Guest post by Aleksandr Voron
To keep OpenVINO™ Toolkit focused on optimizing and deploying inference, we no longer include OpenCV and DL Streamer in our distribution packages. But not to worry! Both OpenCV and DL Streamer continue to work with OpenVINO and in this blog post we will explain how.
In the 2022.1 release of OpenVINO™, OpenCV became an optional dependency that could be installed using a script. This script made it easy to install both OpenVINO and OpenCV together. Starting in the 2022.1.1 release we removed the OpenCV download script and no longer publish the pre-built OpenCV version for OpenVINO.
If this change impacts you, please read the instructions below that explain how to continue using OpenCV with OpenVINO. The change is unlikely to affect you if you just use OpenVINO Runtime directly or run OpenVINO samples – neither have a strong dependency on OpenCV. However, if you use Open Model Zoo demos or OpenVINO Runtime via the OpenCV DNN backend, then you should follow the instructions below to get the OpenCV build.
There are two ways to get OpenCV:
- Install pre-built OpenCV from public sources (system repositories, pip, conda, homebrew). This approach has several limitations:
- OpenCV version could be out-of-date
- It does not contain the G-API module
- It does not take advantage of all available CPU instructions since it is built to cover a wide range of hardware
- Intel TBB or Intel Media SDK are not supported
- The OpenCV DNN module cannot use OpenVINO as computational backend
- Build OpenCV from source code against a specific version of OpenVINO. This approach addresses the limitations highlighted above.
Instructions for both approaches are provided in the OpenCV documentation and wiki. To download the latest version of OpenVINO, please visit .
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