docs/dev/installing.md
Once the project is built you can install OpenVINO™ Runtime into custom location:
cmake --install <BUILDDIR> --prefix <INSTALLDIR>
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
Download a model.
You can download an image classification model from Hugging Face to run the sample
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
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 <architecture> 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 <architecture> 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
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)