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, get started looking at the examples and the docs!

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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