To get started with OpenVINO, the first thing to do is to actually install it. If you haven't done it yet, choose the installation type that best suits your needs and follow the instructions:
Package Install from
images or repositories Build
With OpenVINO installed, you are ready to run your first inference and learn the workflow.
Here is a set of hands-on demonstrations of various complexity levels to guide you through the process: from performing sample inference with just one command, to running code samples, demo application or Jupyter notebooks. If you prefer working with GUI, you can also get started with the DL Workbench application. This way you can choose the right level for you.
Choose how you want to progress:
Execute just one command and watch all the steps happening before your eyes.
Follow the step-by-step instructions to execute simple tasks with OpenVINO.
Learn from a choice of interactive Python tutorials targeting typical OpenVINO use cases.
Use a web-based version of OpenVINO with a Graphical User Interface. Installing a DL Workbench container is required.
Inference Engine samples
See ready-made applications explaining OpenVINO features and various use-cases.
Reference Implementation For Speech Recognition Apps
Use a speech recognition demo and Kaldi* model conversion tool as reference.
Develop, test, and run your OpenVINO solution for free on a cluster of the latest Intel® hardware.