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## Software Requirements
- [CMake\*](https://cmake.org/download/) 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 3.4 or higher on Windows\*
## Prerequisites
2. Install Inference Engine Python API dependencies:
```bash
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:
```shellscript
cd <IE_ROOT>
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:
```shellscript
cd <IE_ROOT>
mkdir build
cd build
set PATH=C:\Program Files\Python36\Scripts;%PATH%
cmake -G "Visual Studio 15 2017 Win64" -T "Intel C++ Compiler 18.0" ^
-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.
## Running sample
Before running the Python samples:
- add the folder with built `openvino` Python module (located at `inference-engine/bin/intel64/Release/lib/python_api/python3.6`) 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:
```bash
python3 sample/classification_sample.py -m <path/to/xml> -i <path/to/input/image> -d CPU
```
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