diff --git a/docs/install_guides/installing-model-dev-tools.md b/docs/install_guides/installing-model-dev-tools.md index 9edf66b7e398cc..7015de7f338981 100644 --- a/docs/install_guides/installing-model-dev-tools.md +++ b/docs/install_guides/installing-model-dev-tools.md @@ -160,7 +160,7 @@ Note that the commands are different for a Python installation and a C++ install @endsphinxdirective -For more details on the openvino-dev PyPI package, see https://pypi.org/project/openvino-dev/2022.3.1/. +For more details on the openvino-dev PyPI package, see https://pypi.org/project/openvino-dev/2022.3.2/. ### Step 5. Test the Installation diff --git a/docs/install_guides/installing-openvino-conda.md b/docs/install_guides/installing-openvino-conda.md index 3b842797d5666a..1de19d46bed34c 100644 --- a/docs/install_guides/installing-openvino-conda.md +++ b/docs/install_guides/installing-openvino-conda.md @@ -42,7 +42,7 @@ Installing OpenVINO Runtime with Anaconda Package Manager .. code-block:: sh - conda install -c conda-forge openvino=2022.3.1 + conda install -c conda-forge openvino=2022.3.2 Congratulations! You have finished installing OpenVINO Runtime. @@ -50,21 +50,21 @@ Installing OpenVINO Runtime with Anaconda Package Manager Uninstalling OpenVINO™ Runtime ########################################################### -Once OpenVINO Runtime is installed via Conda, you can remove it using the following command, +Once OpenVINO Runtime is installed via Conda, you can remove it using the following command, with the proper OpenVINO version number: .. code-block:: sh - conda remove openvino=2022.3.1 + conda remove openvino=2022.3.2 What's Next? ############################################################ -Now that you've installed OpenVINO Runtime, you are ready to run your own machine learning applications! +Now that you've installed OpenVINO Runtime, you are ready to run your own machine learning applications! To learn more about how to integrate a model in OpenVINO applications, try out some tutorials and sample applications. -Try the :doc:`C++ Quick Start Example ` for step-by-step instructions +Try the :doc:`C++ Quick Start Example ` for step-by-step instructions on building and running a basic image classification C++ application. .. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg diff --git a/docs/install_guides/installing-openvino-from-archive-linux.md b/docs/install_guides/installing-openvino-from-archive-linux.md index c4fd36b07872fa..ff3bf2c697297b 100644 --- a/docs/install_guides/installing-openvino-from-archive-linux.md +++ b/docs/install_guides/installing-openvino-from-archive-linux.md @@ -4,7 +4,7 @@ With the OpenVINO™ 2022.3 release, you can download and use archive files to i 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. See the [Install OpenVINO from PyPI](installing-openvino-pip.md) page for instructions on how to install OpenVINO Runtime for Python using PyPI. -> **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/2022.3.1/) only. +> **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/2022.3.2/) only. See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino-2022-3-lts-relnotes.html) for more information on updates in the latest release. @@ -84,45 +84,45 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl cd /Downloads -4. Download the `OpenVINO Runtime archive file for your system `__, extract the files, rename the extracted folder and move it to the desired path: +4. Download the `OpenVINO Runtime archive file for your system `__, extract the files, rename the extracted folder and move it to the desired path: .. tab:: Ubuntu 20.04 .. code-block:: sh - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/linux/l_openvino_toolkit_ubuntu20_2022.3.1.9227.cf2c7da5689_x86_64.tgz --output openvino_2022.3.1.tgz - tar -xf openvino_2022.3.1.tgz - sudo mv l_openvino_toolkit_ubuntu20_2022.3.1.9227.cf2c7da5689_x86_64 /opt/intel/openvino_2022.3.1 + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/linux/l_openvino_toolkit_ubuntu20_2022.3.2.9279.e2c7e4d7b4d_x86_64.tgz --output openvino_2022.3.2.tgz + tar -xf openvino_2022.3.2.tgz + sudo mv l_openvino_toolkit_ubuntu20_2022.3.2.9279.e2c7e4d7b4d_x86_64 /opt/intel/openvino_2022.3.2 .. tab:: Ubuntu 18.04 .. code-block:: sh - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/linux/l_openvino_toolkit_ubuntu18_2022.3.1.9227.cf2c7da5689_x86_64.tgz --output openvino_2022.3.1.tgz - tar -xf openvino_2022.3.1.tgz - sudo mv l_openvino_toolkit_ubuntu18_2022.3.1.9227.cf2c7da5689_x86_64 /opt/intel/openvino_2022.3.1 + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/linux/l_openvino_toolkit_ubuntu18_2022.3.2.9279.e2c7e4d7b4d_x86_64.tgz --output openvino_2022.3.2.tgz + tar -xf openvino_2022.3.2.tgz + sudo mv l_openvino_toolkit_ubuntu18_2022.3.2.9279.e2c7e4d7b4d_x86_64 /opt/intel/openvino_2022.3.2 .. tab:: RHEL 8 .. code-block:: sh - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/linux/l_openvino_toolkit_rhel8_2022.3.1.9227.cf2c7da5689_x86_64.tgz --output openvino_2022.3.1.tgz - tar -xf openvino_2022.3.1.tgz - sudo mv l_openvino_toolkit_rhel8_2022.3.1.9227.cf2c7da5689_x86_64 /opt/intel/openvino_2022.3.1 + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/linux/l_openvino_toolkit_rhel8_2022.3.2.9279.e2c7e4d7b4d_x86_64.tgz --output openvino_2022.3.2.tgz + tar -xf openvino_2022.3.2.tgz + sudo mv l_openvino_toolkit_rhel8_2022.3.2.9279.e2c7e4d7b4d_x86_64 /opt/intel/openvino_2022.3.2 .. tab:: CentOS 7 .. code-block:: sh - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/linux/l_openvino_toolkit_centos7_2022.3.1.9227.cf2c7da5689_x86_64.tgz --output openvino_2022.3.1.tgz - tar -xf openvino_2022.3.1.tgz - sudo mv l_openvino_toolkit_centos7_2022.3.1.9227.cf2c7da5689_x86_64 /opt/intel/openvino_2022.3.1 + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/linux/l_openvino_toolkit_centos7_2022.3.2.9279.e2c7e4d7b4d_x86_64.tgz --output openvino_2022.3.2.tgz + tar -xf openvino_2022.3.2.tgz + sudo mv l_openvino_toolkit_centos7_2022.3.2.9279.e2c7e4d7b4d_x86_64 /opt/intel/openvino_2022.3.2 5. Install required system dependencies on Linux. To do this, OpenVINO provides a script in the extracted installation directory. Run the following command: .. code-block:: sh - cd /opt/intel/openvino_2022.3.1 + cd /opt/intel/openvino_2022.3.2 sudo -E ./install_dependencies/install_openvino_dependencies.sh 6. (Optional) Install *numpy* Python Library: @@ -131,11 +131,11 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl This step is required only when you decide to use Python API. - You can use the ``requirements.txt`` file from the ``/opt/intel/openvino_2022.3.1/python/python.`` folder: + You can use the ``requirements.txt`` file from the ``/opt/intel/openvino_2022.3.2/python/python.`` folder: .. code-block:: sh - cd /opt/intel/openvino_2022.3.1 + cd /opt/intel/openvino_2022.3.2 python3 -m pip install -r ./python/python3./requirements.txt 7. For simplicity, it is useful to create a symbolic link as below: @@ -143,7 +143,7 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl .. code-block:: sh cd /opt/intel - sudo ln -s openvino_2022.3.1 openvino_2022 + sudo ln -s openvino_2022.3.2 openvino_2022 .. 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. @@ -158,7 +158,7 @@ You must update several environment variables before you can compile and run Ope ```sh source /opt/intel/openvino_2022/setupvars.sh -``` +``` 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. diff --git a/docs/install_guides/installing-openvino-from-archive-macos.md b/docs/install_guides/installing-openvino-from-archive-macos.md index b0f7bef083f81b..9ac1be399cd32e 100644 --- a/docs/install_guides/installing-openvino-from-archive-macos.md +++ b/docs/install_guides/installing-openvino-from-archive-macos.md @@ -6,7 +6,7 @@ Installing OpenVINO Runtime from archive files is recommended for C++ developers See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino-2022-3-lts-relnotes.html) for more information on updates in the latest 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/2022.3.1/) only. +> **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/2022.3.2/) only. @sphinxdirective @@ -47,23 +47,23 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl cd /Downloads -4. Download the `OpenVINO Runtime archive file for macOS `__, extract the files, rename the extracted folder and move it to the desired path: +4. Download the `OpenVINO Runtime archive file for macOS `__, extract the files, rename the extracted folder and move it to the desired path: .. tab:: x86, 64-bit .. code-block:: sh - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/macos/m_openvino_toolkit_macos_10_15_2022.3.1.9227.cf2c7da5689_x86_64.tgz --output openvino_2022.3.1.tgz - tar -xf openvino_2022.3.1.tgz - sudo mv m_openvino_toolkit_macos_10_15_2022.3.1.9227.cf2c7da5689_x86_64 /opt/intel/openvino_2022.3.1 + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/macos/m_openvino_toolkit_macos_10_15_2022.3.2.9279.e2c7e4d7b4d_x86_64.tgz --output openvino_2022.3.2.tgz + tar -xf openvino_2022.3.2.tgz + sudo mv m_openvino_toolkit_macos_10_15_2022.3.2.9279.e2c7e4d7b4d_x86_64 /opt/intel/openvino_2022.3.2 .. tab:: ARM, 64-bit .. code-block:: sh - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/macos/m_openvino_toolkit_macos_11_0_2022.3.1.9227.cf2c7da5689_arm64.tgz --output openvino_2022.3.1.tgz - tar -xf openvino_2022.3.1.tgz - sudo mv m_openvino_toolkit_macos_11_0_2022.3.1.9227.cf2c7da5689_arm64 /opt/intel/openvino_2022.3.1 + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/macos/m_openvino_toolkit_macos_11_0_2022.3.2.9279.e2c7e4d7b4d_arm64.tgz --output openvino_2022.3.2.tgz + tar -xf openvino_2022.3.2.tgz + sudo mv m_openvino_toolkit_macos_11_0_2022.3.2.9279.e2c7e4d7b4d_arm64 /opt/intel/openvino_2022.3.2 5. (Optional) Install *numpy* Python Library: @@ -71,18 +71,18 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl This step is required only when you decide to use Python API. - You can use the ``requirements.txt`` file from the ``opt/intel/openvino_2022.3.1/python/python.`` folder: + You can use the ``requirements.txt`` file from the ``opt/intel/openvino_2022.3.2/python/python.`` folder: .. code-block:: sh - cd /opt/intel/openvino_2022.3.1 + cd /opt/intel/openvino_2022.3.2 python3 -m pip install -r ./python/python3./requirements.txt 6. For simplicity, it is useful to create a symbolic link as below: .. code-block:: sh - sudo ln -s openvino_2022.3.1 openvino_2022 + sudo ln -s openvino_2022.3.2 openvino_2022 .. note:: @@ -98,7 +98,7 @@ You must update several environment variables before you can compile and run Ope ```sh source /opt/intel/openvino_2022/setupvars.sh -``` +``` 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. @@ -169,13 +169,13 @@ To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalli * IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ +---> .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit @endsphinxdirective diff --git a/docs/install_guides/installing-openvino-from-archive-windows.md b/docs/install_guides/installing-openvino-from-archive-windows.md index 34d23034398db6..3a69260379f0f0 100644 --- a/docs/install_guides/installing-openvino-from-archive-windows.md +++ b/docs/install_guides/installing-openvino-from-archive-windows.md @@ -4,7 +4,7 @@ With the OpenVINO™ 2022.3 release, you can download and use archive files to i 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. See the [Install OpenVINO from PyPI](installing-openvino-pip.md) page for instructions on how to install OpenVINO Runtime for Python using PyPI. -> **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/2022.3.1/) only. +> **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/2022.3.2/) only. See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino-2022-3-lts-relnotes.html) for more information on updates in the latest release. @@ -58,19 +58,19 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl ``C:\Program Files (x86)\Intel`` is the recommended folder. You may also use a different path if desired or if you don't have administrator privileges on your computer. -2. Download the `OpenVINO Runtime archive file for Windows `__ to your local ``Downloads`` folder. +2. Download the `OpenVINO Runtime archive file for Windows `__ to your local ``Downloads`` folder. If you prefer using command-lines, run the following commands in the command prompt window you opened: .. code-block:: sh cd /Downloads - curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/windows/w_openvino_toolkit_windows_2022.3.1.9227.cf2c7da5689_x86_64.zip --output openvino_2022.3.1.zip + curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/windows/w_openvino_toolkit_windows_2022.3.2.9279.e2c7e4d7b4d_x86_64.zip--output openvino_2022.3.2.zip .. note:: - A ``.sha256`` file is provided together with the archive file to validate your download process. To do that, download the ``.sha256`` file from the same repository and run ``CertUtil -hashfile openvino_2022.3.1.zip SHA256``. Compare the returned value in the output with what's in the ``.sha256`` file: if the values are the same, you have downloaded the correct + A ``.sha256`` file is provided together with the archive file to validate your download process. To do that, download the ``.sha256`` file from the same repository and run ``CertUtil -hashfile openvino_2022.3.2.zip SHA256``. Compare the returned value in the output with what's in the ``.sha256`` file: if the values are the same, you have downloaded the correct file successfully; if not, create a Support ticket `here `__. @@ -80,9 +80,9 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl .. code-block:: sh - tar -xf openvino_2022.3.1.zip - ren w_openvino_toolkit_windows_2022.3.1.9227.cf2c7da5689_x86_64 openvino_2022.3.1 - move openvino_2022.3.1 "C:\Program Files (x86)\Intel" + tar -xf openvino_2022.3.2.zip + ren w_openvino_toolkit_windows_2022.3.2.9227.cf2c7da5689_x86_64 openvino_2022.3.2 + move openvino_2022.3.2 "C:\Program Files (x86)\Intel" 6. (Optional) Install *numpy* Python Library: @@ -91,11 +91,11 @@ See the [Release Notes](https://www.intel.com/content/www/us/en/developer/articl This step is required only when you decide to use Python API. - You can use the ``requirements.txt`` file from the ``C:\Program Files (x86)\Intel\openvino_2022.3.1\python\python.`` folder: + You can use the ``requirements.txt`` file from the ``C:\Program Files (x86)\Intel\openvino_2022.3.2\python\python.`` folder: .. code-block:: sh - cd "C:\Program Files (x86)\Intel\openvino_2022.3.1" + cd "C:\Program Files (x86)\Intel\openvino_2022.3.2" python -m pip install -r .\python\python3.\requirements.txt @@ -205,14 +205,7 @@ To uninstall OpenVINO, follow the steps on the [Uninstalling page](uninstalling- * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models ` * IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ - + .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit @endsphinxdirective diff --git a/docs/install_guides/installing-openvino-pip.md b/docs/install_guides/installing-openvino-pip.md index 127f2d50135f8c..a775a3545aec78 100644 --- a/docs/install_guides/installing-openvino-pip.md +++ b/docs/install_guides/installing-openvino-pip.md @@ -7,14 +7,14 @@ You can install both OpenVINO™ Runtime and OpenVINO Development Tools through .. note: * If you install OpenVINO Development Tools, OpenVINO Runtime will also be installed as a dependency, so you don't need to install it separately. - * The PyPI distribution does not include support for VPU, VAD, and HDDL. For information on how to use these devices, + * The PyPI distribution does not include support for VPU, VAD, and HDDL. For information on how to use these devices, see :doc:`Additional Configurations For Hardware ` Installing OpenVINO Runtime ########################### -For system requirements and troubleshooting, see https://pypi.org/project/openvino/2022.3.1/ +For system requirements and troubleshooting, see https://pypi.org/project/openvino/2022.3.2/ Step 1. Set Up Python Virtual Environment +++++++++++++++++++++++++++++++++++++++++ diff --git a/docs/install_guides/installing-openvino-raspbian.md b/docs/install_guides/installing-openvino-raspbian.md index cda2c6702f1048..668031bafc39ee 100644 --- a/docs/install_guides/installing-openvino-raspbian.md +++ b/docs/install_guides/installing-openvino-raspbian.md @@ -37,21 +37,21 @@ The `/opt/intel` path is the recommended folder path for administrators or root users. If you prefer to install OpenVINO in regular userspace, the recommended path is `/home//intel`. You may use a different path if desired. -3. Go to your `~/Downloads` directory and download OpenVINO Runtime archive file for Debian from the `OpenVINO package repository `_. +3. Go to your `~/Downloads` directory and download OpenVINO Runtime archive file for Debian from the `OpenVINO package repository `_. .. tab:: ARM 32-bit .. code-block:: sh cd ~/Downloads/ - sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/linux/l_openvino_toolkit_debian9_2022.3.1.9227.cf2c7da5689_armhf.tgz -O openvino_2022.3.1.tgz + sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/linux/l_openvino_toolkit_debian9_2022.3.2.9279.e2c7e4d7b4d_armhf.tgz -O openvino_2022.3.2.tgz .. tab:: ARM 64-bit .. code-block:: sh cd ~/Downloads/ - sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.1/linux/l_openvino_toolkit_debian9_2022.3.1.9227.cf2c7da5689_arm64.tgz -O openvino_2022.3.1.tgz + sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3.2/linux/l_openvino_toolkit_debian9_2022.3.2.9279.e2c7e4d7b4d_arm64.tgz -O openvino_2022.3.2.tgz 4. Extract the archive file and move it to the installation folder: @@ -59,15 +59,15 @@ .. code-block:: sh - sudo tar -xf openvino_2022.3.1.tgz - sudo mv l_openvino_toolkit_debian9_2022.3.1.9227.cf2c7da5689_armhf /opt/intel/openvino_2022.3.1 + sudo tar -xf openvino_2022.3.2.tgz + sudo mv l_openvino_toolkit_debian9_2022.3.2.9279.e2c7e4d7b4d_armhf /opt/intel/openvino_2022.3.2 .. tab:: ARM 64-bit .. code-block:: sh sudo tar -xf openvino_2022.3.0.tgz - sudo mv l_openvino_toolkit_debian9_2022.3.1.9227.cf2c7da5689_arm64 /opt/intel/openvino_2022.3.1 + sudo mv l_openvino_toolkit_debian9_2022.3.2.9279.e2c7e4d7b4d_arm64 /opt/intel/openvino_2022.3.2 5. Install required system dependencies on Linux. To do this, OpenVINO provides a script in the extracted installation directory. Run the following command: @@ -81,18 +81,18 @@ This step is required only when you decide to use Python API. - You can use the ``requirements.txt`` file from the ``/opt/intel/openvino_2022.3.1/python/python.`` folder: + You can use the ``requirements.txt`` file from the ``/opt/intel/openvino_2022.3.2/python/python.`` folder: .. code-block:: sh - cd /opt/intel/openvino_2022.3.1 + cd /opt/intel/openvino_2022.3.2 pip3 install -r ./python/python3./requirements.txt 7. For simplicity, it is useful to create a symbolic link as below: .. code-block:: sh - sudo ln -s openvino_2022.3.1 openvino_2022 + sudo ln -s openvino_2022.3.2 openvino_2022 .. note:: @@ -117,7 +117,7 @@ You must update several environment variables before you can compile and run Ope ```sh source /opt/intel/openvino_2022/setupvars.sh -``` +``` 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. @@ -185,7 +185,7 @@ To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalli * Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide ` * Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview ` * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models ` -* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ +* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ * :ref:`OpenVINO Installation Selector Tool ` .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit diff --git a/docs/install_guides/pypi-openvino-dev.md b/docs/install_guides/pypi-openvino-dev.md index 3b2e9bae139ca4..44e81c4cb2b472 100644 --- a/docs/install_guides/pypi-openvino-dev.md +++ b/docs/install_guides/pypi-openvino-dev.md @@ -1,4 +1,4 @@ -# OpenVINO™ Development Tools +# OpenVINO™ Development Tools Intel® Distribution of OpenVINO™ toolkit is an open-source toolkit for optimizing and deploying AI inference. It can be used to develop applications and solutions based on deep learning tasks, such as: emulation of human vision, automatic speech recognition, natural language processing, recommendation systems, etc. It provides high-performance and rich deployment options, from edge to cloud. @@ -16,7 +16,7 @@ Before you start the installation, check the supported operating systems and req ### Step 1. Set Up Python Virtual Environment -Use a virtual environment to avoid dependency conflicts. +Use a virtual environment to avoid dependency conflicts. To create a virtual environment, use the following commands: @@ -67,7 +67,7 @@ To install and configure the components of the package for working with specific ```sh pip install openvino-dev[extras] ``` - where `extras` is one or more of the following values separated with "," : + where `extras` is one or more of the following values separated with "," : | Extras Value | DL Framework | | :-------------------------------| :------------------------------------------------------------------------------- | @@ -79,7 +79,7 @@ pip install openvino-dev[extras] | tensorflow | [TensorFlow* 1.x](https://www.tensorflow.org/versions#tensorflow_1) | | tensorflow2 | [TensorFlow* 2.x](https://www.tensorflow.org/versions#tensorflow_2) | -For example, to install and configure the components for working with TensorFlow 2.x, Apache MXNet and Caffe, use the following command: +For example, to install and configure the components for working with TensorFlow 2.x, Apache MXNet and Caffe, use the following command: ```sh pip install openvino-dev[tensorflow2,mxnet,caffe] ``` @@ -105,34 +105,34 @@ For example, to install and configure the components for working with TensorFlow ## What's in the Package? -> **NOTE**: The openvino-dev package installs [OpenVINO™ Runtime](https://pypi.org/project/openvino/2022.3.1/) as a dependency, which is the engine that runs the deep learning model and includes a set of libraries for an easy inference integration into your applications. +> **NOTE**: The openvino-dev package installs [OpenVINO™ Runtime](https://pypi.org/project/openvino/2022.3.2/) as a dependency, which is the engine that runs the deep learning model and includes a set of libraries for an easy inference integration into your applications. **In addition, the openvino-dev package installs the following components by default:** -| Component | Console Script | Description | +| Component | Console Script | Description | |------------------|---------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | [Model Optimizer](https://docs.openvino.ai/2022.3/openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html) | `mo` |**Model Optimizer** imports, converts, and optimizes models that were trained in popular frameworks to a format usable by OpenVINO components.
Supported frameworks include Caffe\*, TensorFlow\*, MXNet\*, PaddlePaddle\*, and ONNX\*. | | [Benchmark Tool](https://docs.openvino.ai/2022.3/openvino_inference_engine_tools_benchmark_tool_README.html)| `benchmark_app` | **Benchmark Application** allows you to estimate deep learning inference performance on supported devices for synchronous and asynchronous modes. | | [Accuracy Checker](https://docs.openvino.ai/2022.3/omz_tools_accuracy_checker.html) and
[Annotation Converter](https://docs.openvino.ai/2022.3/omz_tools_accuracy_checker_annotation_converters.html) | `accuracy_check`
`convert_annotation` |**Accuracy Checker** is a deep learning accuracy validation tool that allows you to collect accuracy metrics against popular datasets. The main advantages of the tool are the flexibility of configuration and a set of supported datasets, preprocessing, postprocessing, and metrics.
**Annotation Converter** is a utility that prepares datasets for evaluation with Accuracy Checker. | | [Post-Training Optimization Tool](https://docs.openvino.ai/2022.3/pot_introduction.html)| `pot` |**Post-Training Optimization Tool** allows you to optimize trained models with advanced capabilities, such as quantization and low-precision optimizations, without the need to retrain or fine-tune models. | -| [Model Downloader and other Open Model Zoo tools](https://docs.openvino.ai/2022.3/omz_tools_downloader.html)| `omz_downloader`
`omz_converter`
`omz_quantizer`
`omz_info_dumper`| **Model Downloader** is a tool for getting access to the collection of high-quality and extremely fast pre-trained deep learning [public](@ref omz_models_group_public) and [Intel](@ref omz_models_group_intel)-trained models. These free pre-trained models can be used to speed up the development and production deployment process without training your own models. The tool downloads model files from online sources and, if necessary, patches them to make them more usable with Model Optimizer. A number of additional tools are also provided to automate the process of working with downloaded models:
**Model Converter** is a tool for converting Open Model Zoo models that are stored in an original deep learning framework format into the OpenVINO Intermediate Representation (IR) using Model Optimizer.
**Model Quantizer** is a tool for automatic quantization of full-precision models in the IR format into low-precision versions using the Post-Training Optimization Tool.
**Model Information Dumper** is a helper utility for dumping information about the models to a stable, machine-readable format. | +| [Model Downloader and other Open Model Zoo tools](https://docs.openvino.ai/2022.3/omz_tools_downloader.html)| `omz_downloader`
`omz_converter`
`omz_quantizer`
`omz_info_dumper`| **Model Downloader** is a tool for getting access to the collection of high-quality and extremely fast pre-trained deep learning [public](@ref omz_models_group_public) and [Intel](@ref omz_models_group_intel)-trained models. These free pre-trained models can be used to speed up the development and production deployment process without training your own models. The tool downloads model files from online sources and, if necessary, patches them to make them more usable with Model Optimizer. A number of additional tools are also provided to automate the process of working with downloaded models:
**Model Converter** is a tool for converting Open Model Zoo models that are stored in an original deep learning framework format into the OpenVINO Intermediate Representation (IR) using Model Optimizer.
**Model Quantizer** is a tool for automatic quantization of full-precision models in the IR format into low-precision versions using the Post-Training Optimization Tool.
**Model Information Dumper** is a helper utility for dumping information about the models to a stable, machine-readable format. | ## Troubleshooting -For general troubleshooting steps and issues, see [Troubleshooting Guide for OpenVINO Installation](https://docs.openvino.ai/2022.3/openvino_docs_get_started_guide_troubleshooting.html). The following sections also provide explanations to several error messages. +For general troubleshooting steps and issues, see [Troubleshooting Guide for OpenVINO Installation](https://docs.openvino.ai/2022.3/openvino_docs_get_started_guide_troubleshooting.html). The following sections also provide explanations to several error messages. ### Errors with Installing via PIP for Users in China Users in China might encounter errors while downloading sources via PIP during OpenVINO™ installation. To resolve the issues, try the following solution: - -* Add the download source using the ``-i`` parameter with the Python ``pip`` command. For example: + +* Add the download source using the ``-i`` parameter with the Python ``pip`` command. For example: ``` sh pip install openvino-dev -i https://mirrors.aliyun.com/pypi/simple/ ``` Use the ``--trusted-host`` parameter if the URL above is ``http`` instead of ``https``. You can also run the following command to install openvino-dev with specific frameworks. For example: - + ``` pip install openvino-dev[tensorflow2] -i https://mirrors.aliyun.com/pypi/simple/ ``` @@ -146,7 +146,7 @@ pip install openvino-dev[tensorflow2,mxnet,caffe] zsh: no matches found: openvino-dev[tensorflow2,mxnet,caffe] ``` -By default zsh interprets square brackets as an expression for pattern matching. To resolve this issue, you need to escape the command with quotes: +By default zsh interprets square brackets as an expression for pattern matching. To resolve this issue, you need to escape the command with quotes: ```sh pip install 'openvino-dev[tensorflow2,mxnet,caffe]'