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TensorFlow Lite Micro Library for Arduino\n\nThis repository has the code (including examples) needed to use Tensorflow Lite Micro on an Arduino.\n\n## Table of contents\n\u003c!--ts--\u003e\n* [Table of contents](#table-of-contents)\n* [Build Status](#build-status)\n* [How to Install](#how-to-install)\n  * [GitHub](#github)\n  * [Checking your Installation](#checking-your-installation)\n* [Compatibility](#compatibility)\n* [License](#license)\n* [Contributing](#contributing)\n\u003c!--te--\u003e\n\n## Build Status\n\nBuild Type          |     Status    |\n---------------     | ------------- |\nArduino CLI on Linux  | [![Arduino](https://github.com/tensorflow/tflite-micro-arduino-examples/actions/workflows/ci.yml/badge.svg?event=schedule)](https://github.com/tensorflow/tflite-micro-arduino-examples/actions/workflows/ci.yml)\nSync from tflite-micro  | [![Sync from tflite-micro](https://github.com/tensorflow/tflite-micro-arduino-examples/actions/workflows/sync.yml/badge.svg)](https://github.com/tensorflow/tflite-micro-arduino-examples/actions/workflows/sync.yml)\n\n## How to Install\n\n### GitHub\n\nThe officially supported TensorFlow Lite Micro library for Arduino resides\nin the [tflite-micro-arduino-examples](https://github.com/tensorflow/tflite-micro-arduino-examples)\nGitHub repository.\nTo install the in-development version of this library, you can use the\nlatest version directly from the GitHub repository. This requires you clone the\nrepo into the folder that holds libraries for the Arduino IDE. The location for\nthis folder varies by operating system, but typically it's in\n`~/Arduino/libraries` on Linux, `~/Documents/Arduino/libraries/` on MacOS, and\n`My Documents\\Arduino\\Libraries` on Windows.\n\nOnce you're in that folder in the terminal, you can then grab the code using the\ngit command line tool:\n\n```\ngit clone https://github.com/tensorflow/tflite-micro-arduino-examples Arduino_TensorFlowLite\n```\n\nTo update your clone of the repository to the latest code, use the following terminal commands:\n```\ncd Arduino_TensorFlowLite\ngit pull\n```\n\n### Checking your Installation\n\nOnce the library has been installed, you should then start the Arduino IDE.\nYou will now see an `Arduino_TensorFlowLite`\nentry in the `File -\u003e Examples` menu of the Arduino IDE. This submenu contains a list\nof sample projects you can try out.\n\n![Hello World](docs/hello_world_screenshot.png)\n\n## Compatibility\n\nThis library is designed for the `Arduino Nano 33 BLE Sense` board. The framework\ncode for running machine learning models should be compatible with most Arm Cortex\nM-based boards, such as the `Raspberry Pi Pico`, but the code to access peripherals\nlike microphones, cameras, and accelerometers is specific to the `Nano 33 BLE Sense`.\n\n## License\n\nThis code is made available under the Apache 2 license.\n\n## Contributing\n\nForks of this library are welcome and encouraged. If you have bug reports or\nfixes to contribute, the source of this code is at [https://github.com/tensorflow/tflite-micro](http://github.com/tensorflow/tflite-micro)\nand all issues and pull requests should be directed there.\n\nThe code here is created through an automatic project generation process\nand may differ from\nthat source of truth, since it's cross-platform and needs to be modified to\nwork within the Arduino IDE.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorflow%2Ftflite-micro-arduino-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftensorflow%2Ftflite-micro-arduino-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorflow%2Ftflite-micro-arduino-examples/lists"}