Install Intel® Distribution of OpenVINO™ toolkit for Linux* from a Docker* Image

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 Linux* and further installation.

System Requirements

Target Operating Systems

Host Operating Systems

Use Docker* Image for CPU

Build a Docker* Image for CPU

To build a Docker image, create a Dockerfile that contains defined variables and commands required to create an OpenVINO toolkit installation image.

Create your Dockerfile using the following example as a template:

FROM ubuntu:16.04
ENV http_proxy $HTTP_PROXY
ENV https_proxy $HTTPS_PROXY
ARG DOWNLOAD_LINK=http://registrationcenter-download.intel.com/akdlm/irc_nas/13231/l_openvino_toolkit_p_2019.0.000.tgz
ARG INSTALL_DIR=/opt/intel/openvino
ARG TEMP_DIR=/tmp/openvino_installer
RUN apt-get update && apt-get install -y --no-install-recommends \
wget \
cpio \
sudo \
lsb-release && \
rm -rf /var/lib/apt/lists/*
RUN mkdir -p $TEMP_DIR && cd $TEMP_DIR && \
wget -c $DOWNLOAD_LINK && \
tar xf l_openvino_toolkit*.tgz && \
cd l_openvino_toolkit* && \
sed -i 's/decline/accept/g' silent.cfg && \
./install.sh -s silent.cfg && \
rm -rf $TEMP_DIR
RUN $INSTALL_DIR/install_dependencies/install_openvino_dependencies.sh
# build Inference Engine samples
RUN mkdir $INSTALL_DIR/deployment_tools/inference_engine/samples/build && cd $INSTALL_DIR/deployment_tools/inference_engine/samples/build && \
/bin/bash -c "source $INSTALL_DIR/bin/setupvars.sh && cmake .. && make -j1"

NOTE: Please replace direct link to the Intel® Distribution of OpenVINO™ toolkit package to the latest version in the DOWNLOAD_LINK variable. You can copy the link from the Intel® Distribution of OpenVINO™ toolkit download page https://software.seek.intel.com/openvino-toolkit after registration. Right click on Offline Installer button on the download page for Linux in your browser and press Copy link address.

You can select which OpenVINO components will be installed by modifying COMPONENTS parameter in the silent.cfg file. For example to install only CPU runtime for the Inference Engine, set COMPONENTS=intel-openvino-ie-rt-cpu__x86_64 in silent.cfg.

To get a full list of available components for installation, run the ./install.sh --list_components command from the unpacked OpenVINO™ toolkit package.

To build a Docker* image for CPU, run the following command:

docker build . -t <image_name> \
--build-arg HTTP_PROXY=<http://your_proxy_server.com:port> \
--build-arg HTTPS_PROXY=<https://your_proxy_server.com:port>

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 <image_name>

Use a Docker* Image for GPU

Build a Docker* Image for GPU

Prerequisites:

Before building a Docker* image on GPU, add the following commands to the Dockerfile example for CPU above:

COPY intel-opencl*.deb /opt/gfx/
RUN cd /opt/gfx && \
dpkg -i intel-opencl*.deb && \
ldconfig && \
rm -rf /opt/gfx
RUN useradd -G video -ms /bin/bash user
USER user

To build a Docker* image for GPU:

  1. Copy Intel® OpenCL™ driver for Ubuntu* (intel-opencl*.deb) from <OPENVINO_INSTALL_DIR>/install_dependencies to the folder with the Dockerfile.
  2. Run the following command to build a Docker* image:
    docker build . -t <image_name> \
    --build-arg HTTP_PROXY=<http://your_proxy_server.com:port> \
    --build-arg HTTPS_PROXY=<https://your_proxy_server.com:port>

Run the Docker* Image for GPU

To make GPU available in the container, attach the GPU to the container using --device /dev/dri option and run the container:

docker run -it –device /dev/dri <image_name>

Use a Docker* Image for Intel® Movidius™ Neural Compute Stick and Intel® Neural Compute Stick 2

Build a Docker* Image for Intel® Movidius™ Neural Compute Stick and Intel® Neural Compute Stick 2

Build a Docker image using the same steps as for CPU.

Run the Docker* Image for Intel® Movidius™ Neural Compute Stick and Intel® Neural Compute Stick 2

Known limitations:

Use one of the following options to run Possible solutions for Intel Movidius Neural Compute Stick:

Notes:

  • It is not secure
  • Conflicts with Kubernetes* and other tools that use orchestration and private networks

NOTES:

  • It is not secure
  • No conflicts with Kubernetes*

Use a Docker* Image for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs

Build Docker* Image for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs

To use the Docker container for inference on Intel® Vision Accelerator Design with Intel® Movidius™ VPUs:

  1. Set up the environment on the host machine, that is going to be used for running Docker*. It is required to execute hddldaemon, which is responsible for communication between the HDDL plugin and the board. To learn how to set up the environment (the OpenVINO package must be pre-installed), see Configuration Guide for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
  2. Prepare the Docker* image. As a base image, you can use the image from the section Building Docker Image for CPU. To use it for inference on Intel® Vision Accelerator Design with Intel® Movidius™ VPUs you need to rebuild the image with adding the following dependencies:
    RUN apt-get update && \
    apt-get install -y libboost-filesystem1.58.0 libboost-thread1.58.0
  3. Run hddldaemon on the host in a separate terminal session using the following command:
    $HDDL_INSTALL_DIR/hddldaemon

Run the Docker* Image for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs

To run the built Docker* image for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, use the following command:

docker run --device=/dev/ion:/dev/ion -v /var/tmp:/var/tmp -ti <image_name>

NOTE:

  • The device /dev/ion need to be shared to be able to use ion buffers among the plugin, hddldaemon and the kernel.
  • Since separate inference tasks share the same HDDL service communication interface (the service creates mutexes and a socket file in /var/tmp), /var/tmp needs to be mounted and shared among them.

Use a Docker* Image for FPGA

Build a Docker* Image for FPGA

FPGA card is not available in container by default, but it can be mounted there with the following pre-requisites:

To build a Docker* image for FPGA:

  1. Set additional environment variables in the Dockerfile:
    ENV CL_CONTEXT_COMPILER_MODE_INTELFPGA=3
    ENV DLA_AOCX=/opt/intel/openvino/a10_devkit_bitstreams/2-0-1_RC_FP11_Generic.aocx
    ENV PATH=/opt/altera/aocl-pro-rte/aclrte-linux64/bin:$PATH
  2. Install the following UDEV rule:
    cat <<EOF > fpga.rules
    KERNEL=="acla10_ref*",GROUP="users",MODE="0660"
    EOF
    sudo cp fpga.rules /etc/udev/rules.d/
    sudo udevadm control --reload-rules
    sudo udevadm trigger
    sudo ldconfig
    Make sure that a container user is added to the "users" group with the same GID as on host.

Run the Docker* container for FPGA

To run the built Docker* container for FPGA, use the following command:

docker run --rm -it \
--mount type=bind,source=/opt/intel/intelFPGA_pro,destination=/opt/intel/intelFPGA_pro \
--mount type=bind,source=/opt/altera,destination=/opt/altera \
--mount type=bind,source=/etc/OpenCL/vendors,destination=/etc/OpenCL/vendors \
--mount type=bind,source=/opt/Intel/OpenCL/Boards,destination=/opt/Intel/OpenCL/Boards \
--device /dev/acla10_ref0:/dev/acla10_ref0 \
<image_name>

Additional Resources

OpenVINO™ toolkit home page: https://software.intel.com/en-us/openvino-toolkit

OpenVINO™ toolkit documentation: https://software.intel.com/en-us/openvino-toolkit/documentation/featured

Intel® Neural Compute Stick 2 Get Started: https://software.intel.com/en-us/neural-compute-stick/get-started