A collection of OpenVX related tools, documentation, and resources contributed by the community. To contribute, create a pull request to add new resource or update/delete an out of date resource. This resource page lives on GitHub and is open for anyone to issue pull requests to.
- Homepage
- Registry - The OpenVX registry contains specifications of the core API, headers, extensions, and related documentation.
- Discussion Forum
- Quick Reference Guide - 1.1, 1.0
- Adopters Process
- Conformant Products
- Conformant Companies
- YouTube Channel
- Book: OpenVX Programming Guide
- AMD OpenVX (AMDOVX) (open-source on GitHub) is a highly optimized implementation of the Khronos OpenVX™ computer vision specification. It is a library that allows for rapid prototyping as well as fast execution on a wide range of computer hardware, including small embedded x86 CPUs and large workstation discrete GPUs. On GitHub: core (OpenVX) and modules (Libraries)
- Cadence - Tensilica Vision DSPs for Imaging, Computer Vision, and Neural Networks and the Tensilica OpenVX Application Programming Kit (APK).
- Imagination - PowerVR GPUs From Imagination pass OpenVX Conformance
- Synopsys - High-Performance, Energy-Efficient Vision Processors
- Texas Instruments’ OpenVX (TIOVX) framework and optimized software libraries accelerate and simplify development for automotive applications using TI’s efficient, heterogeneous Jacinto™ ADAS SoCs.
- VisionWorks - NVIDIA VisionWorks toolkit is a software development package for computer vision (CV) and image processing. VisionWorks™ implements and extends the Khronos OpenVX standard, and it is optimized for CUDA-capable GPUs and SOCs enabling developers to realize CV applications on a scalable and flexible platform.
- Addressing System-Level Optimization with OpenVX Graphs
- OpenVX Tutorial Material
- Videos: OpenVX Tutorial from EVS 2016
- Video: Tutorial Part 1: Kick-off and Introduction to OpenVX Ecosystem
- Video: Tutorial Part 2: Introduction to OpenVX
- Video: Tutorial Part 3: OpenVX Graphs
- Video: Tutorial Part 4: I/O Bandwidth Optimization and User Kernels
- Video: Tutorial part 5: New features in OpenVX 1.1
- Video: OpenVX Workshop for Vision and Neural Network Acceleration - Part I
- Video: OpenVX Workshop for Vision and Neural Network Acceleration - Part II
- Video: OpenVX Workshop for Vision and Neural Network Acceleration - Part III
- Video: OpenVX Workshop for Vision and Neural Network Acceleration - Part IV
- Video: OpenVX - Safety Critical Extension v1.1
- MIVisionX (GitHub) MIVisionX toolkit is a comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit. AMD MIVisionX delivers open source highly optimized implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers.
- AMD OpenVX (open-source on GitHub) is a highly optimized implementation of the Khronos OpenVX™ computer vision specification. It is a library that allows for rapid prototyping as well as fast execution on a wide range of computer hardware, including small embedded x86 CPUs and large workstation discrete GPUs. On Github: core (OpenVX) and modules (Libraries)
- OpenVINO (The OpenVINO toolkit was formerly known as the Intel Computer Vision SDK) Develop applications and solutions that emulate human vision with the Open Visual Inference & Neural Network Optimization (OpenVINO) toolkit. Based on convolutional neural networks (CNN), the toolkit extends workloads across Intel® hardware and maximizes performance.
- Texas Instruments’ OpenVX (TIOVX) framework and optimized software libraries accelerate and simplify development for automotive applications using TI’s efficient, heterogeneous Jacinto™ ADAS SoCs.
- Khronos OpenVX Tutorial - A course covering both the function-based API and the graph API that enable OpenVX developers to efficiently run computer vision algorithms on heterogeneous computing architectures:
- The Embedded Vision Summit schedule: Khronos event page
- Complete tutorial with link to the VirtualBox VM: GitHub
- Videos from the day long tutorial: YouTube.
- Addressing System-Level Optimization with OpenVX Graphs (PDF)
- OpenVX Tutorial (on Github) a series of tutorial exercises.
- OpenVX IEEE Summer School training December 2020 Tutorial