2c6078e96c
* [LPT] Documentation * 1) ToC was removed 2) SVG => PNG temporary conversion * [LPT] Refactoring + developer guide * [LPT] attribute doxygen documentation was added * [LPT] Developer Guide to Reference API links were added * [LPT] comments fixes * [LPT] Reference API to Developer Guide links were added * [LPT] titles were changed * [LPT] comments fixes #2 * [LPT] root document was moved to Plugin DG * [LPT] Documentation: image link quick fix * [LPT] Docummentation: PrecisionsAttribute description quick fix * fix comments from Karol * fixes * movement * directive was added * movement #2 * LPT reference in Executable Network rollback * snippets were updated ini accordance with new API
107 lines
4.7 KiB
Markdown
107 lines
4.7 KiB
Markdown
# Documentation {#documentation}
|
|
|
|
@sphinxdirective
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Converting and Preparing Models
|
|
:hidden:
|
|
|
|
openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide
|
|
openvino_docs_HOWTO_Custom_Layers_Guide
|
|
omz_tools_downloader
|
|
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Deploying Inference
|
|
:hidden:
|
|
|
|
openvino_docs_IE_DG_Deep_Learning_Inference_Engine_DevGuide
|
|
openvino_docs_nGraph_DG_DevGuide
|
|
openvino_docs_install_guides_deployment_manager_tool
|
|
openvino_inference_engine_tools_compile_tool_README
|
|
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Tuning for Performance
|
|
:hidden:
|
|
|
|
openvino_docs_performance_benchmarks
|
|
openvino_docs_optimization_guide_dldt_optimization_guide
|
|
openvino_docs_MO_DG_Getting_Performance_Numbers
|
|
pot_README
|
|
openvino_docs_tuning_utilities
|
|
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Graphical Web Interface for OpenVINO™ toolkit
|
|
:hidden:
|
|
|
|
workbench_docs_Workbench_DG_Introduction
|
|
workbench_docs_Workbench_DG_Install
|
|
workbench_docs_Workbench_DG_Work_with_Models_and_Sample_Datasets
|
|
workbench_docs_Workbench_DG_User_Guide
|
|
workbench_docs_security_Workbench
|
|
workbench_docs_Workbench_DG_Troubleshooting
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:hidden:
|
|
:caption: Media Processing
|
|
|
|
DL Streamer API Reference <https://openvinotoolkit.github.io/dlstreamer_gst/>
|
|
gst_samples_README
|
|
openvino_docs_gapi_gapi_intro
|
|
OpenVX Developer Guide <https://software.intel.com/en-us/openvino-ovx-guide>
|
|
OpenVX API Reference <https://khronos.org/openvx>
|
|
OpenCV* Developer Guide <https://docs.opencv.org/master/>
|
|
OpenCL™ Developer Guide <https://software.intel.com/en-us/openclsdk-devguide>
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Add-Ons
|
|
:hidden:
|
|
|
|
openvino_docs_ovms
|
|
ovsa_get_started
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Developing Inference Engine Plugins
|
|
:hidden:
|
|
|
|
Inference Engine Plugin Developer Guide <openvino_docs_ie_plugin_dg_overview>
|
|
groupie_dev_api
|
|
Plugin Transformation Pipeline <openvino_docs_IE_DG_plugin_transformation_pipeline>
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:hidden:
|
|
:caption: Use OpenVINO™ Toolkit Securely
|
|
|
|
openvino_docs_security_guide_introduction
|
|
openvino_docs_security_guide_workbench
|
|
openvino_docs_IE_DG_protecting_model_guide
|
|
ovsa_get_started
|
|
|
|
@endsphinxdirective
|
|
|
|
This section provides reference documents that guide you through developing your own deep learning applications with the OpenVINO™ toolkit. These documents will most helpful if you have first gone through the [Get Started](get_started.md) guide.
|
|
|
|
## Converting and Preparing Models
|
|
With the [Model Downloader](@ref omz_tools_downloader) and [Model Optimizer](MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md) guides, you will learn to download pre-trained models and convert them for use with the OpenVINO™ toolkit. You can provide your own model or choose a public or Intel model from a broad selection provided in the [Open Model Zoo](model_zoo.md).
|
|
|
|
## Deploying Inference
|
|
The [Inference Engine Developer Guide](IE_DG/Deep_Learning_Inference_Engine_DevGuide.md) explains the process of creating your own application that runs inference with the OpenVINO™ toolkit. The [API Reference](./api_references.html) defines the Inference Engine API for Python, C++, and C and the nGraph API for Python and C++. The Inference Engine API is what you'll use to create an OpenVINO™ application, while the nGraph API is available for using enhanced operations sets and other features. After writing your application, you can use the [Deployment Manager](install_guides/deployment-manager-tool.md) for deploying to target devices.
|
|
|
|
## Tuning for Performance
|
|
The toolkit provides a [Performance Optimization Guide](optimization_guide/dldt_optimization_guide.md) and utilities for squeezing the best performance out of your application, including [Accuracy Checker](@ref omz_tools_accuracy_checker), [Post-Training Optimization Tool](@ref pot_README), and other tools for measuring accuracy, benchmarking performance, and tuning your application.
|
|
|
|
## 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. |