Product overview
Description
X-LINUX-AI is an STM32 MPU OpenSTLinux Expansion Package that targets artificial intelligence for STM32MP1 Series microprocessors. It contains Linux® AI frameworks, as well as application examples to get started with some basic use cases such as computer vision (CV). The examples provided in X-LINUX-AI use TensorFlow™ Lite models for image classification based on MobileNet v1, and for object detection based on the COCO SSD MobileNet v1 model. 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 use either the TensorFlow™ Lite inference engine supporting Python™ scripting and C/C++ applications, or the Google Edge TPU™ accelerator supporting Python™ scripting and C/C++application.
X-LINUX-AI runs on the STM32MP157C-DK2 with a USB image sensor, on the STM32MP157A-EV1 and STM32MP157C-EV1 with their built-in camera module.
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All features
- 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 (Grouper) aligned with TensorFlow™ Lite 2.8.0
- libcoral 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.8.0
- PyCoral 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.8.0
- 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
- 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 edge.ai@st.com
- 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
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