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added opencv for openvino tutorial
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@tableofcontents
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@tableofcontents
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@prev_tutorial{tutorial_dnn_halide_scheduling}
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@prev_tutorial{tutorial_dnn_openvino}
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@next_tutorial{tutorial_dnn_yolo}
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@next_tutorial{tutorial_dnn_yolo}
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@tableofcontents
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@tableofcontents
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@prev_tutorial{tutorial_dnn_halide}
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@prev_tutorial{tutorial_dnn_halide}
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@next_tutorial{tutorial_dnn_android}
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@next_tutorial{tutorial_dnn_openvino}
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28
doc/tutorials/dnn/dnn_openvino/dnn_openvino.markdown
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28
doc/tutorials/dnn/dnn_openvino/dnn_openvino.markdown
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OpenCV usage with OpenVINO {#tutorial_dnn_openvino}
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=====================
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@prev_tutorial{tutorial_dnn_halide_scheduling}
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@next_tutorial{tutorial_dnn_android}
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| Original author | Aleksandr Voron |
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| Compatibility | OpenCV == 4.x |
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This tutorial provides OpenCV installation guidelines how to use OpenCV with OpenVINO.
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Since 2021.1.1 release OpenVINO does not provide pre-built OpenCV.
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The change does not affect you if you are using OpenVINO runtime directly or OpenVINO samples: it does not have a strong dependency to OpenCV.
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However, if you are using Open Model Zoo demos or OpenVINO runtime as OpenCV DNN backend you need to get the OpenCV build.
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There are 2 approaches how to get OpenCV:
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- Install pre-built OpenCV from another sources: system repositories, pip, conda, homebrew. Generic pre-built OpenCV package may have several limitations:
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- OpenCV version may be out-of-date
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- OpenCV may not contain G-API module with enabled OpenVINO support (e.g. some OMZ demos use G-API functionality)
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- OpenCV may not be optimized for modern hardware (default builds need to cover wide range of hardware)
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- OpenCV may not support Intel TBB, Intel Media SDK
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- OpenCV DNN module may not use OpenVINO as an inference backend
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- Build OpenCV from source code against specific version of OpenVINO. This approach solves the limitations mentioned above.
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The instruction how to follow both approaches is provided in [OpenCV wiki](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
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@ -4,6 +4,7 @@ Deep Neural Networks (dnn module) {#tutorial_table_of_content_dnn}
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- @subpage tutorial_dnn_googlenet
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- @subpage tutorial_dnn_googlenet
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- @subpage tutorial_dnn_halide
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- @subpage tutorial_dnn_halide
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- @subpage tutorial_dnn_halide_scheduling
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- @subpage tutorial_dnn_halide_scheduling
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- @subpage tutorial_dnn_openvino
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- @subpage tutorial_dnn_android
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- @subpage tutorial_dnn_android
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- @subpage tutorial_dnn_yolo
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- @subpage tutorial_dnn_yolo
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- @subpage tutorial_dnn_javascript
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- @subpage tutorial_dnn_javascript
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@ -65,12 +65,12 @@ CV__DNN_INLINE_NS_BEGIN
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enum Backend
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enum Backend
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{
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{
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//! DNN_BACKEND_DEFAULT equals to DNN_BACKEND_INFERENCE_ENGINE if
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//! DNN_BACKEND_DEFAULT equals to DNN_BACKEND_INFERENCE_ENGINE if
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//! OpenCV is built with Intel's Inference Engine library or
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//! OpenCV is built with Intel OpenVINO or
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//! DNN_BACKEND_OPENCV otherwise.
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//! DNN_BACKEND_OPENCV otherwise.
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DNN_BACKEND_DEFAULT = 0,
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DNN_BACKEND_DEFAULT = 0,
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DNN_BACKEND_HALIDE,
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DNN_BACKEND_HALIDE,
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DNN_BACKEND_INFERENCE_ENGINE, //!< Intel's Inference Engine computational backend
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DNN_BACKEND_INFERENCE_ENGINE, //!< Intel OpenVINO computational backend
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//!< @sa setInferenceEngineBackendType
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//!< @note Tutorial how to build OpenCV with OpenVINO: @ref tutorial_dnn_openvino
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DNN_BACKEND_OPENCV,
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DNN_BACKEND_OPENCV,
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DNN_BACKEND_VKCOM,
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DNN_BACKEND_VKCOM,
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DNN_BACKEND_CUDA,
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DNN_BACKEND_CUDA,
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