Install Intel® OpenVINO™ toolkit

register & download

reference website：
https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit/choose-download.html

reference website：
https://docs.openvinotoolkit.org/latest/openvino_docs_install_guides_installing_openvino_linux.html

tar -xvzf l_openvino_toolkit_p_<version>.tgz
sudo ./install.sh
cd /opt/intel/openvino_2020.3.341/install_dependencies
sudo -E ./install_openvino_dependencies.sh
source /opt/intel/openvino_2020.3.341/bin/setupvars.sh

download model

cd /opt/intel/openvino_2020.3.341/deployment_tools/tools/model_downloader/
python3 info_dumper.py --print_all
sudo python3 ./downloader.py --name squeezenet1.1 --output_dir ~/models

Runs the Model Optimizer to convert the model to the IR

Note that install_prerequisites scripts

aaeon@aaeon:/opt/intel/openvino_2020.3.341/deployment_tools/model_optimizer/install_prerequisites$ sudo ./install_prerequisites_caffe.sh 

cd /opt/intel/openvino_2020.3.341/deployment_tools/model_optimizer
python3 ./mo.py --input_model ~/models/public/squeezenet1.1/squeezenet1.1.caffemodel --data_type FP32  --output_dir .

Builds the Image Classification Sample Async application.

cd /opt/intel/openvino_2020.3.341/deployment_tools/inference_engine/samples/cpp/

./build_samples.sh 

cd ~/inference_engine_cpp_samples_build/intel64/Release

run inference with Accelerator

• Runs the compiled sample with the car.png image located in the demo directory

[Note]
There are lots of demo scripts here

/opt/intel/openvino_2020.3.341/deployment_tools/demo