To get started with OpenVINO, the first thing to do is to actually install it. You can get an overview of what installation options we provide and start from there.
If you already have enough information, you can also choose the installation type that best suits your needs from one of the options below:
OpenVINO Runtime Install OpenVINO
Development Tools Build
If you are using Intel® Processor Graphics, Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, Intel® Neural Compute Stick 2 or Intel® Gaussian & Neural Accelerator (GNA), please check the additional configurations for them accordingly: Configurations for GPU, Configurations for VPU, Configurations for NCS2 or Configurations for GNA.
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:
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.
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.