Merge pull request #22552 from alvoron:ocv_ov_instruction

OpenCV for OpenVINO documentation

doc/tutorials/dnn/dnn_android/dnn_android.markdown

@@ -2,7 +2,7 @@
 
 @tableofcontents
 
-@prev_tutorial{tutorial_dnn_halide_scheduling}
+@prev_tutorial{tutorial_dnn_openvino}
 @next_tutorial{tutorial_dnn_yolo}
 
 |    |    |

doc/tutorials/dnn/dnn_halide_scheduling/dnn_halide_scheduling.markdown

@@ -3,7 +3,7 @@
 @tableofcontents
 
 @prev_tutorial{tutorial_dnn_halide}
-@next_tutorial{tutorial_dnn_android}
+@next_tutorial{tutorial_dnn_openvino}
 
 |    |    |
 | -: | :- |

doc/tutorials/dnn/dnn_openvino/dnn_openvino.markdown

@@ -0,0 +1,28 @@
+OpenCV usage with OpenVINO {#tutorial_dnn_openvino}
+=====================
+
+@prev_tutorial{tutorial_dnn_halide_scheduling}
+@next_tutorial{tutorial_dnn_android}
+
+|    |    |
+| -: | :- |
+| Original author | Aleksandr Voron |
+| Compatibility | OpenCV == 4.x |
+
+This tutorial provides OpenCV installation guidelines how to use OpenCV with OpenVINO.
+
+Since 2021.1.1 release OpenVINO does not provide pre-built OpenCV.
+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.
+However, if you are using Open Model Zoo demos or OpenVINO runtime as OpenCV DNN backend you need to get the OpenCV build.
+
+There are 2 approaches how to get OpenCV:
+
+- Install pre-built OpenCV from another sources: system repositories, pip, conda, homebrew. Generic pre-built OpenCV package may have several limitations:
+    - OpenCV version may be out-of-date
+    - OpenCV may not contain G-API module with enabled OpenVINO support (e.g. some OMZ demos use G-API functionality)
+    - OpenCV may not be optimized for modern hardware (default builds need to cover wide range of hardware)
+    - OpenCV may not support Intel TBB, Intel Media SDK
+    - OpenCV DNN module may not use OpenVINO as an inference backend
+- Build OpenCV from source code against specific version of OpenVINO. This approach solves the limitations mentioned above.
+
+The instruction how to follow both approaches is provided in [OpenCV wiki](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).

doc/tutorials/dnn/table_of_content_dnn.markdown

@@ -4,6 +4,7 @@ Deep Neural Networks (dnn module) {#tutorial_table_of_content_dnn}
 -   @subpage tutorial_dnn_googlenet
 -   @subpage tutorial_dnn_halide
 -   @subpage tutorial_dnn_halide_scheduling
+-   @subpage tutorial_dnn_openvino
 -   @subpage tutorial_dnn_android
 -   @subpage tutorial_dnn_yolo
 -   @subpage tutorial_dnn_javascript

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -65,12 +65,12 @@ CV__DNN_INLINE_NS_BEGIN
     enum Backend
     {
         //! DNN_BACKEND_DEFAULT equals to DNN_BACKEND_INFERENCE_ENGINE if
-        //! OpenCV is built with Intel's Inference Engine library or
+        //! OpenCV is built with Intel OpenVINO or
         //! DNN_BACKEND_OPENCV otherwise.
         DNN_BACKEND_DEFAULT = 0,
         DNN_BACKEND_HALIDE,
-        DNN_BACKEND_INFERENCE_ENGINE,            //!< Intel's Inference Engine computational backend
-                                                 //!< @sa setInferenceEngineBackendType
+        DNN_BACKEND_INFERENCE_ENGINE,            //!< Intel OpenVINO computational backend
+                                                 //!< @note Tutorial how to build OpenCV with OpenVINO: @ref tutorial_dnn_openvino
         DNN_BACKEND_OPENCV,
         DNN_BACKEND_VKCOM,
         DNN_BACKEND_CUDA,