将scikit-learn ML模型转换为微控制器的C语言 [英] Converting scikit-learn ML Models into C language for Microcontrollers

问题描述

我正在使用 scikit-learn 软件包评估各种ML模型.我正在验证 Logistic回归，SVM和随机森林分类器，该功能可在sci-kit学习中使用.第一步，我正在使用Python进行这些工作.

I am evaluating various ML models using scikit-learn package. I am validating Logistic Regression, SVM and Random Forest Classifier which is avaialble on sci-kit learn. In the first step, I am working on these using Python.

我想将这些分类器算法和训练有素的ML模型部署到微控制器中.我需要将 scikit-learn 中的 ML 算法从 Python 转换为 C 或 C++，然后将代码写入我的 MCU.

I would like to deploy these classifier algorithms and the trained ML model into a microcontroller. I would need to convert my ML algorithm in scikit-learn from Python to C or C++ and then flash the code into my MCU.

我查看了Internet，找不到任何用C/C ++语言编写的scikit-learn软件包的库.

I looked over the internet and I could not find any librabries of scikit-learn packages written in C/C++ language.

如果无法直接通过scikit-learn进行迁移，是否有任何用C语言编写的ML分类器库(逻辑回归，SVM，随机森林分类器)?

If it is not directly possible to migrate with scikit-learn, are there any ML Classifier libraries (Logistic Regression, SVM, Random Forest Classifier) written in C language?

推荐答案

您正在寻找的是边缘ML解决方案.我不知道有什么方法可以直接在微控制器上间接部署 scikit-learn 模型，但是这是用于微控制器的Tensorflow Lite .其他选项包括Microsoft的嵌入式学习库或

What you're looking for is an edge ML solution. I'm not aware of any way to directly on indirectly deploy a scikit-learn model on a microcontroller, but This sklearn-porter project might be just what you're looking for. There's also plenty of other interesting work going on. One thing you definitely should have a look at is Tensorflow Lite for Microcontrollers. Other options include Microsoft's Embedded Learning Library or Edge ML Library.

对于ARM设备，您还应该查看 CMSIS-NN库，甚至更具体地讲到 X-CUBE-AI扩展打包(如果您使用的是stm32设备).

For ARM devices you should also look into CMSIS-NN library and even more specifically into X-CUBE-AI extension pack if you're using an stm32 device.

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