eIQ Inference with DeepViewRT | NXP 半导体

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eIQ™ Inference with DeepViewRT™

EIQ-INFERENCE-DEEPVIEWRT

eIQ Inference with DeepViewRT™是一款平台经过优化的运行时推理引擎，可扩展到各种恩智浦设备和神经网络计算引擎。该推理引擎免费提供，让资源受限的设备可使用紧凑的代码，这些设备包括 i.MX RT 跨界MCU (Arm® Cortex®-M 内核)以及i.MX 应用处理器(Cortex-A 和 Cortex-M内核、专用神经处理单元(NPU)和 GPU​)。

该推理引擎提供两种版本：恩智浦Yocto BSP标准版本，用于基于Linux®操作系统的开发，以及MCUXpresso SDK版本，用于基于嵌入式实时操作系统MCU的开发。

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eIQ Inference with DeepViewRT Block Diagram

eIQ Inference with DeepViewRT Block Diagram
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特征

  • 平台经优化，可在i.MX RT跨界MCU和i.MX 8M系列应用处理器上运行机器学习模型
  • 具有在Arm™Cortex™-M和A内核、GPU和NPU上运行推理的能力
  • 可作为恩智浦MCUXpresso SDK版本和Yocto BSP版本(用于基于Linux™操作系统的开发)中的中间件
  • 与Au-Zone Technologies独家合作实现

支持的器件

  • i.MX8M: i.MX 8M系列 - Arm® Cortex®-A53、Cortex-M4、音频、语音、视频
  • i.MX8MMINI: i.MX 8M Mini - Arm® Cortex®-A53, Cortex-M4, 音频, 语音, 视频
  • i.MX8MNANO: i.MX 8M Nano系列 - Arm® Cortex®-A53、Cortex-M7
  • IMX8MPLUS: i.MX 8M Plus – Arm® Cortex®-A53，机器学习，视觉，多媒体和工业物联网
  • i.MX-RT1064: i.MX RT1064: 跨界MCU， 配备Arm®Cortex®-M7
  • i.MX-RT1170: i.MX RT1170: 1GHz跨界MCU，配备Arm®Cortex®内核

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  • 样品及快速入门软件

    MCUXpresso SDK Builder

    EXTERNAL版本 1Jan 28, 20211 KBMCUXPRESSO-SDK-EIQ
    下载

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Y true 0 SSPEIQ-INFERENCE-DEEPVIEWRTzh 2 应用笔记 Application Note t789 1 简介 Fact Sheet t523 1 zh zh zh 应用笔记 Application Note 1 1 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 en Sep 27, 2023 645036621402383989 Application Note Y N Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs 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 pdf N zh Apr 25, 2022 645036621402383989 Application Note Y N Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs 简介 Fact Sheet 1 2 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-INFERENCE-DEEPVIEWRT downloads zh-Hans true 1 Y SSP Y Y 应用笔记 1 /docs/zh/application-note/AN13562.pdf 2022-02-08 1644318754124703028011zh SSP 1 Apr 25, 2022 Application Note 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/zh/application-note/AN13562.pdf Chinese documents 4943726 None 645036621402383989 2024-07-17 N /docs/zh/application-note/AN13562.pdf Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs /docs/zh/application-note/AN13562.pdf documents 645036621402383989 Application Note N zh None Y pdf 1 N N Building and Benchmarking Deep Learning Models for Smart Sensing Appliances on MCUs 4.9 MB AN13562 N 1644318754124703028011 简介 1 /docs/en/fact-sheet/EIQ-FS.pdf 2019-07-12 1562948465206707057398 SSP 2 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

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