Khronos Releases OpenVX 1.3 Open Standard for Cross-Platform Vision and Machine Intelligence Acceleration
Today The Khronos Group, announces the ratification and public release of the OpenVX™ 1.3 specification, along with code samples and a prototype conformance test suite. OpenVX is a royalty-free open standard for portable, optimized, and power-efficient vision and machine learning inferencing acceleration, vital to embedded and real-time use cases, such as face-, body-, and gesture-tracking, smart video surveillance, advanced driver assistance systems, object and scene reconstruction, augmented reality, visual inspection, robotics, and more. Also available today is an open source implementation of OpenVX 1.3 for Raspberry Pi to make OpenVX widely accessible to developers. The new specification can be found on the OpenVX registry.
Today The Khronos Group announces a significant expansion in the ecosystem for the NNEF™ (Neural Network Exchange Format) open, royalty-free standard that enables hardware manufacturers to reliably exchange trained neural networks between training frameworks and inference engines. New and improved NNEF open source convertors, including for TensorFlow Lite and ONNX, enables NNEF to be used to carry trained frameworks from a wider range of training frameworks. A set of extensions to the NNEF 1.0 specification enable NNEF files to contain a richer network of operations and topologies. Finally, an openly available NNEF Model Zoo enables inferencing engines to test their reliable import of NNEF models. More information on NNEF can be found at the NNEF Home Page.