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BuildingForRaspbianStretchOS

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Ilya Lavrenov edited this page Jul 7, 2021 · 19 revisions

Build for Raspbian Stretch* OS

NOTE: Only the MYRIAD plugin is supported.

Table of content

Hardware Requirements

  • Raspberry Pi* 2 or 3 with Raspbian* Stretch OS (32-bit). Check that it's CPU supports ARMv7 instruction set (uname -m command returns armv7l).

    NOTE: Despite the Raspberry Pi* CPU is ARMv8, 32-bit OS detects ARMv7 CPU instruction set. The default gcc compiler applies ARMv6 architecture flag for compatibility with lower versions of boards. For more information, run the gcc -Q --help=target command and refer to the description of the -march= option.

You can compile the Inference Engine for Raspberry Pi* in one of the two ways:

Native Compilation

Native compilation of the Inference Engine is the most straightforward solution. However, it might take at least one hour to complete on Raspberry Pi* 3.

  1. Install dependencies:
sudo apt-get update
sudo apt-get install -y git cmake libusb-1.0-0-dev
  1. Go to the cloned openvino repository:
cd openvino
  1. Initialize submodules:
git submodule update --init --recursive
  1. Create a build folder:
mkdir build && cd build
  1. Build the Inference Engine:
cmake -DCMAKE_BUILD_TYPE=Release -DTHREADING=SEQ .. && make

Cross Compilation Using Docker*

This compilation was tested on the following configuration:

  • Host: Ubuntu* 18.04 (64-bit, Intel® Core™ i7-6700K CPU @ 4.00GHz × 8)
  • Target: Raspbian* Stretch (32-bit, ARMv7, Raspberry Pi* 3)
  1. Install Docker*:
sudo apt-get install -y docker.io
  1. Add a current user to docker group:
sudo usermod -a -G docker $USER

Log out and log in for this to take effect.

  1. Create a directory named ie_cross_armhf and add a text file named Dockerfile with the following content:
FROM debian:stretch

USER root

RUN dpkg --add-architecture armhf && \
    apt-get update && \
    apt-get install -y --no-install-recommends \
    build-essential \
    crossbuild-essential-armhf \
    git \
    wget \
    libusb-1.0-0-dev:armhf \
    libgtk-3-dev:armhf \
    libavcodec-dev:armhf \
    libavformat-dev:armhf \
    libswscale-dev:armhf \
    libgstreamer1.0-dev:armhf \
    libgstreamer-plugins-base1.0-dev:armhf \
    libpython3-dev:armhf \
    python3-pip \
    python-minimal \
    python-argparse

RUN wget https://www.cmake.org/files/v3.14/cmake-3.14.3.tar.gz && \
    tar xf cmake-3.14.3.tar.gz && \
    (cd cmake-3.14.3 && ./bootstrap --parallel=$(nproc --all) && make --jobs=$(nproc --all) && make install) && \
    rm -rf cmake-3.14.3 cmake-3.14.3.tar.gz

RUN git config --global user.name "Your Name" && \
    git config --global user.email "[email protected]"

It uses the Debian* Stretch (Debian 9) OS for compilation because it is a base of the Raspbian* Stretch.

  1. Build a Docker* image:
docker image build -t ie_cross_armhf ie_cross_armhf
  1. Run Docker* container with mounted source code folder from host:
docker run -it -v /absolute/path/to/openvino:/openvino ie_cross_armhf /bin/bash

  1. While in the container:

    1. Go to the cloned openvino repository:
    cd openvino
    1. Create a build folder:
    mkdir build && cd build
    1. Build the Inference Engine:
    cmake -DCMAKE_BUILD_TYPE=Release \
    -DCMAKE_TOOLCHAIN_FILE="../cmake/arm.toolchain.cmake" \
    -DTHREADS_PTHREAD_ARG="-pthread" ..
make --jobs=$(nproc --all)

  2. Press Ctrl+D to exit from Docker. You can find the resulting binaries in the openvino/bin/armv7l/ directory and the OpenCV* installation in the openvino/inference-engine/temp.

NOTE: Native applications that link to cross-compiled Inference Engine library require an extra compilation flag -march=armv7-a.

Additional Build Options

You can use the following additional build options:

  • Required versions of OpenCV packages are downloaded automatically by the CMake-based script. If you want to use the automatically downloaded packages but you already have installed OpenCV packages configured in your environment, you may need to clean the OpenCV_DIR environment variable before running the cmake command; otherwise they won't be downloaded and the build may fail if incompatible versions were installed.

  • If the CMake-based build script cannot find and download the OpenCV package that is supported on your platform, or if you want to use a custom build of the OpenCV library, see: Use Custom OpenCV Builds for details.

  • To build Python API wrapper, install libpython3-dev:armhf and python3-pip packages using apt-get; then install numpy and cython python modules via pip3, adding the following options:

    -DENABLE_PYTHON=ON \
-DPYTHON_EXECUTABLE=/usr/bin/python3.5 \
-DPYTHON_LIBRARY=/usr/lib/arm-linux-gnueabihf/libpython3.5m.so \
-DPYTHON_INCLUDE_DIR=/usr/include/python3.5

  • nGraph-specific compilation options: -DNGRAPH_ONNX_IMPORT_ENABLE=ON enables the building of the nGraph ONNX importer. -DNGRAPH_DEBUG_ENABLE=ON enables additional debug prints.

(Optional) Additional Installation Steps for the Intel® Neural Compute Stick 2

NOTE: These steps are only required if you want to perform inference on the Intel® Neural Compute Stick 2 using the Inference Engine MYRIAD Plugin. See also Intel® Neural Compute Stick 2 Get Started.

For Linux, Raspbian* Stretch OS

  1. Add the current Linux user to the users group; you will need to log out and log in for it to take effect:
sudo usermod -a -G users "$(whoami)"
  1. To perform inference on Intel® Neural Compute Stick 2, install the USB rules as follows:
cat <<EOF > 97-myriad-usbboot.rules
SUBSYSTEM=="usb", ATTRS{idProduct}=="2485", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1"
SUBSYSTEM=="usb", ATTRS{idProduct}=="f63b", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1"
EOF
sudo cp 97-myriad-usbboot.rules /etc/udev/rules.d/
sudo udevadm control --reload-rules
sudo udevadm trigger
sudo ldconfig
rm 97-myriad-usbboot.rules

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