diff --git a/docs/documentation.md b/docs/documentation.md index 16c6886effd..5481d5f08bb 100644 --- a/docs/documentation.md +++ b/docs/documentation.md @@ -91,7 +91,7 @@ Intel® Deep Learning Streamer openvino_docs_gapi_gapi_intro - OpenCV* Developer Guide + OpenCV Developer Guide OpenCL™ Developer Guide OneVPL Developer Guide diff --git a/docs/gapi/face_beautification.md b/docs/gapi/face_beautification.md index 7026d9b98a0..1db673db72c 100644 --- a/docs/gapi/face_beautification.md +++ b/docs/gapi/face_beautification.md @@ -10,7 +10,7 @@ In this tutorial you will learn: ## Prerequisites This sample requires: -* PC with GNU/Linux* or Microsoft Windows* (Apple macOS* is supported but was not tested) +* PC with GNU/Linux or Microsoft Windows (Apple macOS is supported but was not tested) * OpenCV 4.2 or higher built with [Intel® Distribution of OpenVINO™ Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) (building with [Intel® TBB](https://www.threadingbuildingblocks.org/intel-tbb-tutorial) is a plus) * The following pre-trained models from the [Open Model Zoo](@ref omz_models_group_intel) * [face-detection-adas-0001](@ref omz_models_model_face_detection_adas_0001) @@ -23,8 +23,6 @@ We will implement a simple face beautification algorithm using a combination of ![Face Beautification Algorithm](../img/gapi_face_beautification_algorithm.png) -Briefly the algorithm is described as follows: - Briefly the algorithm is described as follows: - Input image \f$I\f$ is passed to unsharp mask and bilateral filters (\f$U\f$ and \f$L\f$ respectively); diff --git a/docs/gapi/gapi_face_analytics_pipeline.md b/docs/gapi/gapi_face_analytics_pipeline.md index be07aaae573..861aec24ebc 100644 --- a/docs/gapi/gapi_face_analytics_pipeline.md +++ b/docs/gapi/gapi_face_analytics_pipeline.md @@ -9,8 +9,8 @@ In this tutorial you will learn: ## Prerequisites This sample requires: -* PC with GNU/Linux* or Microsoft Windows* (Apple macOS* is supported but was not tested) -* OpenCV 4.2 or higher built with [Intel® Distribution of OpenVINO™ Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) (building with [Intel® TBB](https://www.threadingbuildingblocks.org/intel-tbb-tutorial) +* PC with GNU/Linux or Microsoft Windows (Apple macOS is supported but was not tested) +* OpenCV 4.2 or higher built with [Intel® Distribution of OpenVINO™ Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) (building with [Intel® TBB](https://www.threadingbuildingblocks.org/intel-tbb-tutorial) is a plus) * The following pre-trained models from the [Open Model Zoo](@ref omz_models_group_intel): * [face-detection-adas-0001](@ref omz_models_model_face_detection_adas_0001) * [age-gender-recognition-retail-0013](@ref omz_models_model_age_gender_recognition_retail_0013)