eIQ® Auto Deep Learning (DL) Toolkit for S32V23x Processors
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.
ソフトウェア詳細
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
システム要件
- Ubuntu LTS 16.04 64-bit
- NXP Vision SDK Software for S32V234
- SBC-S32V234 S32V Vision and Sensor Fusion Evaluation Board
ダウンロード
クイック・リファレンス ソフトウェア・タイプ.
2 ダウンロード
-
BSPとデバイスドライバ
Vision SDK Software
-
BSPとデバイスドライバ
Automotive SW for S32V234 – Linux BSP
注: より快適にご利用いただくために、ソフトウェアのダウンロードはデスクトップで行うことを推奨します。
ドキュメント
クイック・リファレンス ドキュメンテーションの種類.
