This repository has the code (including examples) needed to use Tensorflow Lite Micro on an Arduino.
| Build Type | Status |
|---|---|
| Arduino CLI on Linux |  |
| Sync from tflite-micro |  |
The officially supported TensorFlow Lite Micro library for Arduino resides
in the tflite-micro-arduino-examples
GitHub repository.
To install the in-development version of this library, you can use the
latest version directly from the GitHub repository. This requires you clone the
repo into the folder that holds libraries for the Arduino IDE. The location for
this folder varies by operating system, but typically it's in
~/Arduino/libraries on Linux, ~/Documents/Arduino/libraries/ on MacOS, and
My Documents\Arduino\Libraries on Windows.
Once you're in that folder in the terminal, you can then grab the code using the git command line tool:
git clone https://github.com/tensorflow/tflite-micro-arduino-examples Arduino_TensorFlowLite
To update your clone of the repository to the latest code, use the following terminal commands:
cd Arduino_TensorFlowLite
git pull
Once the library has been installed, you should then start the Arduino IDE.
You will now see an Arduino_TensorFlowLite
entry in the File -> Examples menu of the Arduino IDE. This submenu contains a list
of sample projects you can try out.
This library is designed for the Arduino Nano 33 BLE Sense board. The framework
code for running machine learning models should be compatible with most Arm Cortex
M-based boards, such as the Raspberry Pi Pico, but the code to access peripherals
like microphones, cameras, and accelerometers is specific to the Nano 33 BLE Sense.
This code is made available under the Apache 2 license.
Forks of this library are welcome and encouraged. If you have bug reports or fixes to contribute, the source of this code is at https:://github.com/tensorflow/tflite-micro and all issues and pull requests should be directed there.
The code here is created through an automatic project generation process and may differ from that source of truth, since it's cross-platform and needs to be modified to work within the Arduino IDE.