X-LINUX-AI is a free of charge open-source software package dedicated to AI. It is a complete ecosystem that allow developers working with OpenSTLinux to create AI-based application very easily.
- All-in-one AI solutions for the entire STM32MPU serie
- Pre-integrated into Linux distribution based on ST environment
- Include AI frameworks to execute Neural Network models
- Include AI model benchmark application tools for MPU
- Easy application prototyping using Python language and AI frameworks Python API
- C++ API for embedded high-performance applications
- Optimized open-source solutions provided with source codes that allow extensive code reuse and time savings
meta-st-stm32mpu-ai
X-LINUX-AI OpenEmbedded meta layer to be integrated into OpenSTLinux distribution. It contains recipes for AI frameworks, tools and application examples for STM32MPx series
Compatibility
The X-LINUX-AI OpenSTLinux Expansion Package v3.0.0 is compatible with the Yocto Project™ build systems Kirkston. It is validated over the OpenSTLinux Distributions v4.1 on STM32MP157F-DK2 with a USB image sensor and on STM32MP157F-EV1 with its built-in camera module
Available frameworks and tools within the meta-layer
X-LINUX-AI v3.0.0 expansion package:
- TensorFlow™ Lite 2.11.0
- ONNX Runtime 1.11.0
- OpenCV 4.5.x
- Python™ 3.10.x (enabling Pillow module)
- Coral Edge TPU™ accelerator native support
- libedgetpu 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.11.0
- libcoral 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.11.0
- PyCoral 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.11.0
- 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 edge.ai@st.com
- Python™ image classification example using ONNX Runtime based on the MobileNet v1 quantized model
- Application support for the 720p, 480p, and 272p display configurations
- 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