产品概述
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所有功能
- 从预训练神经网络和经典机器学习模型生成STM32优化库
- 原生支持各种深度学习框架，如Keras和TensorFlow™ Lite，并支持可导出为ONNX标准格式的所有框架，如PyTorch™、Microsoft® Cognitive Toolkit、MATLAB®等
- 支持各种内置scikit-learn模型，如孤立森林、支持向量机(SVM)、K-means等
- 支持8位量子化Keras网络以及TensorFlow™ Lite量子化网络
- 允许将权重存储在外部Flash存储器和外部RAM的激活缓冲区中，从而使用更大的网络
- 通过STM32Cube集成在不同的STM32微控制器系列之间实现轻松移植
- 借助TensorFlow™ Lite神经网络，使用STM32Cube.AI运行时或面向微控制器的TensorFlow™ Lite运行时来生成代码
- 免费易用的许可条款
精选 产品
STM32Cube.AI
STM32 solutions for Artificial Neural Networks
精选 视频
Follow issues and share solutions on Github for STM32Cube MCU packages. Integrate your own software components in a STM32Cube Expansion for STM32CubeMX and STM32CubeIDE tools, thanks to the new STM32PackCreator utility
STM32CubeMX is part of the STM32Cube initiative designed to simplify and accelerate the development of applications for STM32 microcontrollers. STM32CubeMX offers the possibility to generate C projects using embedded software offers packages like CMSIS-Pack compliant software packs. Starting with the 6.0.0 revision, STM32CubeMX is delivered with STM32PackCreator, an STM32 pack creation graphical companion tool, whose main purpose is the creation of software packs.
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STM32配置程序和代码生成器 ST
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