OpenVINO™ toolkit 2020.1 Release Now Available!

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Wednesday, February 5, 2020 - 13:00

OpenVINO™ toolkit 2020.1 Release Now Available!

What's New in 2020.1

  • Post-training Optimization Tool enables significant acceleration improvement. Little or no degradation in accuracy using a model quantization; while streamlining the development process with no model re-training or fine-tuning required.
  • Low-precision runtime for INT8, including native support for “fake quantization” and support for 3D convolution layers along with reduced memory footprint. Enabling developers to add more deep learning models to their applications. 
  • Extends support for custom layers on the Intel® Movidius™ VPU. This enables greater flexibility and customizability for dedicated edge, media and vision inferencing.   
  • Leverages maximized performance optimizations and cross-platform flexibility with the Deep Learning Workbench. Simplify the development and deployment workflow, with support for the Post-training Optimization tool, COCO dataset, new algorithms and improvements in developer experience and interfaces. Watch webinar to learn more. 
  • Added support for new demos and preoptimized, ready-to-deploy models on Open Model Zoo to reduce time to production. They include:
    • End-to-end speech recognition
    • American Sign Language (ASL) recognition
    • Character and text detection with Mask R-CNN
    • 3D human pose estimation
  • Added support for new public models, which includes:
    • For computer vision: MobileNet* v3, Yolo* v3 (from MXNet GluonCV*)
    • For speech and language: LibriSpeech, Automatic Speech Recognition in Reverberant Environments (ASpIRE)
  • New release versioning convention to reflect [MAJOR.MINOR]. MAJOR version reflects significant feature additions, bug fixes, and security patches, and is incremented once a year. MINOR version reflects added functionality, and is incremented 3-4 times a year.

Learn more from the release notes, and join the conversation below.
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