espressif / esp-tflite-micro

TensorFlow Lite Micro for Espressif Chipsets
Apache License 2.0
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TensorFlow Lite Micro for Espressif Chipsets

Component Registry

Build Status

Build Type Status
Examples Build CI

How to Install

Install the ESP IDF

Follow the instructions of the ESP-IDF get started guide to setup the toolchain and the ESP-IDF itself.

The next steps assume that this installation is successful and the IDF environment variables are set. Specifically,

Using the component

Run the following command in your ESP-IDF project to install this component:

idf.py add-dependency "esp-tflite-micro"

Building the example

To get the example, run the following command:

idf.py create-project-from-example "esp-tflite-micro:<example_name>"

Note:

Available examples are:

Set the IDF_TARGET (For ESP32-S3 target, minimum IDF version release/v4.4 is needed)

idf.py set-target esp32s3

To build the example, run:

idf.py build

Load and run the example

To flash (replace /dev/ttyUSB0 with the device serial port):

idf.py --port /dev/ttyUSB0 flash

Monitor the serial output:

idf.py --port /dev/ttyUSB0 monitor

Use Ctrl+] to exit.

The previous two commands can be combined:

idf.py --port /dev/ttyUSB0 flash monitor

ESP-NN Integration

ESP-NN contains optimized kernel implementations for kernels used in TFLite Micro. The library is integrated with this repo and gets compiled as a part of every example. Additional information along with performance numbers can be found here.

Performance Comparison

A quick summary of ESP-NN optimisations, measured on various chipsets:

Target TFLite Micro Example without ESP-NN with ESP-NN CPU Freq
ESP32-S3 Person Detection 2300ms 54ms 240MHz
ESP32 Person Detection 4084ms 380ms 240MHz
ESP32-C3 Person Detection 3355ms 426ms 160MHz

Note:

Detailed kernelwise performance can be found here.

Sync to latest TFLite Micro upstream

As per the upstream repository policy, the tflite-lib is copied into the components directory in this repository. We keep updating this to the latest upstream version from time to time. Should you, in any case, wish to update it locally, you may run the scripts/sync_from_tflite_micro.sh script.

Contributing

License

This component and the examples are provided under Apache 2.0 license, see LICENSE file for details.

TensorFlow library code and third_party code contains their own license specified under respective repos.