This is the official repo of micromind, a toolkit that aims at bridging two communities: artificial intelligence and embedded systems. micromind is based on PyTorch and provides exportability for the supported models in ONNX, Intel OpenVINO, and TFLite.

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💡 Key features

• Smooth flow from research to deployment;
• Support for multimedia analytics recipes (image classification, sound event detection, etc);
• Detailed API documentation;
• Tutorials for embedded deployment;

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🛠️️ Installation

Using Pip

First of all, install Python 3.8 or later. Open a terminal and run:

pip install micromind

for the basic install. To install micromind with the full exportability features, run

pip install micromind[conversion]

From source

First of all, install Python 3.9 or later. Clone or download and extract the repository, navigate to <path-to-repository>, open a terminal and run:

pip install -e .

for the basic install. To install micromind with the full exportability features, run

pip install -e .[conversion]

Training networks with recipes

After the installation, explore the available recipes under recipes/ to train your own neural network. Please note that micromind is under heavy development and new recipes will be added in a really short period.

Export your model and run it on your MCU

Check out this tutorial and have fun deploying your network on MCU!

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📧 Contact

francescopaissan@gmail.com

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