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.

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図

eIQ® TensorFlow Lite for MCUs

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

対応製品

  • i.MX-RT1050: i.MX RT1050 Arm® Cortex®-M7コア搭載クロスオーバーMCU
  • i.MX-RT1060: i.MX RT1060：Arm® Cortex®-M7搭載クロスオーバーMCU
  • i.MX-RT1064: i.MX RT1064：Arm® Cortex®-M7搭載クロスオーバーMCU
  • i.MX-RT1170: i.MX RT1170：Arm® Cortex®コア搭載1 GHzクロスオーバーMCU
  • i.MX-RT1160: i.MX RT1160 デュアルコアArm® Cortex®-M7およびCortex-M4搭載クロスオーバーMCU
  • i.MX-RT600: i.MX RT600 Arm® Cortex®-M33およびDSPコア搭載クロスオーバーMCU
  • i.MX-RT500: i.MX RT500 Arm® Cortex®-M33、DSP、GPUコア搭載クロスオーバーMCU

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    MCUXpresso SDK Builder

    EXTERNAL改訂 1Jan 28, 2021 02:41:001 KBMCUXPRESSO-SDK-EIQ
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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 アプリケーション・ノート・ソフトウェア 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 ファクト・シート Fact Sheet 1 4 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 en Jan 21, 2022 736675474163315314 Fact Sheet Y N eIQ Software Fact Sheet 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 pdf N ja Jul 11, 2023 736675474163315314 Fact Sheet Y N eIQ 機械学習ソフトウェア開発環境 false 0 EIQ-TFLITE-MICRO downloads ja true 1 Y SSP Y Y アプリケーション・ノート 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 アプリケーション・ノート・ソフトウェア 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 ファクト・シート 1 /docs/ja/fact-sheet/EIQ-FS.pdf 2019-07-12 1562948465206707057398ja SSP 4 Jul 11, 2023 Fact Sheet Machine learning software for NXP i.MX and MCUs – libraries, example applications, inference engines, HALs None /docs/ja/fact-sheet/EIQ-FS.pdf Japanese documents 653150 None 736675474163315314 2022-12-07 N /docs/ja/fact-sheet/EIQ-FS.pdf eIQ 機械学習ソフトウェア開発環境 /docs/ja/fact-sheet/EIQ-FS.pdf documents 736675474163315314 Fact Sheet N ja None Y pdf 4 N N eIQ Software Fact Sheet 653.2 KB EIQ-FS N 1562948465206707057398 true Y Softwares

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