openvino/inference-engine/ie_bridges/python

Software Requirements

• CMake* 3.9 or later
• Microsoft* Visual Studio 2015 or later on Windows*
• gcc 4.8 or later on Linux
• Python 2.7 or higher on Linux*
• Python 3.6 or higher on Windows*

Prerequisites

2. Install Inference Engine Python API dependencies:

pip3 install -r requirements.txt

Building on Linux

Build Inference Engine Python API alongside with the Inference Engine build. You need to run Inference Engine build with the following flags:

  cd <INSTALL_DIR>/openvino
  mkdir -p build
  cd build
  cmake -DENABLE_PYTHON=ON -DPYTHON_EXECUTABLE=`which python3.6` \
  	-DPYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.6m.so \
  	-DPYTHON_INCLUDE_DIR=/usr/include/python3.6 ..
  make -j16

Building on Windows

You need to run Inference Engine build with the following flags:

	cd <INSTALL_DIR>/openvino
	mkdir build
	cd build
	set PATH=C:\Program Files\Python36\Scripts;%PATH%
	cmake -G "Visual Studio 15 2017 Win64" ^
		-DENABLE_PYTHON=ON ^
		-DPYTHON_EXECUTABLE="C:\Program Files\Python36\python.exe" ^
		-DPYTHON_INCLUDE_DIR="C:\Program Files\Python36\include" ^
		-DPYTHON_LIBRARY="C:\Program Files\Python36\libs\python36.lib" ..

Then build generated solution INFERENCE_ENGINE_DRIVER.sln using Microsoft* Visual Studio or run cmake --build . --config Release to build from the command line.

Building Python wheel

1. Install Inference Engine Python API dependencies:

pip3 install -r wheel/requirements-dev.txt

2. Install the patchelf tool on Linux only:

sudo apt install patchelf

3. Run Inference Engine build with the following options:

-DENABLE_PYTHON=ON
-DENABLE_WHEEL=ON

Running sample

Before running the Python samples:

• add the folder with built openvino Python module (located at bin/intel64/Release/lib/python_api/python3.6 for Linux) to the PYTHONPATH environment variable.
• add the folder with Inference Engine libraries to LD_LIBRARY_PATH variable on Linux (or PATH on Windows).

Example of command line to run classification sample:

python3 sample/classification_sample.py -m <path/to/xml> -i <path/to/input/image> -d CPU