# OpenVINO™
Intel® Distribution of OpenVINO™ toolkit is an open-source toolkit for optimizing and deploying
AI inference. It can be used to develop applications and solutions based on deep learning tasks,
such as: emulation of human vision, automatic speech recognition, natural language processing,
recommendation systems, etc. It provides high-performance and rich deployment options, from
edge to cloud.
If you have chosen a model, you can integrate it with your application through OpenVINO™ and
deploy it on various devices. The OpenVINO™ Python package includes a set of libraries for easy
inference integration with your products.
## System Requirements
Before you start the installation, check the supported operating systems and required Python*
versions. The complete list of supported hardware is available on the
[System Requirements page](https://docs.openvino.ai/system_requirements).
**C++ libraries** are also required for the installation on Windows*. To install that, you can
[download the Visual Studio Redistributable file (.exe)](https://aka.ms/vs/17/release/vc_redist.x64.exe).
> **NOTE**: This package may work on other Linux and Windows versions but only the versions specified in system requirements are fully validated.
## Install OpenVINO™
### Step 1. Set Up Python Virtual Environment
Use a virtual environment to avoid dependency conflicts. To create a virtual environment, use
the following commands:
On Windows:
```sh
python -m venv openvino_env
```
On Linux and macOS:
```sh
python3 -m venv openvino_env
```
> **NOTE**: On Linux and macOS, you may need to [install pip](https://pip.pypa.io/en/stable/installation/).
### Step 2. Activate the Virtual Environment
On Windows:
```sh
openvino_env\Scripts\activate
```
On Linux and macOS:
```sh
source openvino_env/bin/activate
```
### Step 3. Set Up and Update PIP to the Highest Version
Run the command below:
```sh
python -m pip install --upgrade pip
```
### Step 4. Install the Package
Run the command below: <br>
```sh
pip install openvino
```
### Step 5. Verify that the Package Is Installed
Run the command below:
```sh
python -c "from openvino import Core; print(Core().available_devices)"
```
If installation was successful, you will see the list of available devices.
## What's in the Package
<table>
<tr>
<th>Component</th>
<th>Content</th>
<th>Description</th>
</tr>
<tr>
<td><a href="https://docs.openvino.ai/2024/openvino-workflow/running-inference.html">OpenVINO Runtime</a></td>
<td>`openvino package`</td>
<td>OpenVINO Runtime is a set of C++ libraries with C and Python bindings providing a common
API to deliver inference solutions on the platform of your choice. Use the OpenVINO
Runtime API to read PyTorch, TensorFlow, TensorFlow Lite, ONNX, and PaddlePaddle models
and execute them on preferred devices. OpenVINO Runtime uses a plugin architecture and
includes the following plugins:
<a href="https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/cpu-device.html">CPU</a>,
<a href="https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device.html">GPU</a>,
<a href="https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching.html">Auto Batch</a>,
<a href="https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection.html">Auto</a>,
<a href="https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution.html">Hetero</a>,
</td>
</tr>
<tr>
<td><a href="https://docs.openvino.ai/2024/openvino-workflow/model-preparation.html#convert-a-model-in-cli-ovc">OpenVINO Model Converter (OVC)</a></td>
<td>`ovc`</td>
<td>OpenVINO Model Converter converts models that were trained in popular frameworks to a
format usable by OpenVINO components. </br>Supported frameworks include ONNX, TensorFlow,
TensorFlow Lite, and PaddlePaddle.
</td>
</tr>
<tr>
<td><a href="https://docs.openvino.ai/2024/learn-openvino/openvino-samples/benchmark-tool.html">Benchmark Tool</a></td>
<td>`benchmark_app`</td>
<td>Benchmark Application** allows you to estimate deep learning inference performance on
supported devices for synchronous and asynchronous modes.
</td>
</table> |
## Troubleshooting
For general troubleshooting steps and issues, see
[Troubleshooting Guide for OpenVINO Installation](https://docs.openvino.ai/2024/get-started/troubleshooting-install-config.html).
The following sections also provide explanations to several error messages.
### Errors with Installing via PIP for Users in China
Users in China may encounter errors while downloading sources via PIP during OpenVINO™ installation.
To resolve the issues, try the following solution:
* Add the download source using the ``-i`` parameter with the Python ``pip`` command. For example:
``` sh
pip install openvino -i https://mirrors.aliyun.com/pypi/simple/
```
Use the ``--trusted-host`` parameter if the URL above is ``http`` instead of ``https``.
### ERROR:root:Could not find OpenVINO Python API.
On Windows, additional libraries may be necessary to run OpenVINO. To resolve this issue, install
the [C++ redistributable (.exe)](https://aka.ms/vs/17/release/vc_redist.x64.exe).
You can also view a full download list on the
[official support page](https://docs.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist).
### ImportError: libpython3.8.so.1.0: cannot open shared object file: No such file or directory
To resolve missing external dependency on Ubuntu*, execute the following command:
```sh
sudo apt-get install libpython3.8
```
## Additional Resources
- [Intel® Distribution of OpenVINO™ toolkit](https://software.intel.com/en-us/openvino-toolkit)
- [OpenVINO™ Documentation](https://docs.openvino.ai/)
- [OpenVINO™ Notebooks](https://github.com/openvinotoolkit/openvino_notebooks)
- [OpenVINO Installation Selector Tool](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/download.html)
Copyright © 2018-2024 Intel Corporation
> **LEGAL NOTICE**: Your use of this software and any required dependent software (the
“Software Package”) is subject to the terms and conditions of the
[Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0.html) for the Software Package,
which may also include notices, disclaimers, or license terms for third party or open source
software included in or with the Software Package, and your use indicates your acceptance of all
such terms. Please refer to the “third-party-programs.txt” or other similarly-named text file
included with the Software Package for additional details.
>Intel is committed to the respect of human rights and avoiding complicity in human rights abuses,
a policy reflected in the [Intel Global Human Rights Principles](https://www.intel.com/content/www/us/en/policy/policy-human-rights.html).
Accordingly, by accessing the Intel material on this platform you agree that you will not use the
material in a product or application that causes or contributes to a violation of an
internationally recognized human right.
Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its
subsidiaries. Other names and brands may be claimed as the property of others.
Raw data
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"description": "# OpenVINO\u2122\n\nIntel\u00ae Distribution of OpenVINO\u2122 toolkit is an open-source toolkit for optimizing and deploying\nAI inference. It can be used to develop applications and solutions based on deep learning tasks,\nsuch as: emulation of human vision, automatic speech recognition, natural language processing,\nrecommendation systems, etc. It provides high-performance and rich deployment options, from\nedge to cloud.\n\nIf you have chosen a model, you can integrate it with your application through OpenVINO\u2122 and\ndeploy it on various devices. The OpenVINO\u2122 Python package includes a set of libraries for easy\ninference integration with your products.\n\n## System Requirements\n\nBefore you start the installation, check the supported operating systems and required Python*\nversions. The complete list of supported hardware is available on the\n[System Requirements page](https://docs.openvino.ai/system_requirements).\n\n**C++ libraries** are also required for the installation on Windows*. To install that, you can\n[download the Visual Studio Redistributable file (.exe)](https://aka.ms/vs/17/release/vc_redist.x64.exe).\n\n> **NOTE**: This package may work on other Linux and Windows versions but only the versions specified in system requirements are fully validated.\n\n## Install OpenVINO\u2122\n\n### Step 1. Set Up Python Virtual Environment\n\nUse a virtual environment to avoid dependency conflicts. To create a virtual environment, use\nthe following commands:\n\nOn Windows:\n```sh\npython -m venv openvino_env\n```\n\nOn Linux and macOS:\n```sh\npython3 -m venv openvino_env\n```\n\n> **NOTE**: On Linux and macOS, you may need to [install pip](https://pip.pypa.io/en/stable/installation/).\n\n### Step 2. Activate the Virtual Environment\n\nOn Windows:\n```sh\nopenvino_env\\Scripts\\activate\n```\n\nOn Linux and macOS:\n```sh\nsource openvino_env/bin/activate\n```\n\n### Step 3. Set Up and Update PIP to the Highest Version\n\nRun the command below:\n```sh\npython -m pip install --upgrade pip\n```\n\n### Step 4. Install the Package\n\nRun the command below: <br>\n\n ```sh\n pip install openvino\n ```\n\n### Step 5. Verify that the Package Is Installed\n\nRun the command below:\n```sh\npython -c \"from openvino import Core; print(Core().available_devices)\"\n```\n\nIf installation was successful, you will see the list of available devices.\n\n## What's in the Package\n\n<table>\n <tr>\n <th>Component</th>\n <th>Content</th>\n <th>Description</th>\n </tr>\n <tr>\n <td><a href=\"https://docs.openvino.ai/2024/openvino-workflow/running-inference.html\">OpenVINO Runtime</a></td>\n <td>`openvino package`</td>\n <td>OpenVINO Runtime is a set of C++ libraries with C and Python bindings providing a common\n API to deliver inference solutions on the platform of your choice. Use the OpenVINO\n Runtime API to read PyTorch, TensorFlow, TensorFlow Lite, ONNX, and PaddlePaddle models\n and execute them on preferred devices. OpenVINO Runtime uses a plugin architecture and\n includes the following plugins:\n <a href=\"https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/cpu-device.html\">CPU</a>,\n <a href=\"https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device.html\">GPU</a>,\n <a href=\"https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching.html\">Auto Batch</a>,\n <a href=\"https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/auto-device-selection.html\">Auto</a>,\n <a href=\"https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes/hetero-execution.html\">Hetero</a>,\n </td>\n </tr>\n <tr>\n <td><a href=\"https://docs.openvino.ai/2024/openvino-workflow/model-preparation.html#convert-a-model-in-cli-ovc\">OpenVINO Model Converter (OVC)</a></td>\n <td>`ovc`</td>\n <td>OpenVINO Model Converter converts models that were trained in popular frameworks to a\n format usable by OpenVINO components. </br>Supported frameworks include ONNX, TensorFlow,\n TensorFlow Lite, and PaddlePaddle.\n </td>\n </tr>\n <tr>\n <td><a href=\"https://docs.openvino.ai/2024/learn-openvino/openvino-samples/benchmark-tool.html\">Benchmark Tool</a></td>\n <td>`benchmark_app`</td>\n <td>Benchmark Application** allows you to estimate deep learning inference performance on\n supported devices for synchronous and asynchronous modes.\n </td>\n</table> |\n\n\n\n## Troubleshooting\n\nFor general troubleshooting steps and issues, see\n[Troubleshooting Guide for OpenVINO Installation](https://docs.openvino.ai/2024/get-started/troubleshooting-install-config.html).\nThe following sections also provide explanations to several error messages.\n\n### Errors with Installing via PIP for Users in China\n\nUsers in China may encounter errors while downloading sources via PIP during OpenVINO\u2122 installation.\nTo resolve the issues, try the following solution:\n\n* Add the download source using the ``-i`` parameter with the Python ``pip`` command. For example:\n\n ``` sh\n pip install openvino -i https://mirrors.aliyun.com/pypi/simple/\n ```\n Use the ``--trusted-host`` parameter if the URL above is ``http`` instead of ``https``.\n\n### ERROR:root:Could not find OpenVINO Python API.\n\nOn Windows, additional libraries may be necessary to run OpenVINO. To resolve this issue, install\nthe [C++ redistributable (.exe)](https://aka.ms/vs/17/release/vc_redist.x64.exe).\nYou can also view a full download list on the\n[official support page](https://docs.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist).\n\n### ImportError: libpython3.8.so.1.0: cannot open shared object file: No such file or directory\n\nTo resolve missing external dependency on Ubuntu*, execute the following command:\n```sh\nsudo apt-get install libpython3.8\n```\n\n## Additional Resources\n\n- [Intel\u00ae Distribution of OpenVINO\u2122 toolkit](https://software.intel.com/en-us/openvino-toolkit)\n- [OpenVINO\u2122 Documentation](https://docs.openvino.ai/)\n- [OpenVINO\u2122 Notebooks](https://github.com/openvinotoolkit/openvino_notebooks)\n- [OpenVINO Installation Selector Tool](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/download.html)\n\nCopyright \u00a9 2018-2024 Intel Corporation\n> **LEGAL NOTICE**: Your use of this software and any required dependent software (the\n\u201cSoftware Package\u201d) is subject to the terms and conditions of the\n[Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0.html) for the Software Package,\nwhich may also include notices, disclaimers, or license terms for third party or open source\nsoftware included in or with the Software Package, and your use indicates your acceptance of all\nsuch terms. Please refer to the \u201cthird-party-programs.txt\u201d or other similarly-named text file\nincluded with the Software Package for additional details.\n\n>Intel is committed to the respect of human rights and avoiding complicity in human rights abuses,\na policy reflected in the [Intel Global Human Rights Principles](https://www.intel.com/content/www/us/en/policy/policy-human-rights.html).\nAccordingly, by accessing the Intel material on this platform you agree that you will not use the\nmaterial in a product or application that causes or contributes to a violation of an\ninternationally recognized human right.\n\nIntel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its\nsubsidiaries. Other names and brands may be claimed as the property of others.\n",
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