78 lines
4.2 KiB
Markdown
78 lines
4.2 KiB
Markdown
# Get Started {#get_started}
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@sphinxdirective
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.. toctree::
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:maxdepth: 1
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:hidden:
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:caption: Install & Config
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Installing OpenVINO <openvino_docs_install_guides_overview>
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Additional Configurations <openvino_docs_install_guides_configurations_header>
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Uninstalling <openvino_docs_install_guides_uninstalling_openvino>
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Troubleshooting <openvino_docs_get_started_guide_troubleshooting>
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.. toctree::
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:maxdepth: 1
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:hidden:
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:caption: Get Started Guides
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Interactive Tutorials (Python) <tutorials>
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Samples <openvino_docs_OV_UG_Samples_Overview>
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@endsphinxdirective
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@sphinxdirective
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.. raw:: html
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<link rel="stylesheet" type="text/css" href="_static/css/getstarted_style.css">
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<p id="GSG_introtext">This guide introduces the installation, configuration, and get started guides of Intel® Distribution of OpenVINO™ toolkit. Check the following steps from left to right:<br />
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<a href="openvino_docs_install_guides_overview.html" >Install Intel® Distribution<br/>of OpenVINO™ toolkit</a>
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<a href="openvino_docs_install_guides_configurations_header.html" >Perform <br/>Additional Configurations</a>
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<a href="#get-started-tutorials" >Try <br/>Get Started Materials</a>
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</p>
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<p>If you prefer using a graphical interface, you can <a href="workbench_docs_Workbench_DG_Start_DL_Workbench_in_DevCloud.html" >Run Deep Learning Workbench in the Intel® DevCloud for the Edge</a>. Deep Learning Workbench (DL Workbench) is the web version of OpenVINO developed based on Intel® Distribution of OpenVINO™ toolkit with a similar but slightly different function set.</li>
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</p>
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<div style="clear:both;"> </div>
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<!--
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<p>If you are using Intel® Processor Graphics, Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, Intel® Neural Compute Stick 2 or Intel® Gaussian & Neural Accelerator (GNA), please check the additional configurations for them accordingly: <a href="openvino_docs_install_guides_configurations_for_intel_gpu.html" >Configurations for GPU</a>, <a href="openvino_docs_install_guides_installing_openvino_ivad_vpu.html" >Configurations for VPU</a>, <a href="openvino_docs_install_guides_configurations_for_ncs2.html" >Configurations for NCS2</a> or <a href="openvino_docs_install_guides_configurations_for_intel_gna.html" >Configurations for GNA</a>.
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</p>
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-->
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<h3><a name="get-started-tutorials">Tutorials, Samples, and Demo Applications</a></h3>
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<p>After all the installation and configuration steps are done, you are ready to run your first inference and learn the workflow. Here is a set of hands-on demonstrations of various complexity levels to guide you through the process. You can run Jupyter notebooks, code samples, or demo applications.</p>
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<div id="GSG_nextstepchoice">
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<a href="tutorials.html" >
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<h4>Interactive Tutorials - Jupyter Notebooks (Python) </h4>
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<p>Learn from a choice of interactive Python tutorials targeting typical OpenVINO use cases.</p>
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</a>
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<a href="openvino_docs_OV_UG_Samples_Overview.html" >
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<h4>OpenVINO Samples </h4>
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<p>See ready-made applications explaining OpenVINO features and various use-cases. </p>
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</a>
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<a href="openvino_inference_engine_ie_bridges_python_sample_speech_sample_README.html" >
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<h4>Reference Implementation For Speech Recognition Apps (Python)</h4>
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<p>Use a speech recognition demo and Kaldi model conversion tool as reference. </p>
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</a>
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<a href="openvino_inference_engine_samples_speech_sample_README.html" >
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<h4>Reference Implementation For Speech Recognition Apps (C++)</h4>
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<p>Use a speech recognition demo and Kaldi model conversion tool as reference. </p>
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</a>
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<a href="omz_demos.html" >
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<h4>Open Model Zoo Demo Applications</h4>
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<p>See Open Model Zoo demo applications to use robust application templates for implementing specific deep learning scenarios. </p>
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</a>
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<a href="http://devcloud.intel.com/edge/" >
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<h4>Intel® DevCloud </h4>
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<p>Develop, test, and run your OpenVINO solution for free on a cluster of the latest Intel® hardware. </p>
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</a>
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</div>
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<div style="clear:both;"> </div>
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@endsphinxdirective |