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Installing

Once the project is built you can install OpenVINO™ Runtime into custom location:

cmake --install <BUILDDIR> --prefix <INSTALLDIR>

Build and Run Samples

  1. Build samples.

    To build C++ sample applications, run the following commands:

    Linux and macOS:

    cd <INSTALLDIR>/samples/cpp
./build_samples.sh

    Windows Command Prompt:

    cd <INSTALLDIR>\samples\cpp
build_samples_msvc.bat

    Windows PowerShell:

    & <path-to-build-samples-folder>/build_samples.ps1

  2. Download a model.

    You can download an image classification model from Hugging Face to run the sample

  3. Convert the model.

    Linux and macOS:

    ovc <path-to-your-model> --compress_to_fp16=True

    Windows:

    ovc <path-to-your-model> --compress_to_fp16=True

  4. Run inference on the sample.

    Set up the OpenVINO environment variables:

    Linux and macOS:

    source <INSTALLDIR>/setupvars.sh

    Windows Command Prompt:

    <INSTALLDIR>\setupvars.bat

    Windows PowerShell:

    . <path-to-setupvars-folder>/setupvars.ps1

    The following commands run the Image Classification Code Sample using the [dog.bmp](https://storage.openvinotoolkit.org/data/test_data/images/ 224x224/dog.bmp) file as an input image, the model in IR format, and on different hardware devices:

    Linux and macOS:

    cd ~/openvino_cpp_samples_build/<architecture>/Release
./classification_sample_async -i <path-to-input-image>/dog.bmp -m <path-to-your-model>/model.xml -d CPU

    where the is the output of uname -m, for example, intel64, armhf, or aarch64.

    Windows:

    cd  %USERPROFILE%\Documents\Intel\OpenVINO\openvino_cpp_samples_build\<architecture>\Release
.\classification_sample_async.exe -i <path-to-input-image>\dog.bmp -m <path-to-your-model>\model.xml -d CPU

    where the is either intel64 or aarch64 depending on the platform architecture.

When the sample application is complete, you see the label and confidence data for the top 10 categories on the display:

Below are results of using the googlenet-v1 model.

Top 10 results:

Image dog.bmp

classid probability
------- -----------
156     0.6875963
215     0.0868125
218     0.0784114
212     0.0597296
217     0.0212105
219     0.0194193
247     0.0086272
157     0.0058511
216     0.0057589
154     0.0052615

Adding OpenVINO Runtime to Your Project

For CMake projects, set the OpenVINO_DIR and when you run CMake tool:

cmake -DOpenVINO_DIR=<INSTALLDIR>/runtime/cmake .

Then you can find OpenVINO Runtime by [find_package]:

find_package(OpenVINO REQUIRED)
add_executable(ov_app main.cpp)
target_link_libraries(ov_app PRIVATE openvino::runtime)

add_executable(ov_c_app main.c)
target_link_libraries(ov_c_app PRIVATE openvino::runtime::c)

See also