X-LINUX-AI

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STM32 MPU OpenSTLinux Expansion Pack for AI computer vision application

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Product overview

Key Benefits

Run AI models on STM32MPUs

Contains Linux® AI frameworks, as well as application examples.

XNNPACK support for TensorFlow™ Lite and ONNX Runtime

Convert and optimize deep neural networks using the tool.

Part of the ST Edge AI Suite

A collection of free online tools, case studies, and resources to support engineers at every stage of their edge AI development.

Go the the ST Edge AI Suite

Description

X-LINUX-AI is an STM32 MPU OpenSTLinux Expansion Package that targets artificial intelligence for STM32MP1 and STM32MP2 series microprocessors. It contains Linux® AI frameworks, as well as application examples to get started with some basic use cases.

The examples provided in X-LINUX-AI include a selection of optimized models for image classification, object detection, semantic segmentation, and human pose estimation. The face recognition application provided in X-LINUX-AI as a prebuilt binary is based on models retrained by STMicroelectronics. Contact the local STMicroelectronics support for more information about this application.

These examples rely on the STAI_MPU API based on either the TensorFlow™ Lite inference engine, ONNX Runtime, OpenVX™, or the Google Edge TPU™ accelerator. They all support Python™ scripting and C/C++applications.

  • All features

    • Software environment
      • The X-LINUX-AI OpenSTLinux Expansion Package v5.1.0 is compatible with the Yocto Project® build system Mickledore. It is validated over the OpenSTLinux Distribution v5.1
    • AI frameworks
      • STAI_MPU unified API based on OpenVX™ (STM32MP25xx only), TensorFlow™ Lite, Coral Edge TPU™, and ONNX Runtime compatible with all STM32 MPU series
      • TIM-VX™ 1.1.57 (STM32MP25xx only)
      • ONNX Runtime 1.14.0 (CPU only) with XNNPACK execution engine activated
      • TensorFlow™ Lite 2.11.0 (CPU only) with XNNPACK delegate activated
      • Coral Edge TPU™ accelerator native support
        • libedgetpu 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.11.0
        • libcoral 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.11.0
        • PyCoral 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.11.0
    • Applications
      • Image classification
        • C++ / Python™ example using STAI_MPU unified API based on the MobileNet v1 and v2 quantized models
      • Object detection
        • C++ / Python™ example using STAI_MPU unified API based on the SSD MobileNet v1 and v2 quantized models
      • Face recognition
        • C++ example using a proprietary face recognition model of an enrolled user. Contact the local STMicroelectronics support for more information about this application or send a request to edge.ai@st.com
      • Human pose estimation (STM32MP25xx only)
        • Python™ example using STAI_MPU unified API based on YOLOv8n pose quantized model
      • Semantic segmentation (STM32MP25xx only)
        • Python™ example using STAI_MPU unified API based on DeepLabv3 quantized model
      • Application examples based on Gstreamer 1.22.x, GTK® 3.x, OpenCV 4.7.x, Pillow, Python™ 3
    • On-target utilities
      • X-LINUX-AI tool suite: software information, management of AI packages, and benchmarking of neural network models
      • Support for a wide range of image sensors and camera modules for STM32 MPUs including
        • IMX335 (5MP) for STM32MP2 with the use of its internal ISP
        • GC2145
        • OV5640 for STM32MP13xx
    • Host tools
      • 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 supports all the above frameworks. It is available from the X-LINUX-AI product page
      • Optimization and deployment of AI with the offline compiler available through the ST Edge AI Core (STEdgeAI-Core)

Get Software

STM32 MCU wiki
Getting started with FP-AI-NANOEDG1
STM32MPU WIKI
OpenSTLinux Expansion Package
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