MIVisionX

MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX also delivers a highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions.

MIT licensed doc Build Status

MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized conformant open-source 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 computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers.

Latest Release

GitHub tag (latest SemVer)

Table of Contents

Documentation

Run the steps below to build documentation locally.

AMD OpenVX™

AMD OpenVX™ is a highly optimized conformant open source implementation of the Khronos OpenVX™ 1.3 computer vision specification. It 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.

Khronos OpenVX™ 1.0.1 conformant implementation is available in MIVisionX Lite

AMD OpenVX™ Extensions

The OpenVX framework provides a mechanism to add new vision functionality to OpenVX by vendors. This project has below mentioned OpenVX modules and utilities to extend amd_openvx, which contains the AMD OpenVX™ Core Engine.

Applications

MIVisionX has several applications built on top of OpenVX modules, it uses AMD optimized libraries to build applications that can be used to prototype or use as a model to develop products.

Neural Net Model Compiler & Optimizer

Neural Net Model Compiler & Optimizer converts pre-trained neural net models to MIVisionX runtime code for optimized inference.

rocAL

The ROCm Augmentation Library - rocAL is designed to efficiently decode and process images and videos from a variety of storage formats and modify them through a processing graph programmable by the user.

Toolkit

MIVisionX Toolkit, is a comprehensive set of helpful tools for neural net creation, development, training, and deployment. The Toolkit provides you with helpful tools to design, develop, quantize, prune, retrain, and infer your neural network work in any framework. The Toolkit is designed to help you deploy your work to any AMD or 3rd party hardware, from embedded to servers.

MIVisionX provides you with tools for accomplishing your tasks throughout the whole neural net life-cycle, from creating a model to deploying them for your target platforms.

Utilities

Prerequisites

Hardware

Operating System & Prerequisites

Windows

macOS

Linux

Prerequisites setup script for Linux

For the convenience of the developer, we provide the setup script MIVisionX-setup.py which will install all the dependencies required by this project.

NOTE: This script only needs to be executed once.

Prerequisites for running the script

Build & Install MIVisionX

Windows

Using Visual Studio

macOS

macOS build instructions

Linux

Using apt-get / yum / zypper

Using MIVisionX-setup.py

Verify the Installation

Verifying on Linux / macOS

Verifying on Windows

Docker

MIVisionX provides developers with docker images for Ubuntu 20.04 / 22.04. Using docker images developers can quickly prototype and build applications without having to be locked into a single system setup or lose valuable time figuring out the dependencies of the underlying software.

Docker files to build MIVisionX containers are available

MIVisionX Docker

Docker Workflow on Ubuntu 20.04/22.04

Prerequisites

Workflow

Run docker image: Local Machine

sudo docker run -it --privileged --device=/dev/kfd --device=/dev/dri --device=/dev/mem --cap-add=SYS_RAWIO  --group-add video --shm-size=4g --ipc="host" --network=host mivisionx/ubuntu-20.04:latest

Option 1: Map localhost directory on the docker image

Technical Support

Please email mivisionx.support@amd.com for questions, and feedback on MIVisionX.

Please submit your feature requests, and bug reports on the GitHub issues page.

Release Notes

Latest Release Version

GitHub tag (latest SemVer)

Changelog

Review all notable changes with the latest release

Tested configurations

Known issues

MIVisionX Dependency Map

HIP Backend

Docker Image: sudo docker build -f docker/ubuntu20/{DOCKER_LEVEL_FILE_NAME}.dockerfile -t {mivisionx-level-NUMBER} .

Build Level MIVisionX Dependencies Modules Libraries and Executables Docker Tag
Level_1 cmake
gcc
g++
amd_openvx
utilities
#c5f015 libopenvx.so - OpenVX™ Lib - CPU
#c5f015 libvxu.so - OpenVX™ immediate node Lib - CPU
#c5f015 runvx - OpenVX™ Graph Executor - CPU with Display OFF
Docker Image Version (tag latest semver)
Level_2 ROCm HIP
+Level 1
amd_openvx
amd_openvx_extensions
utilities
#c5f015 libopenvx.so - OpenVX™ Lib - CPU/GPU
#c5f015 libvxu.so - OpenVX™ immediate node Lib - CPU/GPU
#c5f015 runvx - OpenVX™ Graph Executor - Display OFF
Docker Image Version (tag latest semver)
Level_3 OpenCV
FFMPEG
+Level 2
amd_openvx
amd_openvx_extensions
utilities
#1589F0 libopenvx.so - OpenVX™ Lib
#1589F0 libvxu.so - OpenVX™ immediate node Lib
#c5f015 libvx_amd_media.so - OpenVX™ Media Extension
#c5f015 libvx_opencv.so - OpenVX™ OpenCV InterOp Extension
#c5f015 mv_compile - Neural Net Model Compile
#c5f015 runvx - OpenVX™ Graph Executor - Display ON
Docker Image Version (tag latest semver)
Level_4 MIOpenGEMM
MIOpen
ProtoBuf
+Level 3
amd_openvx
amd_openvx_extensions
apps
utilities
#1589F0 libopenvx.so - OpenVX™ Lib
#1589F0 libvxu.so - OpenVX™ immediate node Lib
#1589F0 libvx_amd_media.so - OpenVX™ Media Extension
#1589F0 libvx_opencv.so - OpenVX™ OpenCV InterOp Extension
#1589F0 mv_compile - Neural Net Model Compile
#1589F0 runvx - OpenVX™ Graph Executor - Display ON
#c5f015 libvx_nn.so - OpenVX™ Neural Net Extension
Docker Image Version (tag latest semver)
Level_5 AMD_RPP
rocAL deps
+Level 4
amd_openvx
amd_openvx_extensions
apps
rocAL
utilities
#1589F0 libopenvx.so - OpenVX™ Lib
#1589F0 libvxu.so - OpenVX™ immediate node Lib
#1589F0 libvx_amd_media.so - OpenVX™ Media Extension
#1589F0 libvx_opencv.so - OpenVX™ OpenCV InterOp Extension
#1589F0 mv_compile - Neural Net Model Compile
#1589F0 runvx - OpenVX™ Graph Executor - Display ON
#1589F0 libvx_nn.so - OpenVX™ Neural Net Extension
#c5f015 libvx_rpp.so - OpenVX™ RPP Extension
#c5f015 librocal.so - Radeon Augmentation Library
#c5f015 rocal_pybind.so - rocAL Pybind Lib
Docker Image Version (tag latest semver)

NOTE: OpenVX and the OpenVX logo are trademarks of the Khronos Group Inc.