From 25bd2c8aee7f8525dcb8d595d1606e42add968de Mon Sep 17 00:00:00 2001 From: Andrey Zaytsev Date: Mon, 14 Feb 2022 15:43:52 +0300 Subject: [PATCH] Feature/azaytsev/docs dlsteamer revision (#10155) * Added info on DockerHub CI Framework * Feature/azaytsev/change layout (#3295) * Changes according to feedback comments * Replaced @ref's with html links * Fixed links, added a title page for installing from repos and images, fixed formatting issues * Added links * minor fix * Added DL Streamer to the list of components installed by default * Link fixes * Link fixes * ovms doc fix (#2988) * added OpenVINO Model Server * ovms doc fixes Co-authored-by: Trawinski, Dariusz * Updated openvino_docs.xml * Updated the link to software license agreements * Revert "Updated the link to software license agreements" This reverts commit 706dac500e764bd7534f7005ac6197f827d68cb5. * Revised dlstreamer documentation * Minor edits * Fixed link * Fix * Edits after review * Shorten DL Streamer name in the TOC * Update documentation.md Co-authored-by: Trawinski, Dariusz --- docs/dlstreamer.md | 18 ++++++++++++++++++ docs/documentation.md | 16 +++++++++++----- 2 files changed, 29 insertions(+), 5 deletions(-) create mode 100644 docs/dlstreamer.md diff --git a/docs/dlstreamer.md b/docs/dlstreamer.md new file mode 100644 index 00000000000..eb21196221f --- /dev/null +++ b/docs/dlstreamer.md @@ -0,0 +1,18 @@ +# Intel® Deep Learning Streamer (Intel® DL Streamer) {#openvino_docs_dlstreamer} + +Intel® DL Streamer is a streaming media analytics framework, based on GStreamer* multimedia framework, for creating complex media analytics pipelines. + +Intel® DL Streamer makes Media analytics easy: + +* Write less code and get better performance +* Quickly develop, optimize, benchmark, and deploy video & audio analytics pipelines in the Cloud and at the Edge +* Analyze video and audio streams, create actionable results, capture results, and send them to the cloud +* Leverage the efficiency and computational power of Intel hardware platforms + +Go to [Intel® DL Streamer documentation website](https://dlstreamer.github.io) for information on how to download, install, and use. + +**Media analytics** is the analysis of audio & video streams to detect, classify, track, identify and count objects, events and people. The analyzed results can be used to take actions, coordinate events, identify patterns and gain insights across multiple domains. + +**Media analytics pipelines** transform media streams into insights through audio / video processing, inference, and analytics operations across multiple IP blocks. + +\* Other names and brands may be claimed as the property of others. \ No newline at end of file diff --git a/docs/documentation.md b/docs/documentation.md index ae477d00ebb..17f8991dd2d 100644 --- a/docs/documentation.md +++ b/docs/documentation.md @@ -49,10 +49,9 @@ .. toctree:: :maxdepth: 1 :hidden: - :caption: Media Processing + :caption: Media Processing and Computer Vision Libraries - DL Streamer API Reference - gst_samples_README + Intel® Deep Learning Streamer openvino_docs_gapi_gapi_intro OpenVX Developer Guide OpenVX API Reference @@ -102,5 +101,12 @@ The toolkit provides a [Performance Optimization Guide](optimization_guide/dldt_ ## Graphical Web Interface for OpenVINO™ Toolkit You can choose to use the [OpenVINO™ Deep Learning Workbench](@ref workbench_docs_Workbench_DG_Introduction), a web-based tool that guides you through the process of converting, measuring, optimizing, and deploying models. This tool also serves as a low-effort introduction to the toolkit and provides a variety of useful interactive charts for understanding performance. -## Media Processing -The OpenVINO™ toolkit comes with several sets of libraries and tools that add capability and flexibility to the toolkit. These include [DL Streamer](@ref gst_samples_README), a utility that eases creation of pipelines via command line or API, and optimized versions of OpenCV and OpenCL. +## Media Processing and Computer Vision Libraries + +The OpenVINO™ toolkit also works with the following media processing frameworks and libraries: + +* [Intel® Deep Learning Streamer (Intel® DL Streamer)](@ref openvino_docs_dlstreamer) — A streaming media analytics framework based on GStreamer, for creating complex media analytics pipelines optimized for Intel hardware platforms. Go to the Intel® DL Streamer [documentation](https://dlstreamer.github.io/) website to learn more. +* [Intel® oneAPI Video Processing Library (oneVPL)](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/api-based-programming/intel-oneapi-video-processing-library-onevpl.html) — A programming interface for video decoding, encoding, and processing to build portable media pipelines on CPUs, GPUs, and other accelerators. + +You can also add computer vision capabilities to your application using optimized versions of [OpenCV](https://opencv.org/) and [OpenVX](https://khronos.org/openvx). +