Port 2022.2 install guide to master (#13138)
* port installing from archive * fix formatting in code * Updating archive names in qsg (#12927) * port 2022.2 install guide changes to master * small fix Co-authored-by: Artyom Anokhov <artyom.anokhov@intel.com>
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README.md
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README.md
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@ -144,7 +144,7 @@ The latest documentation for OpenVINO™ Toolkit is available [here](https://doc
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### Developer documentation
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[Developer documentation](./docs/dev/index.md) contains information about architectural decisions used inside the OpenVINO components. This documentation has all necessary information for contribution to OpenVINO.
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[Developer documentation](./docs/dev/index.md) contains information about architectural decisions which are applied inside the OpenVINO components. This documentation has all necessary information which could be needed in order to contribute to OpenVINO.
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## Tutorials
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@ -161,11 +161,11 @@ The list of OpenVINO tutorials:
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## System requirements
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The full information about system requirements depends on platform is available on dedicated pages:
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- [Linux](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_linux.html#system-requirements)
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- [Windows](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_windows.html#system-requirements)
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- [macOS](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_macos.html#system-requirements)
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- [Raspbian](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_raspbian.html#system-requirements)
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The full information about system requirements depends on platform and is available on dedicated pages:
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- [Linux](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_linux_header.html)
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- [Windows](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_windows_header.html)
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- [macOS](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_macos_header.html)
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- [Raspbian](https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_raspbian.html)
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## How to build
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@ -14,8 +14,7 @@ To use the Deployment Manager tool, the following requirements need to be met:
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* **For VPU**, see [Configurations for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs](../../install_guides/configurations-for-ivad-vpu.md).
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* **For GNA**, see [Intel® Gaussian & Neural Accelerator (GNA)](../../install_guides/configurations-for-intel-gna.md)
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> **IMPORTANT**: The target operating system must be the same as the development system on which you are creating the package. For example, if the target system is Ubuntu 18.04, the deployment package must be created from the OpenVINO™ toolkit installed on Ubuntu 18.04.
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> **IMPORTANT**: The operating system on the target system must be the same as the development system on which you are creating the package. For example, if the target system is Ubuntu 18.04, the deployment package must be created from the OpenVINO™ toolkit installed on Ubuntu 18.04.
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> **TIP**: If your application requires additional dependencies, including the Microsoft Visual C++ Redistributable, use the ['--user_data' option](https://docs.openvino.ai/latest/openvino_docs_install_guides_deployment_manager_tool.html#run-standard-cli-mode) to add them to the deployment archive. Install these dependencies on the target host before running inference.
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@ -6,7 +6,7 @@ The OpenVINO Runtime HDDL plugin was developed for inference with neural network
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## Configuring the HDDL Plugin
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To configure your Intel® Vision Accelerator Design With Intel® Movidius™ on supported operating systems, refer to the [installation guide](../../install_guides/installing-openvino-config-ivad-vpu).
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To configure your Intel® Vision Accelerator Design With Intel® Movidius™ on supported operating systems, refer to the [Additional Configurations for VPU](../../install_guides/configurations-for-ivad-vpu.md) in Installation Guide.
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> **NOTE**: The HDDL and Myriad plugins may cause conflicts when used at the same time.
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> To ensure proper operation in such a case, the number of booted devices needs to be limited in the 'hddl_autoboot.config' file.
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@ -5,7 +5,7 @@ The OpenVINO Runtime MYRIAD plugin has been developed for inference of neural ne
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## Configuring the MYRIAD Plugin
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To configure your Intel® Vision Accelerator Design With Intel® Movidius™ on supported operating systems, refer to the [installation guide](../../install_guides/installing-openvino-config-ivad-vpu).
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To configure your Intel® Vision Accelerator Design With Intel® Movidius™ on supported operating systems, refer to the [Additional Configurations for VPU](../../install_guides/configurations-for-ivad-vpu.md) in Installation Guide.
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> **NOTE**: The HDDL and MYRIAD plugins may cause conflicts when used at the same time.
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> To ensure proper operation in such a case, the number of booted devices needs to be limited in the `hddl_autoboot.config` file.
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@ -21,15 +21,15 @@ If you have not yet installed and configured the toolkit, see the following guid
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@sphinxdirective
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.. tab:: Linux
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See :doc:`Install Intel® Distribution of OpenVINO™ toolkit for Linux <openvino_docs_install_guides_installing_openvino_linux>`
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See :doc:`Install Intel® Distribution of OpenVINO™ toolkit for Linux <openvino_docs_install_guides_installing_openvino_linux_header>`
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.. tab:: Windows
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See :doc:`Install Intel® Distribution of OpenVINO™ toolkit for Windows <openvino_docs_install_guides_installing_openvino_windows>`
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See :doc:`Install Intel® Distribution of OpenVINO™ toolkit for Windows <openvino_docs_install_guides_installing_openvino_windows_header>`
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.. tab:: macOS
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See :doc:`Install Intel® Distribution of OpenVINO™ toolkit for macOS <openvino_docs_install_guides_installing_openvino_macos>`
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See :doc:`Install Intel® Distribution of OpenVINO™ toolkit for macOS <openvino_docs_install_guides_installing_openvino_macos_header>`
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@endsphinxdirective
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@ -12,7 +12,7 @@ This page introduces additional configurations for Intel® Processor Graphics (G
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## Linux
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If you have installed OpenVINO Runtime via the installer, APT, or YUM, follow these steps to work with GPU:
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If you have installed OpenVINO Runtime from the archive file, follow these steps to work with GPU:
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1. Go to the install_dependencies directory:
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```sh
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@ -38,9 +38,7 @@ If you have installed OpenVINO Runtime via the installer, APT, or YUM, follow th
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3. **Optional:** Install header files to allow compilation of new code. You can find the header files at [Khronos OpenCL™ API Headers](https://github.com/KhronosGroup/OpenCL-Headers.git).
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You've completed all required configuration steps to perform inference on processor graphics.
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Proceed to the <a href="openvino_docs_install_guides_installing_openvino_linux.html#get-started">Start Using the Toolkit</a> section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
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You've completed all required configuration steps to perform inference on processor graphics.
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@sphinxdirective
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.. _gpu guide windows:
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@ -66,5 +64,18 @@ To check if you have this driver installed:
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4. Click the **Driver** tab to see the driver version.
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You are done updating your device driver and are ready to use your GPU. Proceed to the <a href="openvino_docs_install_guides_installing_openvino_windows.html#get-started">Start Using the Toolkit</a> section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
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You are done updating your device driver and are ready to use your GPU.
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## What’s Next?
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You can try out the toolkit with:
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Developing in Python:
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* [Start with tensorflow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
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* [Start with ONNX and PyTorch models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/102-pytorch-onnx-to-openvino-with-output.html)
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* [Start with PaddlePaddle models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html)
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Developing in C++:
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* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
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* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
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* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
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@ -65,4 +65,16 @@ You are done installing your device driver and are ready to use your Intel® Vis
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For advanced configuration steps for your IEI Mustang-V100-MX8 accelerator, see [Configurations for IEI Mustang-V100-MX8-R10 card](configurations-for-iei-card.md).
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After configuration is done, you are ready to go to <a href="openvino_docs_install_guides_installing_openvino_windows.html#get-started">Start Using the Toolkit</a> section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
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## What’s Next?
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After configuration is done, you are ready to try out the toolkit.
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Developing in Python:
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* [Start with tensorflow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
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* [Start with ONNX and PyTorch models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/102-pytorch-onnx-to-openvino-with-output.html)
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* [Start with PaddlePaddle models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html)
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Developing in C++:
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* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
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* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
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* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
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@ -93,4 +93,17 @@ brew install libusb
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```
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You've completed all required configuration steps to perform inference on your Intel® Neural Compute Stick 2.
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Proceed to the <a href="openvino_docs_install_guides_installing_openvino_macos.html#get-started">Start Using the Toolkit</a> section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
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## What’s Next?
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Now you are ready to try out the toolkit. You can use the following tutorials to write your applications using Python and C++.
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Developing in Python:
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* [Start with tensorflow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
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* [Start with ONNX and PyTorch models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/102-pytorch-onnx-to-openvino-with-output.html)
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* [Start with PaddlePaddle models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html)
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Developing in C++:
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* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
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* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
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* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
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@ -96,22 +96,22 @@ You will see the help message for Model Optimizer if installation finished succe
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Note the following things:
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* To install OpenVINO Development Tools, you must have OpenVINO Runtime installed first. You can install OpenVINO Runtime through an installer ([Linux](installing-openvino-linux.md), [Windows](installing-openvino-windows.md), or [macOS](installing-openvino-macos.md)), [APT for Linux](installing-openvino-apt.md) or [YUM for Linux](installing-openvino-yum.md).
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* To install OpenVINO Development Tools, you must have OpenVINO Runtime installed first. You can install OpenVINO Runtime through archive files. See [Install OpenVINO on Linux from Archive](installing-openvino-from-archive-linux.md), [Install OpenVINO on Windows from Archive](installing-openvino-from-archive-windows.md), and [Install OpenVINO on macOS from Archive](installing-openvino-from-archive-macos.md) for more details.
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* Ensure that the version of OpenVINO Development Tools you are installing matches that of OpenVINO Runtime.
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Use either of the following ways to install OpenVINO Development Tools:
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### Recommended: Install Using the Requirements Files
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1. After you have installed OpenVINO Runtime from an installer, APT or YUM repository, you can find a set of requirements files in the `<INSTALLDIR>\tools\` directory. Select the most suitable ones to use.
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1. After you have installed OpenVINO Runtime from an archive file, you can find a set of requirements files in the `<INSTALL_DIR>\tools\` directory. Select the most suitable ones to use.
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2. Install the same version of OpenVINO Development Tools by using the requirements files.
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To install mandatory requirements only, use the following command:
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```
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pip install -r <INSTALLDIR>\tools\requirements.txt
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pip install -r <INSTALL_DIR>\tools\requirements.txt
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```
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3. Make sure that you also install your additional frameworks with the corresponding requirements files. For example, if you are using a TensorFlow model, use the following command to install requirements for TensorFlow:
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```
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pip install -r <INSTALLDIR>\tools\requirements_tensorflow2.txt
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pip install -r <INSTALL_DIR>\tools\requirements_tensorflow2.txt
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```
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### Alternative: Install from the openvino-dev Package
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# Install Intel® Distribution of OpenVINO™ Toolkit for Linux Using APT Repository {#openvino_docs_install_guides_installing_openvino_apt}
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# Install Intel® Distribution of OpenVINO™ Toolkit for Linux Using APT Repository
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This guide provides installation steps for Intel® Distribution of OpenVINO™ toolkit for Linux distributed through the APT repository.
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Currently only the following ways are provided to install OpenVINO™:
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> **NOTE**: From the 2022.1 release, the OpenVINO™ Development Tools can only be installed via PyPI. If you want to develop or optimize your models with OpenVINO, see [Install OpenVINO Development Tools](installing-model-dev-tools.md) for detailed steps.
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* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-linux.md)
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* [Install OpenVINO from PyPI](installing-openvino-pip.md)
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* [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
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* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
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> **IMPORTANT**: By downloading and using this container and the included software, you agree to the terms and conditions of the [software license agreements](https://software.intel.com/content/dam/develop/external/us/en/documents/intel-openvino-license-agreements.pdf). Please review the content inside the `<INSTALL_DIR>/licensing` folder for more details.
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The other installation methods are temporarily unavailable.
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## System Requirements
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The complete list of supported hardware is available in the [Release Notes](https://software.intel.com/content/www/us/en/develop/articles/openvino-relnotes.html).
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**Operating Systems**
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- Ubuntu 18.04 long-term support (LTS), 64-bit
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- Ubuntu 20.04 long-term support (LTS), 64-bit
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**Software**
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- [CMake 3.13 or higher, 64-bit](https://cmake.org/download/)
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- GCC 7.5.0 (for Ubuntu 18.04) or GCC 9.3.0 (for Ubuntu 20.04)
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- [Python 3.6 - 3.10, 64-bit](https://www.python.org/downloads/windows/)
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## Install OpenVINO Runtime
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### Step 1: Set Up the OpenVINO Toolkit APT Repository
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1. Install the GPG key for the repository
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a. Download the [GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB](https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB). You can also use the following command:
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```sh
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wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
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```
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b. Add this key to the system keyring:
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```sh
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sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
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```
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> **NOTE**: You might need to install GnuPG: `sudo apt-get install gnupg`
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2. Add the repository via the following command:
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@sphinxdirective
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.. tab:: Ubuntu 18
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.. code-block:: sh
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echo "deb https://apt.repos.intel.com/openvino/2022 bionic main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2022.list
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.. tab:: Ubuntu 20
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.. code-block:: sh
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echo "deb https://apt.repos.intel.com/openvino/2022 focal main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2022.list
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@endsphinxdirective
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3. Update the list of packages via the update command:
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```sh
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sudo apt update
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```
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4. Verify that the APT repository is properly set up. Run the apt-cache command to see a list of all available OpenVINO packages and components:
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```sh
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apt-cache search openvino
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```
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### Step 2: Install OpenVINO Runtime Using the APT Package Manager
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OpenVINO will be installed in: `/opt/intel/openvino_<VERSION>.<UPDATE>.<PATCH>`
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A symlink will be created: `/opt/intel/openvino_<VERSION>`
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#### To Install the Latest Version
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Run the following command:
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```sh
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sudo apt install openvino
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```
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#### To Install a Specific Version
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1. Get a list of OpenVINO packages available for installation:
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```sh
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sudo apt-cache search openvino
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```
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2. Install a specific version of an OpenVINO package:
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```sh
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sudo apt install openvino-<VERSION>.<UPDATE>.<PATCH>
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```
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For example:
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```sh
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sudo apt install openvino-2022.1.0
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```
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#### To Check for Installed Packages and Versions
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Run the following command:
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```sh
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apt list --installed | grep openvino
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```
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#### To Uninstall the Latest Version
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Run the following command:
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```sh
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sudo apt autoremove openvino
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```
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#### To Uninstall a Specific Version
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Run the following command:
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```sh
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sudo apt autoremove openvino-<VERSION>.<UPDATE>.<PATCH>
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```
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### Step 3 (Optional): Install OpenCV from APT
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OpenCV is necessary to run C++ demos from Open Model Zoo. Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. OpenVINO provides a package to install OpenCV from APT:
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#### To Install the Latest Version of OpenCV
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Run the following command:
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```sh
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sudo apt install openvino-opencv
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```
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#### To Install a Specific Version of OpenCV
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Run the following command:
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```sh
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sudo apt install openvino-opencv-<VERSION>.<UPDATE>.<PATCH>
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```
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### Step 4 (Optional): Install Software Dependencies
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After you have installed OpenVINO Runtime, if you decided to [install OpenVINO Development Tools](installing-model-dev-tools.md), make sure that you install external software dependencies first.
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Refer to <a href="openvino_docs_install_guides_installing_openvino_linux.html#install-external-dependencies">Install External Software Dependencies</a> for detailed steps.
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### Step 5 (Optional): Configure Inference on Non-CPU Devices
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@sphinxdirective
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.. tab:: GNA
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To enable the toolkit components to use Intel® Gaussian & Neural Accelerator (GNA) on your system, follow the steps in :ref:`GNA Setup Guide <gna guide>`.
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||||
.. tab:: GPU
|
||||
|
||||
To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:`GPU Setup Guide <gpu guide>`.
|
||||
|
||||
.. tab:: NCS 2
|
||||
|
||||
To perform inference on Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X VPU, follow the steps on :ref:`NCS2 Setup Guide <ncs guide>`.
|
||||
<!--For more details, see the `Get Started page for Intel® Neural Compute Stick 2 <https://software.intel.com/en-us/neural-compute-stick/get-started>`.-->
|
||||
|
||||
.. tab:: VPU
|
||||
|
||||
To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:`VPU Configuration Guide <vpu guide>`.
|
||||
After configuration is done, you are ready to run the verification scripts with the HDDL Plugin for your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
|
||||
|
||||
.. warning::
|
||||
While working with either HDDL or NCS, choose one of them as they cannot run simultaneously on the same machine.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## What's Next?
|
||||
|
||||
Now you may continue with the following tasks:
|
||||
|
||||
* To convert models for use with OpenVINO, see [Model Optimizer Developer Guide](../MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md).
|
||||
* See pre-trained deep learning models in our [Open Model Zoo](../model_zoo.md).
|
||||
* Try out OpenVINO via [OpenVINO Notebooks](https://docs.openvino.ai/latest/notebooks/notebooks.html).
|
||||
* To write your own OpenVINO™ applications, see [OpenVINO Runtime User Guide](../OV_Runtime_UG/openvino_intro.md).
|
||||
* See sample applications in [OpenVINO™ Toolkit Samples Overview](../OV_Runtime_UG/Samples_Overview.md).
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- Intel® Distribution of OpenVINO™ toolkit home page: <https://software.intel.com/en-us/openvino-toolkit>.
|
||||
- For IoT Libraries & Code Samples see the [Intel® IoT Developer Kit](https://github.com/intel-iot-devkit).
|
||||
|
|
|
|||
|
|
@ -1,74 +1,10 @@
|
|||
# Install Intel® Distribution of OpenVINO™ toolkit from Anaconda Cloud {#openvino_docs_install_guides_installing_openvino_conda}
|
||||
# Install Intel® Distribution of OpenVINO™ toolkit from Anaconda Cloud
|
||||
|
||||
This guide provides installation steps for Intel® Distribution of OpenVINO™ toolkit for Linux distributed through the Anaconda Cloud.
|
||||
Currently only the following ways are provided to install OpenVINO™:
|
||||
|
||||
> **NOTE**: From the 2022.1 release, the OpenVINO™ Development Tools can only be installed via PyPI. If you want to develop or optimize your models with OpenVINO, see [Install OpenVINO Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-linux.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
|
||||
* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
|
||||
|
||||
## System Requirements
|
||||
|
||||
**Software**
|
||||
|
||||
- [Anaconda distribution](https://www.anaconda.com/products/individual/)
|
||||
|
||||
**Operating Systems**
|
||||
|
||||
| Supported Operating System | [Python Version (64-bit)](https://www.python.org/) |
|
||||
| :------------------------------------------------------------| :--------------------------------------------------|
|
||||
| Ubuntu 18.04 long-term support (LTS), 64-bit | 3.6, 3.7, 3.8, 3.9, 3.10 |
|
||||
| Ubuntu 20.04 long-term support (LTS), 64-bit | 3.6, 3.7, 3.8, 3.9, 3.10 |
|
||||
| Red Hat Enterprise Linux 8, 64-bit | 3.6, 3.7, 3.8, 3.9, 3.10 |
|
||||
| macOS 10.15 | 3.6, 3.7, 3.8, 3.9, 3.10 |
|
||||
| Windows 10, 64-bit | 3.6, 3.7, 3.8, 3.9, 3.10 |
|
||||
|
||||
## Install OpenVINO Runtime Using the Anaconda Package Manager
|
||||
|
||||
1. Set up the Anaconda environment (taking Python 3.7 for example):
|
||||
```sh
|
||||
conda create --name py37 python=3.7
|
||||
conda activate py37
|
||||
```
|
||||
2. Update Anaconda environment to the latest version:
|
||||
```sh
|
||||
conda update --all
|
||||
```
|
||||
3. Install the Intel® Distribution of OpenVINO™ toolkit:
|
||||
- Ubuntu* 20.04
|
||||
```sh
|
||||
conda install openvino-ie4py-ubuntu20 -c intel
|
||||
```
|
||||
- Ubuntu* 18.04
|
||||
```sh
|
||||
conda install openvino-ie4py-ubuntu18 -c intel
|
||||
```
|
||||
- Red Hat Enterprise Linux 8, 64-bit
|
||||
```sh
|
||||
conda install openvino-ie4py-rhel8 -c intel
|
||||
```
|
||||
- Windows 10 and macOS
|
||||
```sh
|
||||
conda install openvino-ie4py -c intel
|
||||
```
|
||||
4. Verify the package is installed:
|
||||
```sh
|
||||
python -c "from openvino.runtime import Core"
|
||||
```
|
||||
If installation was successful, you will not see any error messages (no console output).
|
||||
|
||||
Now you can start developing your application.
|
||||
|
||||
|
||||
## What's Next?
|
||||
|
||||
Now you may continue with the following tasks:
|
||||
|
||||
* To convert models for use with OpenVINO, see [Model Optimizer Developer Guide](../MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md).
|
||||
* See pre-trained deep learning models in our [Open Model Zoo](../model_zoo.md).
|
||||
* Try out OpenVINO via [OpenVINO Notebooks](https://docs.openvino.ai/latest/notebooks/notebooks.html).
|
||||
* To write your own OpenVINO™ applications, see [OpenVINO Runtime User Guide](../OV_Runtime_UG/openvino_intro.md).
|
||||
* See sample applications in [OpenVINO™ Toolkit Samples Overview](../OV_Runtime_UG/Samples_Overview.md).
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- Intel® Distribution of OpenVINO™ toolkit home page: <https://software.intel.com/en-us/openvino-toolkit>.
|
||||
- For IoT Libraries & Code Samples see the [Intel® IoT Developer Kit](https://github.com/intel-iot-devkit).
|
||||
- Intel® Distribution of OpenVINO™ toolkit Anaconda home page: [https://anaconda.org/intel/openvino-ie4py](https://anaconda.org/intel/openvino-ie4py)
|
||||
The other installation methods are temporarily unavailable.
|
||||
|
|
|
|||
|
|
@ -0,0 +1,174 @@
|
|||
# Install OpenVINO™ Runtime on Linux from an Archive File {#openvino_docs_install_guides_installing_openvino_from_archive_linux}
|
||||
|
||||
With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime.
|
||||
|
||||
You can also check the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in this release.
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter can be installed via [pypi.org](https://pypi.org/project/openvino-dev/) only.
|
||||
|
||||
## System Requirements
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Operating Systems
|
||||
|
||||
* Ubuntu 18.04 long-term support (LTS), 64-bit
|
||||
* Ubuntu 20.04 long-term support (LTS), 64-bit
|
||||
|
||||
.. note::
|
||||
Since the OpenVINO™ 2022.1 release, CentOS 7.6, 64-bit is not longer supported.
|
||||
|
||||
.. tab:: Hardware
|
||||
|
||||
Optimized for these processors:
|
||||
|
||||
* 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
|
||||
* 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
|
||||
* Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
|
||||
* Intel Atom® processor with support for Intel® Streaming SIMD Extensions 4.1 (Intel® SSE4.1)
|
||||
* Intel Pentium® processor N4200/5, N3350/5, or N3450/5 with Intel® HD Graphics
|
||||
* Intel® Iris® Xe MAX Graphics
|
||||
* Intel® Neural Compute Stick 2
|
||||
* Intel® Vision Accelerator Design with Intel® Movidius™ VPUs
|
||||
|
||||
.. tab:: Processor Notes
|
||||
|
||||
Processor graphics are not included in all processors.
|
||||
See `Product Specifications`_ for information about your processor.
|
||||
|
||||
.. _Product Specifications: https://ark.intel.com/
|
||||
|
||||
.. tab:: Software
|
||||
|
||||
* `CMake 3.13 or higher, 64-bit <https://cmake.org/download/>`_
|
||||
* GCC 7.5.0 (for Ubuntu 18.04) or GCC 9.3.0 (for Ubuntu 20.04)
|
||||
* `Python 3.6 - 3.9, 64-bit <https://www.python.org/downloads/windows/>`_
|
||||
* Note that OpenVINO is gradually stopping the support for Python 3.6. Python 3.7 - 3.9 are recommended.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Installing OpenVINO Runtime
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. important::
|
||||
Before you start your journey with installation of the Intel® Distribution of OpenVINO™ toolkit, we encourage you to check the :ref:`code samples <code samples>` in C, C++, Python and :ref:`notebook tutorials <notebook tutorials>`, so you could see all the amazing things that you can achieve with our tool.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
### <a name="install-openvino"></a>Step 1: Download and Install the OpenVINO Package
|
||||
|
||||
1. Select and download the OpenVINO™ archive files from [Intel® Distribution of OpenVINO™ toolkit download page](https://software.intel.com/en-us/openvino-toolkit/choose-download). There are typically two files for you to download:
|
||||
```sh
|
||||
l_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz
|
||||
l_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz.sha256
|
||||
```
|
||||
where the `.sha256` file is used to verify the success of the download process.
|
||||
2. Open a command prompt terminal window. You can use the keyboard shortcut: Ctrl+Alt+T
|
||||
3. Change the directory to where you downloaded the archive files.<br>
|
||||
For example, if you downloaded the files to the current user's `Downloads` directory, use the following command:
|
||||
```sh
|
||||
cd ~/Downloads/
|
||||
```
|
||||
4. To verify the package by using the `.sha256` file:
|
||||
```sh
|
||||
sha256sum -с <archive name>.tgz.sha256
|
||||
```
|
||||
If any error message appears, check your network connections, re-download the correct files, and make sure the download process completes successfully.
|
||||
5. Extract OpenVINO files from the `.tgz` file:
|
||||
```sh
|
||||
tar xf <archive name>.tgz -C <destination_dir>
|
||||
```
|
||||
where the `<destination_dir>` is the directory that you extract OpenVINO files to. You're recommended to set it as:
|
||||
* For root users or administrators: `/opt/intel/`
|
||||
* For regular users: `/home/<USER>/intel/`
|
||||
|
||||
If you forgot to set the directory in Step 5, you can then use `sudo mv <extracted_folder> /opt/intel` (for root users or administrators), or `mv <extracted_folder> /home/<USER>/intel/` (for regular users) to set that.
|
||||
|
||||
For simplicity, it is useful to create a symbolink link:
|
||||
```sh
|
||||
ln -s /home/<USER>/intel/<extracted_folder> /home/<USER>/intel/openvino_2022
|
||||
```
|
||||
If such link already exists, remove the previous link with `rm /home/<USER>/intel/openvino_2022`.
|
||||
|
||||
The `/opt/intel/openvino_<version>/` or `/home/<USER>/intel/openvino_<version>/` will be referred as the standard OpenVINO `<INSTALL_DIR>` in this document.
|
||||
|
||||
The core components are now installed. Continue to the next section to install components.
|
||||
|
||||
### <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
|
||||
|
||||
You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:
|
||||
|
||||
```sh
|
||||
source <INSTALL_DIR>/setupvars.sh
|
||||
```
|
||||
|
||||
If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
|
||||
|
||||
> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.
|
||||
|
||||
The environment variables are set. Next, you can download some additional tools.
|
||||
|
||||
### <a name="model-optimizer">Step 3 (Optional): Install Additional Components
|
||||
|
||||
Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter can only be installed via PyPI. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
||||
OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on Github](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
|
||||
|
||||
### <a name="optional-steps"></a>Step 4 (Optional): Configure Inference on Non-CPU Devices
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: GPU
|
||||
|
||||
To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:`GPU Setup Guide <gpu guide>`.
|
||||
|
||||
.. tab:: NCS 2
|
||||
|
||||
To perform inference on Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X VPU, follow the steps on :ref:`NCS2 Setup Guide <ncs guide>`.
|
||||
<!--For more details, see the `Get Started page for Intel® Neural Compute Stick 2 <https://software.intel.com/en-us/neural-compute-stick/get-started>`.-->
|
||||
|
||||
.. tab:: VPU
|
||||
|
||||
To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:`VPU Configuration Guide <vpu guide>`.
|
||||
After configuration is done, you are ready to run the verification scripts with the HDDL Plugin for your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
|
||||
|
||||
.. warning::
|
||||
While working with either HDDL or NCS, choose one of them as they cannot run simultaneously on the same machine.
|
||||
|
||||
.. tab:: GNA
|
||||
|
||||
To enable the toolkit components to use Intel® Gaussian & Neural Accelerator (GNA) on your system, follow the steps in :ref:`GNA Setup Guide <gna guide>`.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="get-started"></a>What's Next?
|
||||
|
||||
Now you are ready to try out the toolkit.
|
||||
|
||||
Start with some Python tutorials:
|
||||
* [Hello Image Classification](https://docs.openvino.ai/latest/notebooks/001-hello-world-with-output.html)
|
||||
* [Convert TensorFlow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
|
||||
* [Convert a PyTorch model and remove the image background](https://docs.openvino.ai/latest/notebooks/205-vision-background-removal-with-output.html)
|
||||
|
||||
To start with C++ samples, see [Build Sample Applications on Linux](../OV_Runtime_UG/Samples_Overview.md#build_samples_linux) first, and then you can try the following samples:
|
||||
* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
|
||||
* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
|
||||
* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
|
||||
|
||||
## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
|
||||
|
||||
## Additional Resources
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
* :ref:`Troubleshooting Guide for OpenVINO Installation & Configuration <troubleshooting guide for install>`
|
||||
* Converting models for use with OpenVINO™: :ref:`Model Optimizer User Guide <deep learning model optimizer>`
|
||||
* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
|
||||
* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
|
||||
* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
|
||||
* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
|
||||
|
||||
.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
|
||||
|
||||
@endsphinxdirective
|
||||
|
|
@ -0,0 +1,143 @@
|
|||
# Install OpenVINO™ Runtime on macOS from an Archive File {#openvino_docs_install_guides_installing_openvino_from_archive_macos}
|
||||
|
||||
With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime.
|
||||
|
||||
You can also check the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in this release.
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter can be installed via [pypi.org](https://pypi.org/project/openvino-dev/) only.
|
||||
|
||||
> **NOTE**: The Intel® Distribution of OpenVINO™ toolkit is supported on macOS version 10.15 with Intel® processor-based machines.
|
||||
|
||||
## System Requirements
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Operating Systems
|
||||
|
||||
macOS 10.15
|
||||
|
||||
.. tab:: Hardware
|
||||
|
||||
Optimized for these processors:
|
||||
|
||||
* 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
|
||||
* 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
|
||||
* Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
|
||||
* Intel® Neural Compute Stick 2
|
||||
|
||||
.. note::
|
||||
The current version of the Intel® Distribution of OpenVINO™ toolkit for macOS supports inference on Intel CPUs and Intel® Neural Compute Stick 2 devices only.
|
||||
|
||||
.. tab:: Software Requirements
|
||||
|
||||
* `CMake 3.13 or higher <https://cmake.org/download/>`_ (choose "macOS 10.13 or later"). Add `/Applications/CMake.app/Contents/bin` to path (for default install).
|
||||
* `Python 3.6 - 3.9 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.6 - 3.9). Install and add to path.
|
||||
* Note that OpenVINO is gradually stopping the support for Python 3.6. Python 3.7 - 3.9 are recommended.
|
||||
* Apple Xcode Command Line Tools. In the terminal, run `xcode-select --install` from any directory
|
||||
* (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Installing OpenVINO Runtime
|
||||
|
||||
### <a name="install-core"></a>Step 1: Install OpenVINO Core Components
|
||||
|
||||
1. Select and download the OpenVINO™ archive files from [Intel® Distribution of OpenVINO™ toolkit for macOS download page](https://software.intel.com/en-us/openvino-toolkit/choose-download/free-download-macos). There are typically two files for you to download:
|
||||
```sh
|
||||
m_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz
|
||||
m_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz.sha256
|
||||
```
|
||||
where the `.sha256` file is used to verify the success of the download process.
|
||||
|
||||
2. Locate the downloaded files in your system. This document assumes the files are in your `Downloads` directory.
|
||||
|
||||
3. Open a command prompt terminal window, and verify the checksum of the `sha256` file by using the following command:
|
||||
```sh
|
||||
shasum -c -a 256 <archive name>.tgz.sha256
|
||||
```
|
||||
If any error message appears, check your network connections, re-download the correct files, and make sure the download process completes successfully.
|
||||
|
||||
4. Extract OpenVINO files from the `.tgz` file:
|
||||
```sh
|
||||
tar xf <archive name>.tgz -C <destination_dir>
|
||||
```
|
||||
where the `<destination_dir>` is the directory that you extract OpenVINO files to. You're recommended to set it as `/opt/intel/`.
|
||||
The standard OpenVINO `INSTALL_DIR` referenced in this document is `/opt/intel/openvino_<version>`.
|
||||
|
||||
For simplicity, you can create a symbolic link to the latest installation: `/opt/intel/openvino_2022/`.
|
||||
|
||||
The core components are now installed. Continue to the next section to configure environment.
|
||||
|
||||
### <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
|
||||
|
||||
You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:
|
||||
|
||||
```sh
|
||||
source <INSTALL_DIR>/setupvars.sh
|
||||
```
|
||||
|
||||
If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
|
||||
|
||||
> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.
|
||||
|
||||
The environment variables are set. Continue to the next section if you want to download any additional components.
|
||||
|
||||
### <a name="model-optimizer"></a>Step 3 (Optional): Install Additional Components
|
||||
|
||||
Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
||||
OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on Github](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
|
||||
|
||||
### <a name="configure-ncs2"></a>Step 4 (Optional): Configure the Intel® Neural Compute Stick 2
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
If you want to run inference on Intel® Neural Compute Stick 2 use the following instructions to setup the device: :ref:`NCS2 Setup Guide <ncs guide macos>`.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="get-started"></a>What's Next?
|
||||
|
||||
Now you are ready to try out the toolkit. You can use the following tutorials to write your applications using Python and C++.
|
||||
|
||||
Start with some Python tutorials:
|
||||
* [Hello Image Classification](https://docs.openvino.ai/latest/notebooks/001-hello-world-with-output.html)
|
||||
* [Convert TensorFlow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
|
||||
* [Convert a PyTorch model and remove the image background](https://docs.openvino.ai/latest/notebooks/205-vision-background-removal-with-output.html)
|
||||
|
||||
To start with C++ samples, see [Build Sample Applications on macOS](../OV_Runtime_UG/Samples_Overview.md#build_samples_macos) first, and then you can try the following samples:
|
||||
* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
|
||||
* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
|
||||
* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
|
||||
|
||||
## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
|
||||
|
||||
@sphinxdirective
|
||||
.. raw:: html
|
||||
|
||||
</div>
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: Additional Resources
|
||||
|
||||
* Converting models for use with OpenVINO™: :ref:`Model Optimizer Developer Guide <deep learning model optimizer>`
|
||||
* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
|
||||
* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
|
||||
* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
|
||||
* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
|
||||
|
||||
<!---
|
||||
To learn more about converting models from specific frameworks, go to:
|
||||
* :ref:`Convert Your Caffe Model <convert model caffe>`
|
||||
* :ref:`Convert Your TensorFlow Model <convert model tf>`
|
||||
* :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
|
||||
* :ref:`Convert Your Kaldi Model <convert model kaldi>`
|
||||
* :ref:`Convert Your ONNX Model <convert model onnx>`
|
||||
--->
|
||||
.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
|
||||
|
||||
@endsphinxdirective
|
||||
|
|
@ -0,0 +1,168 @@
|
|||
# Install OpenVINO™ Runtime on Windows 10 from an Archive File {#openvino_docs_install_guides_installing_openvino_from_archive_windows}
|
||||
|
||||
With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime.
|
||||
|
||||
You can also check the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in this release.
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter can be installed via [pypi.org](https://pypi.org/project/openvino-dev/) only.
|
||||
|
||||
## System Requirements
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Operating Systems
|
||||
|
||||
Microsoft Windows 10, 64-bit
|
||||
|
||||
.. tab:: Hardware
|
||||
|
||||
Optimized for these processors:
|
||||
|
||||
* 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
|
||||
* 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
|
||||
* Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
|
||||
* Intel Atom® processor with support for Intel® Streaming SIMD Extensions 4.1 (Intel® SSE4.1)
|
||||
* Intel Pentium® processor N4200/5, N3350/5, or N3450/5 with Intel® HD Graphics
|
||||
* Intel® Iris® Xe MAX Graphics
|
||||
* Intel® Neural Compute Stick 2
|
||||
* Intel® Vision Accelerator Design with Intel® Movidius™ VPUs
|
||||
|
||||
.. tab:: Processor Notes
|
||||
|
||||
Processor graphics are not included in all processors.
|
||||
See `Product Specifications`_ for information about your processor.
|
||||
|
||||
.. _Product Specifications: https://ark.intel.com/
|
||||
|
||||
.. tab:: Software
|
||||
|
||||
* For C++ developers:
|
||||
* `Microsoft Visual Studio 2019 with MSBuild <http://visualstudio.microsoft.com/downloads/>`_
|
||||
* `CMake 3.14 or higher, 64-bit <https://cmake.org/download/>`_ (optional, only required for building sample applications)
|
||||
* For Python developers: `Python 3.6 - 3.9, 64-bit <https://www.python.org/downloads/windows/>`_
|
||||
* Note that OpenVINO is gradually stopping the support for Python 3.6. Python 3.7 - 3.9 are recommended.
|
||||
|
||||
.. note::
|
||||
You can choose to download Community version. Use `Microsoft Visual Studio installation guide <https://docs.microsoft.com/en-us/visualstudio/install/install-visual-studio?view=vs-2019>`_ to walk you through the installation. During installation in the **Workloads** tab, choose **Desktop development with C++**.
|
||||
|
||||
.. note::
|
||||
You can either use `cmake<version>.msi` which is the installation wizard or `cmake<version>.zip` where you have to go into the `bin` folder and then manually add the path to environmental variables.
|
||||
|
||||
.. important::
|
||||
As part of this installation, make sure you click the option **Add Python 3.x to PATH** to `add Python <https://docs.python.org/3/using/windows.html#installation-steps>`_ to your `PATH` environment variable.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Installing OpenVINO Runtime
|
||||
|
||||
### <a name="install-openvino"></a>Step 1: Download and Install OpenVINO Core Components
|
||||
|
||||
1. Select and download the OpenVINO™ archive files from [Intel® Distribution of OpenVINO™ toolkit download page](https://software.intel.com/en-us/openvino-toolkit/choose-download).
|
||||
There are typically two files for you to download:
|
||||
```sh
|
||||
w_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.zip
|
||||
w_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.zip.sha256
|
||||
```
|
||||
where the `.sha256` file is used to verify the success of the download process.
|
||||
|
||||
2. Locate the downloaded files in your system. This document assumes the files are in your `Downloads` directory.
|
||||
|
||||
3. Open a command prompt terminal window, and run the following command with the `.zip` file:
|
||||
```sh
|
||||
CertUtil -hashfile <archive name>.zip SHA256
|
||||
```
|
||||
Compare the returned value in the output with what's in the `<archive name>.zip.sha256` file:
|
||||
* If the values are the same, you have downloaded the correct file successfully.
|
||||
* If not, create a Support ticket [here](https://www.intel.com/content/www/us/en/support/contact-intel.html).
|
||||
|
||||
4. Unzip the `<archive name>.zip` file using your preferred archive tool.
|
||||
> **NOTE**: The name of the archive file might be long. Make sure that you have [enabled long paths on Windows](https://docs.microsoft.com/en-us/windows/win32/fileio/maximum-file-path-limitation?tabs=registry#enable-long-paths-in-windows-10-version-1607-and-later) to avoid possible errors in the unzipping process.
|
||||
|
||||
|
||||
The standard OpenVINO `<INSTALL_DIR>` used in this document is `C:\Program Files (x86)\Intel\openvino_<version>\`. You're recommended to move the extracted files to that directory.
|
||||
|
||||
For simplicity, you can also create a symbolic link to the latest installation: `C:\Program Files (x86)\Intel\openvino_2022\`.
|
||||
|
||||
The core components are now installed. Continue to the next section to configure the environment.
|
||||
|
||||
### <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
|
||||
|
||||
> **NOTE**: If you installed the Intel® Distribution of OpenVINO™ to a non-default install directory, replace `C:\Program Files (x86)\Intel` with that directory in this guide's instructions.
|
||||
|
||||
You must update several environment variables before you can compile and run OpenVINO™ applications. Open the Command Prompt, and run the `setupvars.bat` batch file to temporarily set your environment variables:
|
||||
|
||||
```sh
|
||||
"<INSTALL_DIR>\setupvars.bat"
|
||||
```
|
||||
|
||||
**Optional**: OpenVINO™ toolkit environment variables are removed when you close the command prompt window. You can permanently set the environment variables manually.
|
||||
|
||||
> **NOTE**: If you see an error indicating Python is not installed when you know you installed it, your computer might not be able to find the program. Check your system environment variables, and add Python if necessary.
|
||||
|
||||
The environment variables are set. Next, you can download some additional tools.
|
||||
|
||||
### <a name="model-optimizer">Step 3 (Optional): Install Additional Components</a>
|
||||
|
||||
Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
||||
OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on Github](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
|
||||
|
||||
### <a name="optional-steps"></a>Step 4 (Optional): Configure Inference on non-CPU Devices
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: GPU
|
||||
|
||||
To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:`GPU Setup Guide <gpu guide windows>`.
|
||||
|
||||
.. tab:: VPU
|
||||
|
||||
To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:`VPU Configuration Guide <vpu guide windows>`.
|
||||
|
||||
.. tab:: NCS 2
|
||||
|
||||
No additional configurations are needed.
|
||||
|
||||
.. tab:: GNA
|
||||
|
||||
To enable the toolkit components to use Intel® Gaussian & Neural Accelerator (GNA) on your system, follow the steps in :ref:`GNA Setup Guide <gna guide windows>`.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="get-started"></a>What's Next?
|
||||
|
||||
Now you are ready to try out the toolkit.
|
||||
|
||||
Start with some Python tutorials:
|
||||
* [Hello Image Classification](https://docs.openvino.ai/latest/notebooks/001-hello-world-with-output.html)
|
||||
* [Convert TensorFlow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
|
||||
* [Convert a PyTorch model and remove the image background](https://docs.openvino.ai/latest/notebooks/205-vision-background-removal-with-output.html)
|
||||
|
||||
To start with C++ samples, see [Build Sample Applications on Windows](../OV_Runtime_UG/Samples_Overview.md#build_samples_windows) first, and then you can try the following samples:
|
||||
* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
|
||||
* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
|
||||
* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
|
||||
|
||||
## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: Additional Resources
|
||||
|
||||
* Converting models for use with OpenVINO™: :ref:`Model Optimizer Developer Guide <deep learning model optimizer>`
|
||||
* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
|
||||
* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
|
||||
* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
|
||||
* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
|
||||
|
||||
<!---
|
||||
To learn more about converting models from specific frameworks, go to:
|
||||
* :ref:`Convert Your Caffe Model <convert model caffe>`
|
||||
* :ref:`Convert Your TensorFlow Model <convert model tf>`
|
||||
* :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
|
||||
* :ref:`Convert Your Kaldi Model <convert model kaldi>`
|
||||
* :ref:`Convert Your ONNX Model <convert model onnx>`
|
||||
--->
|
||||
.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
|
||||
|
||||
@endsphinxdirective
|
||||
|
|
@ -1,14 +0,0 @@
|
|||
# Install From Images and Repositories
|
||||
|
||||
You may install Intel® Distribution of OpenVINO™ toolkit from images and repositories using the **Install OpenVINO™** button above or directly from the [Get the Intel® Distribution of OpenVINO™ Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit/download.html) page. Use the documentation below if you need additional support:
|
||||
|
||||
* [Docker](installing-openvino-docker-linux.md)
|
||||
* [Docker with DL Workbench](@ref workbench_docs_Workbench_DG_Run_Locally)
|
||||
* [APT](installing-openvino-apt.md)
|
||||
* [YUM](installing-openvino-yum.md)
|
||||
* [Anaconda Cloud](installing-openvino-conda.md)
|
||||
* [Yocto](installing-openvino-yocto.md)
|
||||
* [PyPI](installing-openvino-pip.md)
|
||||
|
||||
The open source version is available in the [OpenVINO™ toolkit GitHub repository](https://github.com/openvinotoolkit/openvino) and you can build it for supported platforms using the <a href="https://github.com/openvinotoolkit/openvino/wiki/BuildingCode">OpenVINO Build Instructions</a>.
|
||||
|
||||
|
|
@ -6,21 +6,15 @@
|
|||
:maxdepth: 3
|
||||
:hidden:
|
||||
|
||||
Using Installer <openvino_docs_install_guides_installing_openvino_linux>
|
||||
From Archive <openvino_docs_install_guides_installing_openvino_from_archive_linux>
|
||||
From PyPI <openvino_docs_install_guides_installing_openvino_pip>
|
||||
From APT <openvino_docs_install_guides_installing_openvino_apt>
|
||||
From YUM <openvino_docs_install_guides_installing_openvino_yum>
|
||||
From Anaconda Cloud <openvino_docs_install_guides_installing_openvino_conda>
|
||||
Using Docker <openvino_docs_install_guides_installing_openvino_docker_linux>
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
If you want to install Intel® Distribution of OpenVINO™ toolkit on your Linux machine, there are a few ways to accomplish this. We prepared the following options for you:
|
||||
|
||||
* [Install OpenVINO Runtime using an Installer](installing-openvino-linux.md)
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-linux.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO Runtime from APT](installing-openvino-apt.md)
|
||||
* [Install OpenVINO Runtime from YUM](installing-openvino-yum.md)
|
||||
* [Install OpenVINO Runtime from Anaconda Cloud](installing-openvino-conda.md)
|
||||
* [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,214 +1,10 @@
|
|||
# Install and Configure Intel® Distribution of OpenVINO™ Toolkit for Linux {#openvino_docs_install_guides_installing_openvino_linux}
|
||||
# Install Intel® Distribution of OpenVINO™ Toolkit for Linux from Installer
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. These tools are now only available on [pypi.org](https://pypi.org/project/openvino-dev/).
|
||||
Currently only the following ways are provided to install OpenVINO™:
|
||||
|
||||
## System Requirements
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-linux.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
|
||||
* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Operating Systems
|
||||
|
||||
* Ubuntu 18.04 long-term support (LTS), 64-bit
|
||||
* Ubuntu 20.04 long-term support (LTS), 64-bit
|
||||
|
||||
.. note::
|
||||
Since the OpenVINO™ 2022.1 release, CentOS 7.6, 64-bit is not longer supported.
|
||||
|
||||
.. tab:: Hardware
|
||||
|
||||
Optimized for these processors:
|
||||
|
||||
* 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
|
||||
* 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
|
||||
* Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
|
||||
* Intel Atom® processor with support for Intel® Streaming SIMD Extensions 4.1 (Intel® SSE4.1)
|
||||
* Intel Pentium® processor N4200/5, N3350/5, or N3450/5 with Intel® HD Graphics
|
||||
* Intel® Iris® Xe MAX Graphics
|
||||
* Intel® Neural Compute Stick 2
|
||||
* Intel® Vision Accelerator Design with Intel® Movidius™ VPUs
|
||||
|
||||
.. tab:: Processor Notes
|
||||
|
||||
Processor graphics are not included in all processors.
|
||||
See `Product Specifications`_ for information about your processor.
|
||||
|
||||
.. _Product Specifications: https://ark.intel.com/
|
||||
|
||||
.. tab:: Software
|
||||
|
||||
* `CMake 3.13 or higher, 64-bit <https://cmake.org/download/>`_
|
||||
* GCC 7.5.0 (for Ubuntu 18.04) or GCC 9.3.0 (for Ubuntu 20.04)
|
||||
* `Python 3.6 - 3.10, 64-bit <https://www.python.org/downloads/windows/>`_
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Overview
|
||||
|
||||
This guide provides step-by-step instructions on how to install the Intel® Distribution of OpenVINO™ toolkit. Links are provided for each type of compatible hardware including downloads, initialization and configuration steps. The following steps will be covered:
|
||||
|
||||
1. <a href="#install-openvino">Install the Intel® Distribution of OpenVINO™ Toolkit</a>
|
||||
2. <a href="#install-external-dependencies">Install External Software Dependencies</a>
|
||||
3. <a href="#set-the-environment-variables">Configure the Environment</a>
|
||||
4. <a href="#model-optimizer">Download additional components (Optional)</a>
|
||||
5. <a href="#optional-steps">Configure Inference on non-CPU Devices (Optional)</a>
|
||||
6. <a href="#get-started">What's next?</a>
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. important::
|
||||
Before you start your journey with installation of the Intel® Distribution of OpenVINO™, we encourage you to check our :ref:`code samples <code samples>` in C, C++, Python and :ref:`notebook tutorials <notebook tutorials>` that we prepared for you, so you could see all the amazing things that you can achieve with our tool.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="install-openvino"></a>Step 1: Install the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
1. Select and download the Intel® Distribution of OpenVINO™ toolkit installer file from [Intel® Distribution of OpenVINO™ toolkit for Linux](https://software.intel.com/en-us/openvino-toolkit/choose-download).
|
||||
2. Open a command prompt terminal window. You can use the keyboard shortcut: Ctrl+Alt+T
|
||||
3. Change directories to where you downloaded the Intel Distribution of OpenVINO™ toolkit for Linux file.<br>
|
||||
If you downloaded the starter script to the current user's `Downloads` directory:
|
||||
```sh
|
||||
cd ~/Downloads/
|
||||
```
|
||||
You should find there a bootstrapper script `l_openvino_toolkit_p_<version>.sh`.
|
||||
4. Add executable rights for the current user:
|
||||
```sh
|
||||
chmod +x l_openvino_toolkit_p_<version>.sh
|
||||
```
|
||||
5. If you want to use graphical user interface (GUI) installation wizard, run the script without any parameters:
|
||||
```sh
|
||||
./l_openvino_toolkit_p_<version>.sh
|
||||
```
|
||||
<br>You should see the following dialog box open up:
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. image:: _static/images/openvino-install.png
|
||||
:width: 400px
|
||||
:align: center
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
Otherwise, you can add parameters `-a` for additional arguments and `--cli` to run installation in command line (CLI):
|
||||
```sh
|
||||
./l_openvino_toolkit_p_<version>.sh -a --cli
|
||||
```
|
||||
> **NOTE**: To get additional information on all parameters that can be used, use the help option: `--help`. Among others, you can find there `-s` option which offers silent mode, which together with `--eula approve` allows you to run whole installation with default values without any user inference.
|
||||
|
||||
6. Follow the instructions on your screen. During the installation you will be asked to accept the license agreement. Your acceptance is required to continue. Check the installation process on the image below:<br>
|
||||
|
||||
|
||||
Click on the image to see the details.
|
||||
<br>
|
||||
<br>By default, the Intel® Distribution of OpenVINO™ is installed to the following directory, referred to as `<INSTALL_DIR>` elsewhere in the documentation:
|
||||
* For root or administrator: `/opt/intel/openvino_<version>/`
|
||||
* For regular users: `/home/<USER>/intel/openvino_<version>/`
|
||||
|
||||
<br>For simplicity, a symbolic link to the latest installation is also created: `/opt/intel/openvino_2022/` or `/home/<USER>/intel/openvino_2022/`.
|
||||
|
||||
To check **Release Notes** please visit: [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes).
|
||||
|
||||
The core components are now installed. Continue to the next section to install additional dependencies.
|
||||
|
||||
## <a name="install-external-dependencies"></a>Step 2: Install External Software Dependencies
|
||||
|
||||
This script enables you to install Linux platform development tools and components to work with the product.
|
||||
|
||||
1. Go to the `install_dependencies` directory:
|
||||
```sh
|
||||
cd <INSTALL_DIR>/install_dependencies
|
||||
```
|
||||
2. Run a script to download and install the external software dependencies:
|
||||
```sh
|
||||
sudo -E ./install_openvino_dependencies.sh
|
||||
```
|
||||
|
||||
Once the dependencies are installed, continue to the next section to set your environment variables.
|
||||
|
||||
## <a name="set-the-environment-variables"></a>Step 3: Configure the Environment
|
||||
|
||||
You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:
|
||||
|
||||
```sh
|
||||
source <INSTALL_DIR>/setupvars.sh
|
||||
```
|
||||
|
||||
If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
|
||||
|
||||
> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.
|
||||
|
||||
The environment variables are set. Next, you can download some additional tools.
|
||||
|
||||
## <a name="model-optimizer">Step 4 (Optional): Download Additional Components
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: OpenCV
|
||||
|
||||
OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. The Intel® Distribution of OpenVINO™ provides a script to install OpenCV: ``<INSTALL_DIR>/extras/scripts/download_opencv.sh``.
|
||||
|
||||
.. note::
|
||||
Make sure you have 2 prerequisites installed: ``curl`` and ``tar``.
|
||||
|
||||
Depending on how you have installed the Intel® Distribution of OpenVINO™, the script should be run either as root or regular user. After the execution of the script, you will find OpenCV extracted to ``<INSTALL_DIR>/extras/opencv``.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="optional-steps"></a>Step 5 (Optional): Configure Inference on Non-CPU Devices
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: GNA
|
||||
|
||||
To enable the toolkit components to use Intel® Gaussian & Neural Accelerator (GNA) on your system, follow the steps in :ref:`GNA Setup Guide <gna guide>`.
|
||||
|
||||
.. tab:: GPU
|
||||
|
||||
To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:`GPU Setup Guide <gpu guide>`.
|
||||
|
||||
.. tab:: NCS 2
|
||||
|
||||
To perform inference on Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X VPU, follow the steps on :ref:`NCS2 Setup Guide <ncs guide>`.
|
||||
<!--For more details, see the `Get Started page for Intel® Neural Compute Stick 2 <https://software.intel.com/en-us/neural-compute-stick/get-started>`.-->
|
||||
|
||||
.. tab:: VPU
|
||||
|
||||
To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:`VPU Configuration Guide <vpu guide>`.
|
||||
After configuration is done, you are ready to run the verification scripts with the HDDL Plugin for your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
|
||||
|
||||
.. warning::
|
||||
While working with either HDDL or NCS, choose one of them as they cannot run simultaneously on the same machine.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="get-started"></a>Step 6: What's Next?
|
||||
|
||||
Now you are ready to try out the toolkit.
|
||||
|
||||
Developing in Python:
|
||||
* [Start with TensorFlow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
|
||||
* [Start with ONNX and PyTorch models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/102-pytorch-onnx-to-openvino-with-output.html)
|
||||
* [Start with PaddlePaddle models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html)
|
||||
|
||||
Developing in C++:
|
||||
* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
|
||||
* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
|
||||
* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
|
||||
|
||||
## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
|
||||
|
||||
## Additional Resources
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
* :ref:`Troubleshooting Guide for OpenVINO Installation & Configuration <troubleshooting guide for install>`
|
||||
* Converting models for use with OpenVINO™: :ref:`Model Optimizer User Guide <deep learning model optimizer>`
|
||||
* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
|
||||
* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
|
||||
* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
|
||||
* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
|
||||
|
||||
.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
|
||||
|
||||
@endsphinxdirective
|
||||
The other installation methods are temporarily unavailable.
|
||||
|
|
|
|||
|
|
@ -6,14 +6,12 @@
|
|||
:maxdepth: 3
|
||||
:hidden:
|
||||
|
||||
Using Installer <openvino_docs_install_guides_installing_openvino_macos>
|
||||
From Archive <openvino_docs_install_guides_installing_openvino_from_archive_macos>
|
||||
From PyPI <openvino_docs_install_guides_installing_openvino_pip>
|
||||
From Anaconda Cloud <openvino_docs_install_guides_installing_openvino_conda>
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
If you want to install Intel® Distribution of OpenVINO™ toolkit on macOS, there are a few ways to accomplish this. We prepared following options for you:
|
||||
|
||||
* [Install OpenVINO Runtime using an Installer](installing-openvino-macos.md)
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-macos.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO Runtime from Anaconda Cloud](installing-openvino-conda.md)
|
||||
|
|
|
|||
|
|
@ -1,161 +1,9 @@
|
|||
# Install and Configure Intel® Distribution of OpenVINO™ toolkit for macOS {#openvino_docs_install_guides_installing_openvino_macos}
|
||||
# Install Intel® Distribution of OpenVINO™ toolkit for macOS from Installer
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. These tools are now only available on [pypi.org](https://pypi.org/project/openvino-dev/).
|
||||
Currently only the following ways are provided to install OpenVINO™:
|
||||
|
||||
> **NOTE**: The Intel® Distribution of OpenVINO™ toolkit is supported on macOS version 10.15 with Intel® processor-based machines.
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-macos.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
|
||||
|
||||
## System Requirements
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Operating Systems
|
||||
|
||||
macOS 10.15
|
||||
|
||||
.. tab:: Hardware
|
||||
|
||||
Optimized for these processors:
|
||||
|
||||
* 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
|
||||
* 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
|
||||
* Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
|
||||
* Intel® Neural Compute Stick 2
|
||||
|
||||
.. note::
|
||||
The current version of the Intel® Distribution of OpenVINO™ toolkit for macOS supports inference on Intel CPUs and Intel® Neural Compute Stick 2 devices only.
|
||||
|
||||
.. tab:: Software Requirements
|
||||
|
||||
* `CMake 3.13 or higher <https://cmake.org/download/>`_ (choose "macOS 10.13 or later"). Add `/Applications/CMake.app/Contents/bin` to path (for default install).
|
||||
* `Python 3.6 - 3.10 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.6 - 3.10). Install and add to path.
|
||||
* Apple Xcode Command Line Tools. In the terminal, run `xcode-select --install` from any directory
|
||||
* (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Overview
|
||||
|
||||
This guide provides step-by-step instructions on how to install the Intel® Distribution of OpenVINO™ toolkit for macOS. The following steps will be covered:
|
||||
|
||||
1. <a href="#install-core">Install the Intel® Distribution of OpenVINO™ Toolkit</a>
|
||||
2. <a href="#set-the-environment-variables">Configure the Environment</a>
|
||||
3. <a href="#model-optimizer">Download additional components (Optional)</a>
|
||||
4. <a href="#configure-ncs2">Configure the Intel® Neural Compute Stick 2 (Optional)</a>
|
||||
5. <a href="#get-started">What’s next?</a>
|
||||
|
||||
## <a name="install-core"></a>Step 1: Install the Intel® Distribution of OpenVINO™ Toolkit Core Components
|
||||
|
||||
1. Download the Intel® Distribution of OpenVINO™ toolkit package file from [Intel® Distribution of OpenVINO™ toolkit for macOS](https://software.intel.com/en-us/openvino-toolkit/choose-download/free-download-macos). Select the Intel® Distribution of OpenVINO™ toolkit for macOS package from the dropdown menu.
|
||||
|
||||
2. Go to the directory where you downloaded the Intel® Distribution of OpenVINO™ toolkit. This document assumes this is your `Downloads` directory. By default, the disk image file is saved as `m_openvino_toolkit_p_<version>.dmg`.
|
||||
|
||||
3. Double-click the `m_openvino_toolkit_p_<version>.dmg` file to mount. The disk image is mounted to `/Volumes/m_openvino_toolkit_p_<version>` and automatically opens in a separate window.
|
||||
|
||||
4. Run the installation wizard application `bootstrapper.app`. You should see the following dialog box open up:
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. image:: _static/images/openvino-install.png
|
||||
:width: 400px
|
||||
:align: center
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
5. Follow the instructions on your screen. During the installation you will be asked to accept the license agreement. Your acceptance is required to continue.
|
||||
|
||||
Click on the image to see the details.
|
||||
|
||||
By default, the Intel® Distribution of OpenVINO™ is installed in the following directory, referred to as `<INSTALL_DIR>` elsewhere in the documentation:
|
||||
|
||||
`/opt/intel/openvino_<version>/`
|
||||
|
||||
For simplicity, a symbolic link to the latest installation is also created: `/opt/intel/openvino_2022/`.
|
||||
|
||||
To check **Release Notes** please visit: [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes).
|
||||
|
||||
The core components are now installed. Continue to the next section to configure environment.
|
||||
|
||||
## <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
|
||||
|
||||
You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:
|
||||
|
||||
```sh
|
||||
source <INSTALL_DIR>/setupvars.sh
|
||||
```
|
||||
|
||||
If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
|
||||
|
||||
> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.
|
||||
|
||||
The environment variables are set. Continue to the next section if you want to download any additional components.
|
||||
|
||||
## <a name="model-optimizer"></a>Step 3 (Optional): Download Additional Components
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: OpenCV
|
||||
|
||||
OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. The Intel® Distribution of OpenVINO™ provides a script to install OpenCV: ``<INSTALL_DIR>/extras/scripts/download_opencv.sh``.
|
||||
|
||||
.. note::
|
||||
Make sure you have 2 prerequisites installed: ``curl`` and ``tar``.
|
||||
|
||||
Depending on how you have installed the Intel® Distribution of OpenVINO™, the script should be run either as root or regular user. After the execution of the script, you will find OpenCV extracted to ``<INSTALL_DIR>/extras/opencv``.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="configure-ncs2"></a>Step 4 (Optional): Configure the Intel® Neural Compute Stick 2
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
If you want to run inference on Intel® Neural Compute Stick 2 use the following instructions to setup the device: :ref:`NCS2 Setup Guide <ncs guide macos>`.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="get-started"></a>Step 5: What's next?
|
||||
|
||||
Now you are ready to try out the toolkit. You can use the following tutorials to write your applications using Python and C++.
|
||||
|
||||
Developing in Python:
|
||||
* [Start with tensorflow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
|
||||
* [Start with ONNX and PyTorch models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/102-pytorch-onnx-to-openvino-with-output.html)
|
||||
* [Start with PaddlePaddle models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html)
|
||||
|
||||
Developing in C++:
|
||||
* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
|
||||
* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
|
||||
* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
|
||||
|
||||
## <a name="uninstall"></a>Uninstall the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
|
||||
|
||||
@sphinxdirective
|
||||
.. raw:: html
|
||||
|
||||
</div>
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: Additional Resources
|
||||
|
||||
* Converting models for use with OpenVINO™: :ref:`Model Optimizer Developer Guide <deep learning model optimizer>`
|
||||
* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
|
||||
* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
|
||||
* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
|
||||
* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
|
||||
|
||||
<!---
|
||||
To learn more about converting models from specific frameworks, go to:
|
||||
* :ref:`Convert Your Caffe Model <convert model caffe>`
|
||||
* :ref:`Convert Your TensorFlow Model <convert model tf>`
|
||||
* :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
|
||||
* :ref:`Convert Your Kaldi Model <convert model kaldi>`
|
||||
* :ref:`Convert Your ONNX Model <convert model onnx>`
|
||||
--->
|
||||
.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
|
||||
|
||||
@endsphinxdirective
|
||||
The other installation methods are temporarily unavailable.
|
||||
|
|
|
|||
|
|
@ -42,9 +42,9 @@ For Python developers, the easiest way is to [install OpenVINO Development Tools
|
|||
|
||||
For C++ developers, you may choose one of the following installation options for OpenVINO Runtime on your specific operating system:
|
||||
|
||||
* Linux: You can install OpenVINO Runtime using an [Installer](installing-openvino-linux.md), [APT](installing-openvino-apt.md), [YUM](installing-openvino-yum.md), [Anaconda Cloud](installing-openvino-conda.md), or [Docker](installing-openvino-docker-linux.md).
|
||||
* Windows: You can install OpenVINO Runtime using an [Installer](installing-openvino-windows.md), [Anaconda Cloud](installing-openvino-conda.md), or [Docker](installing-openvino-docker-windows.md).
|
||||
* macOS: You can install OpenVINO Runtime using an [Installer](installing-openvino-macos.md) or [Anaconda Cloud](installing-openvino-conda.md).
|
||||
* Linux: You can install OpenVINO Runtime using archive files or Docker. See [Install OpenVINO on Linux](installing-openvino-linux-header.md).
|
||||
* Windows: You can install OpenVINO Runtime using archive files or Docker. See [Install OpenVINO on Windows](installing-openvino-windows-header.md).
|
||||
* macOS: You can install OpenVINO Runtime using archive files or Docker. See [Install OpenVINO on macOS](installing-openvino-macos-header.md).
|
||||
* [Raspbian OS](installing-openvino-raspbian.md).
|
||||
|
||||
> **NOTE**: With the introduction of the 2022.1 release, the OpenVINO Development Tools can be installed **only** via PyPI. See [Install OpenVINO Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
|
|
|||
|
|
@ -6,16 +6,14 @@
|
|||
:maxdepth: 3
|
||||
:hidden:
|
||||
|
||||
Using Installer <openvino_docs_install_guides_installing_openvino_windows>
|
||||
From Archive <openvino_docs_install_guides_installing_openvino_from_archive_windows>
|
||||
From PyPI <openvino_docs_install_guides_installing_openvino_pip>
|
||||
From Anaconda Cloud <openvino_docs_install_guides_installing_openvino_conda>
|
||||
Using Docker <openvino_docs_install_guides_installing_openvino_docker_windows>
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
If you want to install Intel® Distribution of OpenVINO™ toolkit on Windows, you have the following options:
|
||||
|
||||
* [Install OpenVINO Runtime using an installer](installing-openvino-windows.md)
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-windows.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO Runtime from Anaconda Cloud](installing-openvino-conda.md)
|
||||
* [Install OpenVINO with Docker](installing-openvino-docker-windows.md)
|
||||
|
|
|
|||
|
|
@ -1,198 +1,11 @@
|
|||
# Install and Configure Intel® Distribution of OpenVINO™ toolkit for Windows 10 {#openvino_docs_install_guides_installing_openvino_windows}
|
||||
# Install Intel® Distribution of OpenVINO™ toolkit for Windows 10 from Installer
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. These tools are now only available on [pypi.org](https://pypi.org/project/openvino-dev/).
|
||||
Currently only the following ways are provided to install OpenVINO™:
|
||||
|
||||
## System Requirements
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-windows.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO with Docker](installing-openvino-docker-windows.md)
|
||||
* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Operating Systems
|
||||
The other installation methods are temporarily unavailable.
|
||||
|
||||
Microsoft Windows 10, 64-bit
|
||||
|
||||
.. tab:: Hardware
|
||||
|
||||
Optimized for these processors:
|
||||
|
||||
* 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
|
||||
* 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
|
||||
* Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
|
||||
* Intel Atom® processor with support for Intel® Streaming SIMD Extensions 4.1 (Intel® SSE4.1)
|
||||
* Intel Pentium® processor N4200/5, N3350/5, or N3450/5 with Intel® HD Graphics
|
||||
* Intel® Iris® Xe MAX Graphics
|
||||
* Intel® Neural Compute Stick 2
|
||||
* Intel® Vision Accelerator Design with Intel® Movidius™ VPUs
|
||||
|
||||
.. tab:: Processor Notes
|
||||
|
||||
Processor graphics are not included in all processors.
|
||||
See `Product Specifications`_ for information about your processor.
|
||||
|
||||
.. _Product Specifications: https://ark.intel.com/
|
||||
|
||||
.. tab:: Software
|
||||
|
||||
* `Microsoft Visual Studio 2019 with MSBuild <http://visualstudio.microsoft.com/downloads/>`_
|
||||
* `CMake 3.14 or higher, 64-bit <https://cmake.org/download/>`_
|
||||
* `Python 3.6 - 3.10, 64-bit <https://www.python.org/downloads/windows/>`_
|
||||
|
||||
.. note::
|
||||
You can choose to download Community version. Use `Microsoft Visual Studio installation guide <https://docs.microsoft.com/en-us/visualstudio/install/install-visual-studio?view=vs-2019>`_ to walk you through the installation. During installation in the **Workloads** tab, choose **Desktop development with C++**.
|
||||
|
||||
.. note::
|
||||
You can either use `cmake<version>.msi` which is the installation wizard or `cmake<version>.zip` where you have to go into the `bin` folder and then manually add the path to environmental variables.
|
||||
|
||||
.. important::
|
||||
As part of this installation, make sure you click the option **Add Python 3.x to PATH** to `add Python <https://docs.python.org/3/using/windows.html#installation-steps>`_ to your `PATH` environment variable.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Overview
|
||||
|
||||
This guide provides step-by-step instructions on how to install the Intel® Distribution of OpenVINO™ toolkit. Links are provided for each type of compatible hardware including downloads, initialization and configuration steps. The following steps will be covered:
|
||||
|
||||
1. <a href="#install-openvino">Install the Intel® Distribution of OpenVINO™ Toolkit</a>
|
||||
2. <a href="#set-the-environment-variables">Configure the Environment</a>
|
||||
3. <a href="#model-optimizer">Download additional components (Optional)</a>
|
||||
4. <a href="#optional-steps">Configure Inference on non-CPU Devices (Optional)</a>
|
||||
5. <a href="#get-started">What's next?</a>
|
||||
|
||||
## <a name="install-openvino"></a>Step 1: Install the Intel® Distribution of OpenVINO™ toolkit Core Components
|
||||
|
||||
1. Download the Intel® Distribution of OpenVINO™ toolkit package file from [Intel® Distribution of OpenVINO™ toolkit for Windows](https://software.intel.com/en-us/openvino-toolkit/choose-download).
|
||||
Select the Intel® Distribution of OpenVINO™ toolkit for Windows package from the dropdown menu.
|
||||
|
||||
2. Go to the `Downloads` folder and double-click `w_openvino_toolkit_p_<version>.exe`. In the opened window, you can select the folder where installer files will be placed. The directory will be referred to as <INSTALL_DIR> elsewhere in the documentation. Once the files are extracted, you should see the following dialog box open up:
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. image:: _static/images/openvino-install.png
|
||||
:width: 400px
|
||||
:align: center
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
3. Follow the instructions on your screen. During the installation you will be asked to accept the license agreement. Your acceptance is required to continue. Check out the installation process in the image below:<br>
|
||||
|
||||
Click on the image to see the details.
|
||||
<br>
|
||||
<br>By default, the Intel® Distribution of OpenVINO™ is installed to the following directory, referred to as `<INSTALL_DIR>` elsewhere in the documentation: `C:\Program Files (x86)\Intel\openvino_<version>/`.
|
||||
|
||||
<br>For simplicity, a symbolic link to the latest installation is also created: `C:\Program Files (x86)\Intel\openvino_2022/`.
|
||||
|
||||
To check **Release Notes** please visit: [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes).
|
||||
|
||||
The core components are now installed. Continue to the next section to configure environment.
|
||||
|
||||
## <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
|
||||
|
||||
> **NOTE**: If you installed the Intel® Distribution of OpenVINO™ to a non-default install directory, replace `C:\Program Files (x86)\Intel` with that directory in this guide's instructions.
|
||||
|
||||
You must update several environment variables before you can compile and run OpenVINO™ applications. Open the Command Prompt, and run the `setupvars.bat` batch file to temporarily set your environment variables:
|
||||
|
||||
```sh
|
||||
"<INSTALL_DIR>\setupvars.bat"
|
||||
```
|
||||
|
||||
**Optional**: OpenVINO™ toolkit environment variables are removed when you close the command prompt window. You can permanently set the environment variables manually.
|
||||
|
||||
> **NOTE**: If you see an error indicating Python is not installed when you know you installed it, your computer might not be able to find the program. Check your system environment variables, and add Python if necessary.
|
||||
|
||||
The environment variables are set. Next, you can download some additional tools.
|
||||
|
||||
## <a name="model-optimizer">Step 3 (Optional): Download Additional Components</a>
|
||||
|
||||
> **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: OpenCV
|
||||
|
||||
OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. The Intel® Distribution of OpenVINO™ provides a script to install OpenCV: ``<INSTALL_DIR>\extras\scripts\download_opencv.ps1``.
|
||||
|
||||
.. note::
|
||||
No prerequisites are needed.
|
||||
|
||||
There are three ways to run the script:
|
||||
|
||||
* GUI: right-click the script and select ``Run with PowerShell``.
|
||||
|
||||
* Command prompt (CMD) console:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
powershell <INSTALL_DIR>\extras\scripts\download_opencv.ps1
|
||||
|
||||
|
||||
* PowerShell console:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
.\<INSTALL_DIR>\extras\scripts\download_opencv.ps1
|
||||
|
||||
|
||||
If the Intel® Distribution of OpenVINO™ is installed to the system location (e.g. ``Program Files (x86)``) then privilege elevation dialog will be shown. The script can be run from CMD/PowerShell Administrator console to avoid this dialog in case of system-wide installation.
|
||||
The script is interactive by default, so during the execution it will wait for user to press ``Enter`` If you want to avoid this, use the ``-batch`` option, e.g. ``powershell <INSTALL_DIR>\extras\scripts\download_opencv.ps1 -batch``. After the execution of the script, you will find OpenCV extracted to ``<INSTALL_DIR>/extras/opencv``.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="optional-steps"></a>Step 4 (Optional): Configure Inference on non-CPU Devices
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: GNA
|
||||
|
||||
To enable the toolkit components to use Intel® Gaussian & Neural Accelerator (GNA) on your system, follow the steps in :ref:`GNA Setup Guide <gna guide windows>`.
|
||||
|
||||
.. tab:: GPU
|
||||
|
||||
To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:`GPU Setup Guide <gpu guide windows>`.
|
||||
|
||||
.. tab:: VPU
|
||||
|
||||
To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:`VPU Configuration Guide <vpu guide windows>`.
|
||||
|
||||
.. tab:: NCS 2
|
||||
|
||||
No additional configurations are needed.
|
||||
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## <a name="get-started"></a>Step 5: What's next?
|
||||
|
||||
Now you are ready to try out the toolkit.
|
||||
|
||||
Developing in Python:
|
||||
* [Start with tensorflow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
|
||||
* [Start with ONNX and PyTorch models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/102-pytorch-onnx-to-openvino-with-output.html)
|
||||
* [Start with PaddlePaddle models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html)
|
||||
|
||||
Developing in C++:
|
||||
* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
|
||||
* [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
|
||||
* [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
|
||||
|
||||
## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
|
||||
|
||||
To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. dropdown:: Additional Resources
|
||||
|
||||
* Converting models for use with OpenVINO™: :ref:`Model Optimizer Developer Guide <deep learning model optimizer>`
|
||||
* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
|
||||
* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
|
||||
* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
|
||||
* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
|
||||
|
||||
<!---
|
||||
To learn more about converting models from specific frameworks, go to:
|
||||
* :ref:`Convert Your Caffe Model <convert model caffe>`
|
||||
* :ref:`Convert Your TensorFlow Model <convert model tf>`
|
||||
* :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
|
||||
* :ref:`Convert Your Kaldi Model <convert model kaldi>`
|
||||
* :ref:`Convert Your ONNX Model <convert model onnx>`
|
||||
--->
|
||||
.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
|
||||
|
||||
@endsphinxdirective
|
||||
|
|
|
|||
|
|
@ -1,178 +1,10 @@
|
|||
# Install Intel® Distribution of OpenVINO™ Toolkit for Linux Using YUM Repository {#openvino_docs_install_guides_installing_openvino_yum}
|
||||
# Install Intel® Distribution of OpenVINO™ Toolkit for Linux Using YUM Repository
|
||||
|
||||
This guide provides installation steps for Intel® Distribution of OpenVINO™ toolkit for Linux distributed through the YUM repository.
|
||||
Currently only the following ways are provided to install OpenVINO™:
|
||||
|
||||
> **NOTE**: From the 2022.1 release, the OpenVINO™ Development Tools can only be installed via PyPI. If you want to develop or optimize your models with OpenVINO, see [Install OpenVINO Development Tools](installing-model-dev-tools.md) for detailed steps.
|
||||
* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-linux.md)
|
||||
* [Install OpenVINO from PyPI](installing-openvino-pip.md)
|
||||
* [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
|
||||
* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
|
||||
|
||||
> **IMPORTANT**: By downloading and using this container and the included software, you agree to the terms and conditions of the [software license agreements](https://software.intel.com/content/dam/develop/external/us/en/documents/intel-openvino-license-agreements.pdf). Please review the content inside the `<INSTALL_DIR>/licensing` folder for more details.
|
||||
|
||||
## System Requirements
|
||||
|
||||
The complete list of supported hardware is available in the [Release Notes](https://software.intel.com/content/www/us/en/develop/articles/openvino-relnotes.html).
|
||||
|
||||
**Operating systems**
|
||||
|
||||
- Red Hat Enterprise Linux 8, 64-bit
|
||||
|
||||
**Software**
|
||||
|
||||
- [CMake 3.13 or higher, 64-bit](https://cmake.org/download/)
|
||||
- GCC 8.2.0
|
||||
- [Python 3.6 - 3.10, 64-bit](https://www.python.org/downloads/windows/)
|
||||
|
||||
## Install OpenVINO Runtime
|
||||
|
||||
### Step 1: Set Up the Repository
|
||||
|
||||
1. Create the YUM repo file in the `/tmp` directory as a normal user:
|
||||
```
|
||||
tee > /tmp/openvino-2022.repo << EOF
|
||||
[OpenVINO]
|
||||
name=Intel(R) Distribution of OpenVINO 2022
|
||||
baseurl=https://yum.repos.intel.com/openvino/2022
|
||||
enabled=1
|
||||
gpgcheck=1
|
||||
repo_gpgcheck=1
|
||||
gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
|
||||
EOF
|
||||
```
|
||||
2. Move the new openvino-2022.repo file to the YUM configuration directory `/etc/yum.repos.d`:
|
||||
```sh
|
||||
sudo mv /tmp/openvino-2022.repo /etc/yum.repos.d
|
||||
```
|
||||
3. Verify that the new repo is properly setup by running the following command:
|
||||
```sh
|
||||
yum repolist | grep -i openvino
|
||||
```
|
||||
You will see the available list of packages.
|
||||
|
||||
|
||||
To list available OpenVINO packages, use the following command:
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
yum list 'openvino*'
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
### Step 2: Install OpenVINO Runtime Using the YUM Package Manager
|
||||
|
||||
Intel® Distribution of OpenVINO™ toolkit will be installed in: `/opt/intel/openvino_<VERSION>.<UPDATE>.<PATCH>`
|
||||
|
||||
A symlink will be created: `/opt/intel/openvino_<VERSION>`
|
||||
|
||||
You can select one of the following procedures according to your need:
|
||||
|
||||
#### To Install the Latest Version
|
||||
|
||||
Run the following command:
|
||||
```sh
|
||||
sudo yum install openvino
|
||||
```
|
||||
|
||||
#### To Install a Specific Version
|
||||
|
||||
Run the following command:
|
||||
```sh
|
||||
sudo yum install openvino-<VERSION>.<UPDATE>.<PATCH>
|
||||
```
|
||||
|
||||
For example:
|
||||
```sh
|
||||
sudo yum install openvino-2022.1.0
|
||||
```
|
||||
|
||||
#### To Check for Installed Packages and Version
|
||||
|
||||
Run the following command:
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
yum list installed 'openvino*'
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
#### To Uninstall the Latest Version
|
||||
|
||||
Run the following command:
|
||||
```sh
|
||||
sudo yum autoremove openvino
|
||||
```
|
||||
|
||||
#### To Uninstall a Specific Version
|
||||
|
||||
Run the following command:
|
||||
```sh
|
||||
sudo yum autoremove openvino-<VERSION>.<UPDATE>.<PATCH>
|
||||
```
|
||||
|
||||
### Step 3 (Optional): Install OpenCV from YUM
|
||||
|
||||
OpenCV is necessary to run C++ demos from Open Model Zoo. Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. OpenVINO provides a package to install OpenCV from YUM:
|
||||
|
||||
#### To Install the Latest Version of OpenCV
|
||||
|
||||
Run the following command:
|
||||
```sh
|
||||
sudo yum install openvino-opencv
|
||||
```
|
||||
|
||||
#### To Install a Specific Version of OpenCV
|
||||
|
||||
Run the following command:
|
||||
```sh
|
||||
sudo yum install openvino-opencv-<VERSION>.<UPDATE>.<PATCH>
|
||||
```
|
||||
|
||||
### Step 4 (Optional): Install Software Dependencies
|
||||
|
||||
After you have installed OpenVINO Runtime, if you decided to [install OpenVINO Model Development Tools](installing-model-dev-tools.md), make sure that you install external software dependencies first.
|
||||
|
||||
Refer to <a href="openvino_docs_install_guides_installing_openvino_linux.html#install-external-dependencies">Install External Software Dependencies</a> for detailed steps.
|
||||
|
||||
### Step 5 (Optional): Configure Inference on Non-CPU Devices
|
||||
|
||||
@sphinxdirective
|
||||
|
||||
.. tab:: GNA
|
||||
|
||||
To enable the toolkit components to use Intel® Gaussian & Neural Accelerator (GNA) on your system, follow the steps in :ref:`GNA Setup Guide <gna guide>`.
|
||||
|
||||
.. tab:: GPU
|
||||
|
||||
To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:`GPU Setup Guide <gpu guide>`.
|
||||
|
||||
.. tab:: NCS 2
|
||||
|
||||
To perform inference on Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X VPU, follow the steps on :ref:`NCS2 Setup Guide <ncs guide>`.
|
||||
<!--For more details, see the `Get Started page for Intel® Neural Compute Stick 2 <https://software.intel.com/en-us/neural-compute-stick/get-started>`.-->
|
||||
|
||||
.. tab:: VPU
|
||||
|
||||
To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:`VPU Configuration Guide <vpu guide>`.
|
||||
After configuration is done, you are ready to run the verification scripts with the HDDL Plugin for your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
|
||||
|
||||
.. warning::
|
||||
While working with either HDDL or NCS, choose one of them as they cannot run simultaneously on the same machine.
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
|
||||
## What's Next?
|
||||
|
||||
Now you may continue with the following tasks:
|
||||
|
||||
* To convert models for use with OpenVINO, see [Model Optimizer Developer Guide](../MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md).
|
||||
* See pre-trained deep learning models in our [Open Model Zoo](../model_zoo.md).
|
||||
* Try out OpenVINO via [OpenVINO Notebooks](https://docs.openvino.ai/latest/notebooks/notebooks.html).
|
||||
* To write your own OpenVINO™ applications, see [OpenVINO Runtime User Guide](../OV_Runtime_UG/openvino_intro.md).
|
||||
* See sample applications in [OpenVINO™ Toolkit Samples Overview](../OV_Runtime_UG/Samples_Overview.md).
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- Intel® Distribution of OpenVINO™ toolkit home page: <https://software.intel.com/en-us/openvino-toolkit>
|
||||
- For IoT Libraries & Code Samples, see [Intel® IoT Developer Kit](https://github.com/intel-iot-devkit).
|
||||
The other installation methods are temporarily unavailable.
|
||||
|
|
|
|||
|
|
@ -32,11 +32,11 @@ python -m pip install --upgrade pip
|
|||
<!--add this part in future-->
|
||||
|
||||
|
||||
## Check if required external dependencies are installed
|
||||
## Check if required external dependencies are installed (for pre-2022.2 releases)
|
||||
|
||||
For Ubuntu and RHEL 8 systems, if you installed OpenVINO Runtime via the installer, APT, or YUM repository, and decided to [install OpenVINO Development Tools](installing-model-dev-tools.md), make sure that you <a href="openvino_docs_install_guides_installing_openvino_linux.html#install-external-dependencies">Install External Software Dependencies</a> first.
|
||||
|
||||
For C++ developers with Windows systems, make sure that Microsoft Visual Studio 2019 with MSBuild and CMake 3.14 or higher (64-bit) are installed. While installing Microsoft Visual Studio 2019, make sure that you have selected **Desktop development with C++** in the **Workloads** tab. If not, launch the installer again to select that option. For more information on modifying the installation options for Microsoft Visual Studio, see its [official support page](https://docs.microsoft.com/en-us/visualstudio/install/modify-visual-studio?view=vs-2019).
|
||||
For OpenVINO releases prior to 2022.2:
|
||||
- If you are using Ubuntu or RHEL 8 systems, and installed OpenVINO Runtime via the installer, APT, or YUM repository, and then decided to [install OpenVINO Development Tools](installing-model-dev-tools.md), make sure that you **Install External Software Dependencies** first by following the steps in the corresponding installation pages.
|
||||
- For C++ developers with Windows systems, make sure that Microsoft Visual Studio 2019 with MSBuild and CMake 3.14 or higher (64-bit) are installed. While installing Microsoft Visual Studio 2019, make sure that you have selected **Desktop development with C++** in the **Workloads** tab. If not, launch the installer again to select that option. For more information on modifying the installation options for Microsoft Visual Studio, see its [official support page](https://docs.microsoft.com/en-us/visualstudio/install/modify-visual-studio?view=vs-2019).
|
||||
|
||||
## Check if environment variables are set correctly
|
||||
|
||||
|
|
|
|||
|
|
@ -4,112 +4,36 @@
|
|||
|
||||
## Uninstall Using the Original Installation Package
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Windows
|
||||
|
||||
Use initial bootstrapper file ``w_openvino_toolkit_p_<version>.exe`` to select product for uninstallation. Follow the wizard instructions. Select **Remove** option when presented. If you have more product versions installed, you can select one from a drop-down menu in GUI.
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-dropdown-win.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
|
||||
.. tab:: Linux
|
||||
|
||||
If you want to use graphical user interface (GUI) installation wizard, run the script without any parameters:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
./l_openvino_toolkit_p_<version>.sh
|
||||
|
||||
Follow the wizard instructions.
|
||||
|
||||
Otherwise, you can add parameters `-a` for additional arguments and `--cli` to run installation in command line (CLI):
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
./l_openvino_toolkit_p_<version>.sh -a --cli
|
||||
|
||||
Follow the wizard. Select **Remove** option when presented. If you have more product versions installed, you can select one from a drop-down menu in GUI and from a list in CLI.
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-dropdown-linux.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
|
||||
.. tab:: macOS
|
||||
|
||||
Use initial bootstrapper file ``m_openvino_toolkit_p_<version>.dmg`` to select product for uninstallation. Mount the file and double-click ``bootstrapper.app``. Follow the wizard instructions. Select **Remove** option when presented. If you have more product versions installed, you can select one from a drop-down menu in GUI.
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-dropdown-macos.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## Uninstall Using the Intel® Software Installer
|
||||
If you have installed OpenVINO Runtime from archive files, you can uninstall it by deleting the archive files and the extracted folders.
|
||||
|
||||
@sphinxdirective
|
||||
.. tab:: Windows
|
||||
|
||||
1. Choose the **Apps & Features** option from the Windows Settings app.
|
||||
2. From the list of installed applications, select the Intel® Distribution of OpenVINO™ Toolkit and click **Uninstall**.
|
||||
3. Follow the uninstallation wizard instructions.
|
||||
If you have created the symbolic link, remove the link first.
|
||||
|
||||
Alternatively, follow the steps:
|
||||
|
||||
1. Go to installation directory.
|
||||
2. In ``OpenVINO`` directory find ``Installer`` folder and open it.
|
||||
3. Double-click on ``installer.exe`` and you will be presented with dialog box shown below.
|
||||
Use either of the following methods to delete the files:
|
||||
|
||||
.. tab:: Linux
|
||||
|
||||
1. Run the installer file from the user mode installation directory:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
/home/<user>/intel/openvino_installer/installer
|
||||
|
||||
or in a case of administrative installation:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
/opt/intel/openvino_installer/installer
|
||||
|
||||
2. Follow the uninstallation wizard instructions.
|
||||
|
||||
.. tab:: macOS
|
||||
|
||||
1. Open the installer file from the installation directory:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
open /opt/intel/openvino_installer/installer.app
|
||||
|
||||
2. Follow the uninstallation wizard instructions.
|
||||
|
||||
Finally, complete the procedure with clicking on **Modify** and then selecting **Uninstall** option:
|
||||
|
||||
.. tab:: Windows
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-win.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
|
||||
.. tab:: Linux
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-linux.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
* Use Windows Explorer to remove the files.
|
||||
* Open a Command Prompt and run:
|
||||
|
||||
if GUI is not available, installer also could be run in a CLI mode:
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-cli.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
.. code-block:: sh
|
||||
|
||||
.. tab:: macOS
|
||||
rmdir /s <extracted_folder>
|
||||
del <path_to_archive>
|
||||
|
||||
.. image:: _static/images/openvino-uninstall-macos.png
|
||||
:width: 500px
|
||||
:align: center
|
||||
|
||||
.. tab:: Linux & macOS
|
||||
|
||||
If you have created the symbolic link, remove the link first:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
rm /home/<USER>/intel/openvino_2022
|
||||
|
||||
To delete the files:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
rm -r <extracted_folder> && rm <path_to_archive>
|
||||
|
||||
@endsphinxdirective
|
||||
|
|
|
|||
Loading…
Reference in New Issue