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Open Model Zoo Demos

The Open Model Zoo demo applications are console applications that provide robust application templates to help you implement specific deep learning scenarios. These applications involve increasingly complex processing pipelines that gather analysis data from several models that run inference simultaneously, such as detecting a person in a video stream along with detecting the person's physical attributes, such as age, gender, and emotional state

For the Intel® Distribution of OpenVINO™ toolkit, the demos are available after installation in the following directory: <INSTALL_DIR>/deployment_tools/open_model_zoo/demos. The demos can also be obtained from the Open Model Zoo GitHub repository. C++, C++ G-API and Python* versions are located in the cpp, cpp_gapi and python subdirectories respectively.

The Open Model Zoo includes the following demos:

Media Files Available for Demos

To run the demo applications, you can use images and videos from the media files collection available at https://github.com/intel-iot-devkit/sample-videos.

Demos that Support Pre-Trained Models

NOTE: Inference Engine HDDL plugin is available in proprietary distribution only.

You can download the Intel pre-trained models or public pre-trained models using the OpenVINO Model Downloader.

Build the Demo Applications

To be able to build demos you need to source Inference Engine and OpenCV environment from a binary package which is available as proprietary distribution. Please run the following command before the demos build (assuming that the binary package was installed to <INSTALL_DIR>):

source <INSTALL_DIR>/deployment_tools/bin/setupvars.sh

You can also build demos manually using Inference Engine built from the openvino repo. In this case please set InferenceEngine_DIR environment variable to a folder containing InferenceEngineConfig.cmake and ngraph_DIR to a folder containing ngraphConfig.cmake in a build folder. Please also set the OpenCV_DIR to point to the OpenCV package to use. The same OpenCV version should be used both for Inference Engine and demos build. Alternatively these values can be provided via command line while running cmake. See CMake's search procedure. Please refer to the Inference Engine build instructions for details. Please also add path to built Inference Engine libraries to LD_LIBRARY_PATH (Linux*) or PATH (Windows*) variable before building the demos.

Build the Demo Applications on Linux*

The officially supported Linux* build environment is the following:

  • Ubuntu* 18.04 LTS 64-bit or CentOS* 7.6 64-bit
  • GCC* 7.5.0 (for Ubuntu* 18.04) or GCC* 4.8.5 (for CentOS* 7.6)
  • CMake* version 3.10 or higher.

To build the demo applications for Linux, go to the directory with the build_demos.sh script and run it:

build_demos.sh

You can also build the demo applications manually:

  1. Navigate to a directory that you have write access to and create a demos build directory. This example uses a directory named build:
mkdir build
  1. Go to the created directory:
cd build
  1. Run CMake to generate the Make files for release or debug configuration:
  • For release configuration:
cmake -DCMAKE_BUILD_TYPE=Release <open_model_zoo>/demos
  • For debug configuration:
cmake -DCMAKE_BUILD_TYPE=Debug <open_model_zoo>/demos
  1. Run cmake --build tool to build the demos:
cmake --build .

For the release configuration, the demo application binaries are in <path_to_build_directory>/intel64/Release/; for the debug configuration — in <path_to_build_directory>/intel64/Debug/.

Build the Demos Applications on Microsoft Windows* OS

The recommended Windows* build environment is the following:

  • Microsoft Windows* 10
  • Microsoft Visual Studio* 2017, or 2019
  • CMake* version 3.10 or higher

NOTE: If you want to use Microsoft Visual Studio 2019, you are required to install CMake 3.14.

To build the demo applications for Windows, go to the directory with the build_demos_msvc.bat batch file and run it:

build_demos_msvc.bat

By default, the script automatically detects the highest Microsoft Visual Studio version installed on the machine and uses it to create and build a solution for a demo code. Optionally, you can also specify the preferred Microsoft Visual Studio version to be used by the script. Supported versions are: VS2017, VS2019. For example, to build the demos using the Microsoft Visual Studio 2017, use the following command:

build_demos_msvc.bat VS2017

The demo applications binaries are in the C:\Users\<username>\Documents\Intel\OpenVINO\omz_demos_build\intel64\Release directory.

You can also build a generated solution by yourself, for example, if you want to build binaries in Debug configuration. Run the appropriate version of the Microsoft Visual Studio and open the generated solution file from the C:\Users\<username>\Documents\Intel\OpenVINO\omz_demos_build\Demos.sln directory.

You can also build the demo applications using cmake --build tool:

  1. Navigate to a directory that you have write access to and create a demos build directory. This example uses a directory named build:
md build
  1. Go to the created directory:
cd build
  1. Run CMake to generate project files:
cmake -A x64 <open_model_zoo>/demos
  1. Run cmake --build tool to build the demos:
  • For release configuration
cmake --build . --config Release
  • For debug configuration:
cmake --build . --config Debug

Python* model API installation

Python Model API with model wrappers and pipelines can be installed as a part of OpenVINO™ toolkit or from source. Installation from source is as follows:

  1. Install Python (version 3.6 or higher), setuptools:

  2. Build the wheel with the following command:

python <omz_dir>/demos/common/python/setup.py bdist_wheel

The built wheel should appear in the dist folder; Name example: openmodelzoo_modelapi-0.0.0-py3-none-any.whl

  1. Install the package in the clean environment with --force-reinstall key:
python -m pip install openmodelzoo_modelapi-0.0.0-py3-none-any.whl --force-reinstall

Alternatively, instead of building the wheel you can use the following command inside <omz_dir>/demos/common/python/ directory to build and install the package:

python -m pip install .

When the model API package is installed, you can import it as follows:

python -c "from openvino.model_zoo import model_api"

NOTE: On Linux and macOS, you may need to type python3 instead of python. You may also need to install pip. For example, on Ubuntu execute the following command to get pip installed: sudo apt install python3-pip.

Build the Native Python* Extension Modules

Some of the Python demo applications require native Python extension modules to be built before they can be run. This requires you to have Python development files (headers and import libraries) installed. To build these modules, follow the instructions for building the demo applications above, but add -DENABLE_PYTHON=ON to either the cmake or the build_demos* command, depending on which you use. For example:

cmake -DCMAKE_BUILD_TYPE=Release -DENABLE_PYTHON=ON <open_model_zoo>/demos

Once the modules are built, add the demo build folder to the PYTHONPATH environment variable.

Build Specific Demos

To build specific demos, follow the instructions for building the demo applications above, but add --target <demo1> <demo2> ... to the cmake --build command or --target="<demo1> <demo2> ..." to the build_demos* command. Note, cmake --build tool supports multiple targets starting with version 3.15, with lower versions you can specify only one target.

For Linux*:

cmake -DCMAKE_BUILD_TYPE=Release <open_model_zoo>/demos
cmake --build . --target classification_demo segmentation_demo

or

build_demos.sh --target="classification_demo segmentation_demo"

For Microsoft Windows* OS:

cmake -A x64 <open_model_zoo>/demos
cmake --build . --config Release --target classification_demo segmentation_demo

or

build_demos_msvc.bat --target="classification_demo segmentation_demo"

Get Ready for Running the Demo Applications

Get Ready for Running the Demo Applications on Linux*

Before running compiled binary files, make sure your application can find the Inference Engine and OpenCV libraries. If you use a proprietary distribution to build demos, run the setupvars script to set all necessary environment variables:

source <INSTALL_DIR>/bin/setupvars.sh

If you use your own Inference Engine and OpenCV binaries to build the demos please make sure you have added them to the LD_LIBRARY_PATH environment variable.

(Optional): The OpenVINO environment variables are removed when you close the shell. As an option, you can permanently set the environment variables as follows:

  1. Open the .bashrc file in <user_home_directory>:
vi <user_home_directory>/.bashrc
  1. Add this line to the end of the file:
source <INSTALL_DIR>/bin/setupvars.sh
  1. Save and close the file: press the Esc key, type :wq and press the Enter key.
  2. To test your change, open a new terminal. You will see [setupvars.sh] OpenVINO environment initialized.

To run Python demo applications that require native Python extension modules, you must additionally set up the PYTHONPATH environment variable as follows, where <bin_dir> is the directory with the built demo applications:

export PYTHONPATH="$PYTHONPATH:<bin_dir>/lib"

You are ready to run the demo applications. To learn about how to run a particular demo, read the demo documentation by clicking the demo name in the demo list above.

Get Ready for Running the Demo Applications on Windows*

Before running compiled binary files, make sure your application can find the Inference Engine and OpenCV libraries. Optionally download OpenCV community FFmpeg plugin. There is a downloader script in the OpenVINO package: <INSTALL_DIR>\opencv\ffmpeg-download.ps1. If you use a proprietary distribution to build demos, run the setupvars script to set all necessary environment variables:

<INSTALL_DIR>\bin\setupvars.bat

If you use your own Inference Engine and OpenCV binaries to build the demos please make sure you have added to the PATH environment variable.

To run Python demo applications that require native Python extension modules, you must additionally set up the PYTHONPATH environment variable as follows, where <bin_dir> is the directory with the built demo applications:

set PYTHONPATH=%PYTHONPATH%;<bin_dir>

To debug or run the demos on Windows in Microsoft Visual Studio, make sure you have properly configured Debugging environment settings for the Debug and Release configurations. Set correct paths to the OpenCV libraries, and debug and release versions of the Inference Engine libraries. For example, for the Debug configuration, go to the project's Configuration Properties to the Debugging category and set the PATH variable in the Environment field to the following:

PATH=<INSTALL_DIR>\deployment_tools\inference_engine\bin\intel64\Debug;<INSTALL_DIR>\opencv\bin;%PATH%

where <INSTALL_DIR> is the directory in which the OpenVINO toolkit is installed.

You are ready to run the demo applications. To learn about how to run a particular demo, read the demo documentation by clicking the demo name in the demos list above.

See Also

* Other names and brands may be claimed as the property of others.