eIQ® Auto Deep Learning (DL) Toolkit for S32V23x Processors

EIQ-AUTO-TOOLKIT

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The NXP eIQ® Auto Deep Learning toolkit for S32V23x processors is an automotive-grade deep learning (DL) toolkit enabling developers to transition their DL algorithms seamlessly from the development environment to full implementation application.
The eIQ Auto toolkit helps to satisfy stringent automotive quality and reliability standards. The toolkit is comprised of software, accompanying tools, and libraries like TensorFlow, PyTorch, Caffe, and ONNX.

Our eIQ Auto toolkit community will provide you with the needed content and collateral for your application development. Request access to be part of the community.

Features

  • Training Frameworks: Interface to standard frameworks like TensorFlow, Pytorch, Caffe, and ONNX
  • Optimization: Prunes, quantizes, and compresses the Neural Network
  • Embedded Deployment: Automated neural net layer deployment to the optimum available compute resource
  • Auto Quality Inference Engine: A-SPICE qualified inference engine
  • Different types of networks are supported including detection, classification and segmentation
  • Includes optimized support for the following networks: MobileNetV1, MobileNetV2, SqueezeNet1.1, SSDMobileNet, ResNet-50, DeepLab v3 and SqueezeSeg

System Requirements

Downloads

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2 downloads

  • BSPs and Device Drivers

    Vision SDK Software

    FLEXERARev 1.5.1Mar 24, 2020 11:58:001 KBSW32V23-VSDK001E
    Download
  • BSPs and Device Drivers

    Automotive SW for S32V234 – Linux BSP

    FLEXERARev 23.0Mar 24, 2020 11:58:001 KBSW32XX-LINUXBSP01D
    Download

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

Documentation

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1 documents

Hardware

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2 hardware offerings

Training

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3 trainings

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