Docs: Update "Install OpenVINO Runtime on macOS from Archive File" page (#13347)
* docs: Update intro and step 1 * docs: finish updates * docs: fix duplicate section * docs: fix curl command * docs: clarify archive install is for C++ users * docs: add link to PyPI install page * docs: minor fixes * docs: add link to Release Notes * docs: Change back to numbered instructions * docs: typo fix * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Apply suggestions from code review * Update installing-openvino-from-archive-macos.md * Update installing-openvino-from-archive-macos.md * Update installing-openvino-from-archive-macos.md * Update installing-openvino-from-archive-macos.md * Update installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md * Update docs/install_guides/installing-openvino-from-archive-macos.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> Co-authored-by: Maciej Smyk <maciejx.smyk@intel.com>
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# Install OpenVINO™ Runtime on macOS from an Archive File {#openvino_docs_install_guides_installing_openvino_from_archive_macos}
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With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime.
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With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime. The archive files contain pre-built binaries and library files needed for OpenVINO Runtime, as well as code samples.
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You can also check the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in this release.
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Installing OpenVINO Runtime from archive files is recommended for C++ developers. If you are working with Python, the PyPI package has everything needed for Python development and deployment on CPU and GPUs. Visit the [Install OpenVINO from PyPI](installing-openvino-pip.md) page for instructions on how to install OpenVINO Runtime for Python using PyPI.
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See the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in the latest release.
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> **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.
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@ -11,9 +13,14 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
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## System Requirements
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@sphinxdirective
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.. tab:: Operating Systems
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macOS 10.15
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macOS 10.15, 11, 12, and 13 versions with the x86 architecture, 64 bits
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.. note::
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Only macOS 10.15 is fully validated with OpenVINO. Other versions depend on the compatibility of macOS.
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.. tab:: Hardware
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@ -31,7 +38,7 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
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* `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).
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* `Python 3.6 - 3.10 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.6 - 3.10). Install and add to path.
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* Note that OpenVINO is gradually stopping the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10.
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* Note that OpenVINO is gradually phasing out the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10.
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* Apple Xcode Command Line Tools. In the terminal, run `xcode-select --install` from any directory
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* (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
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@ -41,49 +48,53 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
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### <a name="install-core"></a>Step 1: Install OpenVINO Core Components
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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:
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1. Open a command prompt terminal window.
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2. Create the `/opt/intel` folder for OpenVINO by using the following command. If the folder already exists, skip this command.
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```sh
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m_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz
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m_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz.sha256
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sudo mkdir /opt/intel
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```
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where the `.sha256` file is used to verify the success of the download process.
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> **NOTE**: The `/opt/intel` path is the recommended folder path for installing OpenVINO. You may use a different path if desired.
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2. Locate the downloaded files in your system. This document assumes the files are in your `Downloads` directory.
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3. Open a command prompt terminal window, and verify the checksum of the `sha256` file by using the following command:
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3. Browse to the current user's `Downloads` folder:
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```sh
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shasum -c -a 256 <archive name>.tgz.sha256
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```
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If any error message appears, check your network connections, re-download the correct files, and make sure the download process completes successfully.
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cd <user_home>/Downloads
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```
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4. Extract OpenVINO files from the `.tgz` file:
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4. Download the [OpenVINO Runtime archive file for macOS](https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/macos/), extract the files, rename the extracted folder and move it to the desired path:
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```sh
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tar xf <archive name>.tgz -C <destination_dir>
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curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/macos/m_openvino_toolkit_osx_2022.2.0.7713.af16ea1d79a_x86_64.tgz --output openvino_2022.2.0.7713.tgz
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tar -xf openvino_2022.2.0.7713.tgz
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sudo mv m_openvino_toolkit_osx_2022.2.0.7713.af16ea1d79a_x86_64 /opt/intel/openvino_2022.2.0.7713
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```
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where the `<destination_dir>` is the directory that you extract OpenVINO files to. You're recommended to set it as `/opt/intel/`.
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The standard OpenVINO `INSTALL_DIR` referenced in this document is `/opt/intel/openvino_<version>`.
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For simplicity, you can create a symbolic link to the latest installation: `/opt/intel/openvino_2022/`.
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5. For simplicity, it is useful to create a symbolic link as below:
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```
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sudo ln -s openvino_2022.2.0.7713 openvino_2022
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```
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> **NOTE**: If you have already installed a previous release of OpenVINO 2022, a symbolic link to the `openvino_2022` folder may already exist. Unlink the previous link with `sudo unlink openvino_2022`, and then re-run the command above.
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The core components are now installed. Continue to the next section to configure the environment.
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Congratulations, you finished the installation! The `/opt/intel/openvino_2022` folder now contains the core components for OpenVINO. If you used a different path in Step 2, you will find the `openvino_2022` folder there. The path to the `openvino_2022` directory is also referred as `<INSTALL_DIR>` throughout the OpenVINO documentation.
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### <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
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You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:
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You must update several environment variables before you can compile and run OpenVINO applications. Open a terminal window and run the `setupvars.sh` script as shown below to temporarily set your environment variables. If your <INSTALL_DIR> is not `/opt/intel/openvino_2022`, use the correct one instead.
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```sh
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source <INSTALL_DIR>/setupvars.sh
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source /opt/intel/openvino_2022/setupvars.sh
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```
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If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
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If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing the `setupvars.sh` of your choice.
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> **NOTE**: You can also run this script whenever you start a 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 a different setup.
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> **NOTE**: The above command must be re-run every time you start a new terminal session. To set up macOS to automatically run the command every time a new terminal is opened, open `~/.zshrc` in your favorite editor and add `source /opt/intel/openvino_2022/setupvars.sh` after the last line. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `~/.zshrc` is not recommended when you have multiple OpenVINO versions on your machine and want to switch among them.
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The environment variables are set. Continue to the next section if you want to download any additional components.
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### <a name="model-optimizer"></a>Step 3 (Optional): Install Additional Components
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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.
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OpenVINO Development Tools is a set of utilities for working with OpenVINO and OpenVINO models. It provides tools like Model Optimizer, Benchmark Tool, Post-Training Optimization Tool, and Open Model Zoo Downloader. If you install OpenVINO Runtime using archive files, OpenVINO Development Tools must be installed separately.
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See the [Install OpenVINO Development Tools](installing-model-dev-tools.md) page for step-by-step installation instructions.
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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).
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@ -96,18 +107,35 @@ If you want to run inference on Intel® Neural Compute Stick 2 use the following
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@endsphinxdirective
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## <a name="get-started"></a>What's Next?
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Now that you've installed OpenVINO Runtime, you're ready to run your own machine learning applications! Learn more about how to integrate a model in OpenVINO applications by trying out the following tutorials.
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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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@sphinxdirective
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.. tab:: Get started with Python
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Start with some Python tutorials:
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* [Hello Image Classification](https://docs.openvino.ai/latest/notebooks/001-hello-world-with-output.html)
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* [Convert TensorFlow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
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* [Convert a PyTorch model and remove the image background](https://docs.openvino.ai/latest/notebooks/205-vision-background-removal-with-output.html)
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Try the `Python Quick Start Example <https://docs.openvino.ai/2022.2/notebooks/201-vision-monodepth-with-output.html>`_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
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To start with C++ samples, see <a href="openvino_docs_OV_UG_Samples_Overview.html#build-samples-macos">Build Sample Applications on macOS</a> first, and then you can try the following samples:
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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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* [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
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.. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
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:width: 400
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Visit the :ref:`Tutorials <notebook tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
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* `OpenVINO Python API Tutorial <https://docs.openvino.ai/2022.2/notebooks/002-openvino-api-with-output.html>`_
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* `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2022.2/notebooks/001-hello-world-with-output.html>`_
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* `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2022.2/notebooks/205-vision-background-removal-with-output.html>`_
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.. tab:: Get started with C++
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Try the `C++ Quick Start Example <openvino_docs_get_started_get_started_demos.html>`_ for step-by-step instructions on building and running a basic image classification C++ application.
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.. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg
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:width: 400
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Visit the :ref:`Samples <code samples>` page for other C++ example applications to get you started with OpenVINO, such as:
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* `Basic object detection with the Hello Reshape SSD C++ sample <openvino_inference_engine_samples_hello_reshape_ssd_README.html>`_
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* `Automatic speech recognition C++ sample <openvino_inference_engine_samples_speech_sample_README.html>`_
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@endsphinxdirective
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## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
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@ -122,8 +150,16 @@ To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalli
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* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
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* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
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* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
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* IoT libraries and code samples in the GitHub repository: `Intel® IoT Developer Kit`_
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* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_
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<!---
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To learn more about converting models from specific frameworks, go to:
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* :ref:`Convert Your Caffe Model <convert model caffe>`
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* :ref:`Convert Your TensorFlow Model <convert model tf>`
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* :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
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* :ref:`Convert Your Kaldi Model <convert model kaldi>`
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* :ref:`Convert Your ONNX Model <convert model onnx>`
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--->
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.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
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@endsphinxdirective
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