eIQ® Inference with TF Lite Micro | NXP Semiconductors

Automotive

Industrial

Consumer

Technologies

eIQ® Inference with TensorFlow™ Lite Micro

EIQ-TFLITE-MICRO

The eIQ inference with TensorFlow™ Lite for Microcontrollers (TF Micro) is optimized for running machine learning models on resource constrained devices, including NXP's i.MX RT crossover MCUs.

Faster and smaller than the traditional TensorFlow Lite open source platform for machine learning, this TF Micro implementation enables inferencing at the edge with lower latency and smaller binary size.

Diagram

eIQ® TensorFlow Lite for MCUs

eIQ<sup>&reg;</sup> TensorFlow Lite for MCUs
Get diagram PDF

Features

  • Delivered as middleware in NXP MCUXpresso SDK
  • Optimized for running machine learning models on i.MX RT crossover MCUs
  • Provides the ability to run inferencing on Arm® Cortex®-M
  • Enables inference at the edge with lower latency and smaller binary size

Supported Devices

  • i.MX-RT1050: i.MX RT1050 Crossover MCU with Arm® Cortex®-M7 Core
  • i.MX-RT1060: i.MX RT1060: Crossover MCU with Arm® Cortex®-M7
  • i.MX-RT1064: i.MX RT1064: Crossover MCU with Arm® Cortex®-M7
  • i.MX-RT1170: i.MX RT1170: 1 GHz Crossover MCU with Arm® Cortex® Cores
  • i.MX-RT1160: i.MX RT1160 Crossover MCU Dual-Core Arm® Cortex®-M7 and Cortex-M4
  • i.MX-RT600: i.MX RT600 Crossover MCU with Arm® Cortex®-M33 and DSP Cores
  • i.MX-RT500: i.MX RT500 Crossover MCU with Arm® Cortex®-M33, DSP and GPU Cores

Downloads

Quick reference to our software types.
Filters

1 download

  • Examples and Quick Start Software

    MCUXpresso SDK Builder

    EXTERNALRev 1Jan 28, 20211 KBMCUXPRESSO-SDK-EIQ
    Download

Note: For better experience, software downloads are recommended on desktop.

Y true 0 SSPEIQ-TFLITE-MICROen 4 Application Note Application Note t789 2 Application Note Software Application Note Software t783 1 Fact Sheet Fact Sheet t523 1 en_US en_US en Application Note Application Note 2 1 1 Chinese This application note presents the process of building and deploying deep learning models for Smart Sensing Appliances. It also highlights how to validate and evaluate the performance of a model by running it through different inference engines on an Embedded Sensing Device. 1644318754124703028011zh SSP 4.9 MB None None documents None 1644318754124703028011 /docs/zh/application-note/AN13562.pdf 4943726 /docs/zh/application-note/AN13562.pdf AN13562 documents N N 2022-02-08 Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs /docs/zh/application-note/AN13562.pdf /docs/zh/application-note/AN13562.pdf Application Note N 645036621402383989 2024-07-17 zh Apr 25, 2022 645036621402383989 Application Note Y N Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs 2 English AN13562: This application note presents the process of building and deploying deep learning models for Smart Sensing Appliances. It also highlights how to validate and evaluate the performance of a model by running it through different inference engines on an Embedded Sensing Device. 1644318754124703028011 SSP 4.9 MB None None documents None 1644318754124703028011 /docs/en/application-note/AN13562.pdf 4943726 /docs/en/application-note/AN13562.pdf AN13562 documents N N 2022-02-08 Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs /docs/en/application-note/AN13562.pdf /docs/en/application-note/AN13562.pdf Application Note N 645036621402383989 2024-07-17 pdf N en Sep 27, 2023 645036621402383989 Application Note Y N Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs 2 1 English AN12603SW.zip /docs/en/application-note-software/AN12603SW.zip /docs/en/application-note-software/AN12603SW.zip This application note focuses on handwritten digit recognition on embedded systems through deep learning. It explains the process of creating an embedded machine learning application that can classify handwritten digits and present an example solution based on NXP’s SDK and the eIQ technology. 1574420453849717848145 SSP 419.5 KB None None documents None 1574420453849717848145 /docs/en/application-note/AN12603.pdf 419490 /docs/en/application-note/AN12603.pdf AN12603 documents N N 2019-11-22 Handwritten Digit Recognition Using TensorFlow Lite Micro on i.MX RT devices /docs/en/application-note/AN12603.pdf /docs/en/application-note/AN12603.pdf Application Note N 645036621402383989 2024-07-17 pdf N en Oct 20, 2021 645036621402383989 Application Note Y N Handwritten Digit Recognition Using TensorFlow Lite Micro on i.MX RT devices Application Note Software Application Note Software 1 3 1 English Application Note software for AN12603 1590650375305723857901 SSP 9.1 MB None None documents None 1590650375305723857901 /docs/en/application-note-software/AN12603SW.zip 9081713 /docs/en/application-note-software/AN12603SW.zip AN12603SW documents N N 2020-05-28 Application Note software for AN12603 /docs/en/application-note-software/AN12603SW.zip /docs/en/application-note-software/AN12603SW.zip Application Note Software N 789425793691620447 2022-12-07 zip N en Oct 20, 2021 789425793691620447 Application Note Software Y N Application Note software for AN12603 Fact Sheet Fact Sheet 1 4 4 Japanese Machine learning software for NXP i.MX and MCUs – libraries, example applications, inference engines, HALs 1562948465206707057398ja SSP 653.2 KB None None documents None 1562948465206707057398 /docs/ja/fact-sheet/EIQ-FS.pdf 653150 /docs/ja/fact-sheet/EIQ-FS.pdf EIQ-FS documents N N 2019-07-12 eIQ Software Fact Sheet /docs/ja/fact-sheet/EIQ-FS.pdf /docs/ja/fact-sheet/EIQ-FS.pdf Fact Sheet N 736675474163315314 2022-12-07 ja Jul 11, 2023 736675474163315314 Fact Sheet Y N eIQ 機械学習ソフトウェア開発環境 4 English Machine learning software for NXP i.MX and MCUs – libraries, example applications, inference engines, HALs 1562948465206707057398 SSP 653.2 KB None None documents None 1562948465206707057398 /docs/en/fact-sheet/EIQ-FS.pdf 653150 /docs/en/fact-sheet/EIQ-FS.pdf EIQ-FS documents N N 2019-07-12 eIQ Software Fact Sheet /docs/en/fact-sheet/EIQ-FS.pdf /docs/en/fact-sheet/EIQ-FS.pdf Fact Sheet N 736675474163315314 2022-12-07 pdf N en Jan 21, 2022 736675474163315314 Fact Sheet Y N eIQ Software Fact Sheet false 0 EIQ-TFLITE-MICRO downloads en true 1 Y SSP Y Y Application Note 2 /docs/en/application-note/AN13562.pdf 2022-02-08 1644318754124703028011 SSP 1 Sep 27, 2023 Application Note AN13562: This application note presents the process of building and deploying deep learning models for Smart Sensing Appliances. It also highlights how to validate and evaluate the performance of a model by running it through different inference engines on an Embedded Sensing Device. None /docs/en/application-note/AN13562.pdf English documents 4943726 None 645036621402383989 2024-07-17 N /docs/en/application-note/AN13562.pdf Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs /docs/en/application-note/AN13562.pdf documents 645036621402383989 Application Note N en None Y pdf 2 N N Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs 4.9 MB AN13562 N 1644318754124703028011 /docs/en/application-note/AN12603.pdf 2019-11-22 1574420453849717848145 SSP 2 Oct 20, 2021 Application Note This application note focuses on handwritten digit recognition on embedded systems through deep learning. It explains the process of creating an embedded machine learning application that can classify handwritten digits and present an example solution based on NXP’s SDK and the eIQ technology. None /docs/en/application-note/AN12603.pdf English documents 419490 None 645036621402383989 2024-07-17 N /docs/en/application-note/AN12603.pdf Handwritten Digit Recognition Using TensorFlow Lite Micro on i.MX RT devices /docs/en/application-note/AN12603.pdf documents 645036621402383989 Application Note N en None Y pdf 1 N N Handwritten Digit Recognition Using TensorFlow Lite Micro on i.MX RT devices 419.5 KB AN12603 N 1574420453849717848145 Application Note Software 1 /docs/en/application-note-software/AN12603SW.zip 2020-05-28 1590650375305723857901 SSP 3 Oct 20, 2021 Application Note Software Application Note software for AN12603 None /docs/en/application-note-software/AN12603SW.zip English documents 9081713 None 789425793691620447 2022-12-07 N /docs/en/application-note-software/AN12603SW.zip Application Note software for AN12603 /docs/en/application-note-software/AN12603SW.zip documents 789425793691620447 Application Note Software N en None Y zip 1 N N Application Note software for AN12603 9.1 MB AN12603SW N 1590650375305723857901 Fact Sheet 1 /docs/en/fact-sheet/EIQ-FS.pdf 2019-07-12 1562948465206707057398 SSP 4 Jan 21, 2022 Fact Sheet Machine learning software for NXP i.MX and MCUs – libraries, example applications, inference engines, HALs None /docs/en/fact-sheet/EIQ-FS.pdf English documents 653150 None 736675474163315314 2022-12-07 N /docs/en/fact-sheet/EIQ-FS.pdf eIQ Software Fact Sheet /docs/en/fact-sheet/EIQ-FS.pdf documents 736675474163315314 Fact Sheet N en None Y pdf 4 N N eIQ Software Fact Sheet 653.2 KB EIQ-FS N 1562948465206707057398 true Y Softwares

Documentation

Quick reference to our documentation types.

Filters

4 documents

Compact List

Hardware

Quick reference to our board types.
Filters

4 hardware offerings

Related Software

Quick reference to our software types.

Filters

1 software file

Note: For better experience, software downloads are recommended on desktop.

Training

Filters

3 trainings

Recently viewed products

There are no recently viewed products to display.

View or edit your browsing history