eIQ® Toolkit for End-to-End Model Development and Deployment

EIQ-TOOLKIT

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The eIQ Toolkit enables machine learning development with an intuitive GUI (eIQ Portal) and development workflow tools, along with command line host tool options as part of the eIQ ML software development environment. NXP's eIQ Toolkit enables graph-level profiling capability with runtime insights to help optimize neural network architectures on target EdgeVerse™ processors.

The eIQ Portal, developed in exclusive partnership with Au-Zone Technologies, is an intuitive graphical user interface (GUI) that simplifies vision based ML solutions development. Developers can create, optimize, debug and export ML models, as well as import datasets and models, rapidly train and deploy neural network models and ML workloads for vision applications.

The eIQ Portal provides output software that seamlessly feeds into runtime inference engines.

The eIQ Toolkit and the eIQ Portal are provided with examples demonstrating use cases and guidelines for the different process flow options such as importing pretrained models based on popular frameworks, creating, importing and augmenting datasets to develop models within the tools or integrating with users’ existing flow to leverage the supported inference engines.

Diagram

eIQ Toolkit Block Diagram

eIQ Toolkit Block Diagram
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Features

eIQ Toolkit

  • Enables graph-level profiling capability with runtime insights to help optimize neural network architectures for execution on target EdgeVerse™ processors
  • Includes ML application examples
  • Select from a database of pre-trained models or “Bring your own model” (BYOM)
  • Transfer learning feature supports “Bring your own data (BYOD) flow supports working with user's own data"

eIQ Portal

  • An intuitive graphical user interface (GUI) that simplifies vision ML development and empowers developers of all experience levels
  • Create, optimize, debug and export vision ML models
  • Import datasets and models, rapidly train and deploy neural network models and vision ML workloads
  • Output seamlessly feeds into DeepViewRT, TensorFlow™ Lite, TensorFlow Lite Micro, Glow and ONNX Runtime inference engines
  • Can import models from TensorFlow frameworks or in ONNX format
  • Includes object detection and image classification models for computer vision applications

eIQ Extensions

  • Enhanced add-on features and capabilities
  • Model IP protection, training data enhancements, advanced quantization and more

Supported Devices

  • i.MX8: i.MX 8 Family – Arm® Cortex®-A53, Cortex-A72, Virtualization, Vision, 3D Graphics, 4K Video
  • i.MX8M: i.MX 8M Family - Arm® Cortex®-A53, Cortex-M4, Audio, Voice, Video
  • i.MX8MNANO: i.MX 8M Nano Family - Arm® Cortex®-A53, Cortex-M7
  • IMX8MPLUS: i.MX 8M Plus – Arm® Cortex®-A53, Machine Learning, Vision, Multimedia and Industrial IoT
  • i.MX8X: i.MX 8X Family – Arm® Cortex®-A35, 3D Graphics, 4K Video, DSP, Error Correcting Code on DDR
  • 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-RT500: i.MX RT500 Crossover MCU with Arm® Cortex®-M33, DSP and GPU Cores
  • i.MX-RT1160: i.MX RT1160 Crossover MCU Dual-Core Arm® Cortex®-M7 and Cortex-M4
  • i.MX-RT1050: i.MX RT1050 Crossover MCU with Arm® Cortex®-M7 Core
  • i.MX-RT600: i.MX RT600 Crossover MCU with Arm® Cortex®-M33 and DSP Cores
  • i.MX8MMINI: i.MX 8M Mini - Arm® Cortex®-A53, Cortex-M4, Audio, Voice, Video
  • i.MX-RT1060: i.MX RT1060: Crossover MCU with Arm® Cortex®-M7
  • iMX95: i.MX 95 Applications Processor Family: High-Performance, Safety Enabled Platform with eIQ® Neutron NPU
  • i.MX93: i.MX 93 Applications Processor Family – Arm® Cortex®-A55, ML Acceleration, Power Efficient MPU

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    To find a complete list of our partners that support this software, please see our Partner Marketplace.

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