| Name | micromind JSON |
| Version |
0.2.1
JSON |
| download |
| home_page | |
| Summary | MicroMind |
| upload_time | 2023-12-06 10:18:56 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | |
| keywords |
feed
reader
tutorial
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://www.python.org/downloads/)
[](https://github.com/fpaissan/micromind/blob/main/LICENSE)
[](https://pypi.org/project/micromind/)
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](https://pytorch.org) and provides exportability for the supported models in ONNX, Intel OpenVINO, and TFLite.
---------------------------------------------------------------------------------------------------------
## 💡 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;
---------------------------------------------------------------------------------------------------------
## 🛠️️ Installation
### Using Pip
First of all, install [Python 3.8 or later](https://www.python.org). 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](https://www.python.org).
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](https://docs.google.com/document/d/1zt5urvNtI9VSJcoJdIeo10YrdH-tZNcS4JHbT1z5udI/edit?usp=sharing)
tutorial and have fun deploying your network on MCU!
---------------------------------------------------------------------------------------------------------
## 📧 Contact
[francescopaissan@gmail.com](mailto:francescopaissan@gmail.com)
---------------------------------------------------------------------------------------------------------
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