X-CUBE-AI is an STM32Cube Expansion Package part of the STM32Cube.AI ecosystem and extending STM32CubeMX capabilities with automatic conversion of pre-trained Neural Network and integration of generated optimized library into the user's project. The easiest way to use it is to download it inside the STM32CubeMX tool (version 5.0.1 or newer) as described in user manual Getting started with X-CUBE-AI Expansion Package for Artificial Intelligence (AI) (UM2526).
The X-CUBE-AI Expansion Package offers also several means to validate Neural Network models both on desktop PC and STM32, as well as measure performance on STM32 devices without user handmade ad hoc C code.
- Generation of an STM32-optimized library from pre-trained Neural Network models
- Native support of various Deep Learning frameworks such as Keras, TensorFlow™ Lite, Caffe, ConvNetJs and Lasagne, and suppport of all frameworks that can export to the ONNX standard format such as PyTorch™, Microsoft® Cognitive Toolkit, MATLAB® and more
- Supports 8-bit quantization of Keras networks and TensorFlow™ Lite quantized networks
- Allows the use of larger networks by storing weights in external Flash memory and activation buffers in external RAM
- Easy portability across different STM32 microcontroller series through STM32Cube integration
- Free, user-friendly license terms
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|製品型番||概要||Software Version||サプライヤ||GitHub link||ダウンロード||以前のバージョン|
|X-CUBE-AI||AI expansion pack for STM32CubeMX||5.1.2||ST||-||
MadeForSTM32™ is a new quality label delivered by ST, which is granted after an evaluation process. It helps engineers identify third party solutions with the highest level of integration and quality for the STM32 microcontrollers' ecosystem. MadeForSTM32™ is offered to members of the ST Partner Program who want to go one step further in our collaboration, with the overall objective of contributing to a high-quality STM32 ecosystem.
The STM32Cube.AI is an extension pack of the widely used STM32CubeMX configuration and code generation tool enabling AI on STM32 Arm® Cortex®-M-based microcontrollers.
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