Tasmota/lib/libesp32_ml/tf_lite_esp32

TensorFlow Lite Micro Library for Arduino-Espressif32

This repository has the code (including examples) needed to use Tensorflow Lite Micro on an Arduino.

Table of contents

• Table of contents
• Build Status
• How to Install
  • GitHub
  • Checking your Installation
• Compatibility
• License
• Contributing

Build Status

Build Type	Status
Arduino CLI on Linux
Sync from tflite-micro

How to Install

GitHub

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

Checking your Installation

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.

Compatibility

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.

License

This code is made available under the Apache 2 license.

Contributing

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.