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All Projects → STMicroelectronics → meta-st-stm32mpu-ai

STMicroelectronics / meta-st-stm32mpu-ai

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This repository contains the OpenEmbedded meta layer to install AI frameworks and tools for the STM32MP1

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Labels

image-classificationobject-detectionmeta-layertensorflow-litemobilenetv1stm32mp1ai-frameworkscoco-ssd-mobilenet

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meta-st-stm32mpu-ai

OpenEmbedded meta layer to install AI frameworks and tools for the STM32MP1. It also provide application samples.

Compatibility

The X-LINUX-AI OpenSTLinux Expansion Package v2.2.0 is compatible with the Yocto Project™ build systems Kirkstone and Dunfell. It is validated over the OpenSTLinux Distributions v3.1 and v4.0 on STM32MP157C-DK2 with a USB image sensor, and on STM32MP157A-EV1 and STM32MP157C-EV1 with their built-in camera module

Available frameworks and tools within the meta-layer

X-LINUX-AI v2.2.0 expansion package:

  • TensorFlow™ Lite 2.8.0
  • OpenCV 4.5.x
  • Python™ 3.10.x (enabling Pillow module)
  • Support for the STM32MP157F devices operating at up to 800 MHz
  • Coral Edge TPU™ accelerator native support
    • libedgetpu 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.8.0
    • libcoral 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.8.0
    • PyCoral 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.8.0
  • Support for the OpenSTLinux AI package repository allowing the installation of a prebuilt package using apt-* utilities
  • Application samples
    • C++ / Python™ image classification example using TensorFlow™ Lite based on the MobileNet v1 quantized model
    • C++ / Python™ object detection example using TensorFlow™ Lite based on the COCO SSD MobileNet v1 quantized model
    • C++ / Python™ image classification example using Coral Edge TPU™ based on the MobileNet v1 quantized model and compiled for the Edge TPU™
    • C++ / Python™ object detection example using Coral Edge TPU™ based on the COCO SSD MobileNet v1 quantized model and compiled for the Edge TPU™
    • C++ face recognition application using proprietary model capable of recognizing the face of a known (enrolled) user. Contact the local STMicroelectronics support for more information about this application or send a request to [email protected]
  • Application support for the 720p, 480p, and 272p display configurations
  • Application user interface with updated look and feel
  • Python™ and C++ application rework for better performance
  • X-LINUX-AI SDK add-on extending the OpenSTLinux SDK with AI functionality to develop and build an AI application easily. The X-LINUX-AI SDK add-on provides support for all the above frameworks. It is available from the X-LINUX-AI product page

Further information on how to install and how to use X-LINUX-AI

https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_OpenSTLinux_Expansion_Package

Further information on how to install and how to use X-LINUX-AI SDK add-on

https://wiki.st.com/stm32mpu/wiki/How_to_install_and_use_the_X-LINUX-AI_SDK_add-on

Application samples

https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_application_samples_zoo

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