example, it is the image classification application that is built.

Download the github repository:

  git clone https://github.com/PRG-MPU-ALPHA/meta-st-x-linux-ai

Go to the image classification directory:

  cd meta-st-x-linux-ai/recipes-samples/image-classification/tflite/

Export ARCHITECTURE variable to build AI applications with NPU acceleration :

 export ARCHITECTURE=stm32mp2_npu

Then, use the make command to build the application:

  make

A new file is displayed, named tflite_image_classification. This is a binary file, which has been generated using the make command. It is compiled for the STM32MP2x architecture. It must now be transferred to the board.

4.2. Use the application[edit | edit source]

Once the STM32MP2x board is correctly set up and the X-LINUX-AI packages are installed with the right version, it is possible to send the application to the board.

To do it, use the following command using your own IP address:

  scp -r -p tflite_image_classification root@<ip_address>:/usr/local/demo-ai/image-classification/tflite

Then, use the ssh protocol to connect to the board:

  ssh root@<ip_address>

On the board, go to the right directory and use the image classification script to launch the application:

  cd /usr/local/demo-ai/image-classification/tflite
  ./launch_bin_image_classification.sh

This script is using the tflite_image_classification application that has been compiled before.