The Intel® Distribution of OpenVINO™ toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNN), the toolkit extends computer vision (CV) workloads across Intel® hardware, maximizing performance. The Intel® Distribution of OpenVINO™ toolkit includes the Intel® Deep Learning Deployment Toolkit.
This guide provides the steps for creating a Docker* image with Intel® Distribution of OpenVINO™ toolkit for Windows* and further installation.
System Requirements
Target Operating Systems
Host Operating Systems
- Windows 10*, 64-bit Pro, Enterprise or Education (1607 Anniversary Update, Build 14393 or later) editions
- Windows Server* 2016 or higher
Prebuilt Images
Prebuilt images are available on Docker Hub.
Build a Docker* Image for CPU
You can use available Dockerfiles or generate a Dockerfile with your setting via DockerHub CI Framework for Intel® Distribution of OpenVINO™ toolkit. The Framework can generate a Dockerfile, build, test, and deploy an image with the Intel® Distribution of OpenVINO™ toolkit.
Install Additional Dependencies
Install CMake
To add CMake to the image, add the following commands to the Dockerfile:
RUN powershell.exe -Command `
Invoke-WebRequest -URI https://cmake.org/files/v3.14/cmake-3.14.7-win64-x64.msi -OutFile %TMP%\\cmake-3.14.7-win64-x64.msi ; `
Start-Process %TMP%\\cmake-3.14.7-win64-x64.msi -ArgumentList '/quiet /norestart' -Wait ; `
Remove-Item %TMP%\\cmake-3.14.7-win64-x64.msi -Force
RUN SETX /M PATH "C:\Program Files\CMake\Bin;%PATH%"
In case of proxy issues, please add the ARG HTTPS_PROXY
and -Proxy %HTTPS_PROXY%
settings to the powershell.exe
command to the Dockerfile. Then build a docker image:
docker build . -t <image_name> `
--build-arg HTTPS_PROXY=<https://your_proxy_server:port>
Install Microsoft Visual Studio* Build Tools
You can add Microsoft Visual Studio Build Tools* to a Windows* OS Docker image. Available options are to use offline installer for Build Tools (follow the Instruction for the offline installer) or to use the online installer for Build Tools (follow Instruction for the online installer). Microsoft Visual Studio Build Tools* are licensed as a supplement your existing Microsoft Visual Studio* license. Any images built with these tools should be for your personal use or for use in your organization in accordance with your existing Visual Studio* and Windows* licenses.
To add MSBuild 2019 to the image, add the following commands to the Dockerfile:
RUN powershell.exe -Command Invoke-WebRequest -URI https://aka.ms/vs/16/release/vs_buildtools.exe -OutFile %TMP%\\vs_buildtools.exe
RUN %TMP%\\vs_buildtools.exe --quiet --norestart --wait --nocache `
--installPath "C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools" `
--add Microsoft.VisualStudio.Workload.MSBuildTools `
--add Microsoft.VisualStudio.Workload.UniversalBuildTools `
--add Microsoft.VisualStudio.Workload.VCTools --includeRecommended `
--remove Microsoft.VisualStudio.Component.Windows10SDK.10240 `
--remove Microsoft.VisualStudio.Component.Windows10SDK.10586 `
--remove Microsoft.VisualStudio.Component.Windows10SDK.14393 `
--remove Microsoft.VisualStudio.Component.Windows81SDK || IF "%ERRORLEVEL%"=="3010" EXIT 0 && powershell set-executionpolicy remotesigned
In case of proxy issues, please use an offline installer for Build Tools (follow Instruction for the offline installer.
Run the Docker* Image for CPU
To install the OpenVINO toolkit from the prepared Docker image, run the image with the following command:
docker run -it --rm <image_name>
If you want to try some demos then run image with the root privileges (some additional 3-rd party dependencies will be installed):
docker run -itu ContainerAdministrator --rm <image_name> cmd /S /C "cd deployment_tools\demo && demo_security_barrier_camera.bat -d CPU -sample-options -no_show"
Build and Run the Docker* Image for GPU
GPU Acceleration in Windows containers feature requires to meet Windows host, OpenVINO toolkit and Docker* requirements:
- Windows requirements:
- The container host must be running Windows Server 2019 or Windows 10 of version 1809 or higher.
- The container base image must be
mcr.microsoft.com/windows:1809
or higher. Windows Server Core and Nano Server container images are not currently supported.
- The container host must be running Docker Engine 19.03 or higher.
- The container host must have GPU running display drivers of version WDDM 2.5 or higher.
- OpenVINO™ GPU requirement:
- Intel Graphics Driver for Windows of version 15.65 or higher.
- Docker isolation mode requirement:
Build a Docker* Image for Your Host System
- Reuse one of available Dockerfiles. You can also use your own Dockerfile.
- Check your Windows host and container isolation process compatibility.
- Find the appropriate Windows container base image on DockerHub* and set up your host/container version in the
FROM
Dockerfile instruction.
For example, in openvino_c_dev_2021.dockerfile, change:
FROM mcr.microsoft.com/windows/servercore:ltsc2019 AS ov_base
to
FROM mcr.microsoft.com/windows:20H2
- Build the Docker image
docker build --build-arg package_url=<OpenVINO pkg> -f <Dockerfile> -t <image_name> .
- Copy
OpenCL.dll
from your C:\Windows\System32
host folder to any temp
directory: mkdir C:\tmp
copy C:\Windows\System32\OpenCL.dll C:\tmp
Run the Docker* Image for GPU
- To try inference on a GPU, run the image with the following command:
docker run -it --rm -u ContainerAdministrator --isolation process --device class/5B45201D-F2F2-4F3B-85BB-30FF1F953599 -v C:\Windows\System32\DriverStore\FileRepository\iigd_dch.inf_amd64_518f2921ba495409:C:\Windows\System32\DriverStore\FileRepository\iigd_dch.inf_amd64_518f2921ba495409 -v C:\tmp:C:\tmp <image_name>
where
--device class/5B45201D-F2F2-4F3B-85BB-30FF1F953599
is a reserved interface class GUID for a GPU device.
C:\Windows\System32\DriverStore\FileRepository\iigd_dch.inf_amd64_518f2921ba495409
is the path to OpenCL driver home directory. To find it on your PC, run the C:\Windows\System32\DriverStore\FileRepository\iigd_dch.inf_amd64_*
regular expression.
C:\tmp
is the folder with the copy of OpenCL.dll
from your C:\Windows\System32
host folder.
- Copy
OpenCL.dll
to the C:\Windows\System32
folder inside the container and set appropriate registry entry. Now you can run inference on a GPU device: copy C:\tmp\OpenCL.dll C:\Windows\System32\ && reg add "HKLM\SOFTWARE\Khronos\OpenCL\Vendors" /v "C:\Windows\System32\DriverStore\FileRepository\iigd_dch.inf_amd64_518f2921ba495409\ocl\bin\x64\intelocl64.dll" /t REG_DWORD /d 0
- For example, run the
demo_security_barrier_camera
demo with the command below:
cd bin && setupvars.bat && cd ../ && cd deployment_tools\demo && demo_security_barrier_camera.bat -d GPU -sample-options -no_show
NOTE: Addittional third-party dependencies will be installed.
Troubleshooting
If you got proxy issues, please setup proxy settings for Docker. See the Proxy section in the Install the DL Workbench from Docker Hub* topic.
Additional Resources