From c9a44dcb9c5b14311da495b6ad708a09e85f7fbf Mon Sep 17 00:00:00 2001 From: Sebastian Golebiewski Date: Tue, 15 Nov 2022 06:34:38 +0100 Subject: [PATCH] DOCS: Install raspbian updates - for master (#13992) * update raspbian installation * fix formatting * update * update unlink command * update the architecture * Update installing-openvino-raspbian.md * Apply suggestions from code review Co-authored-by: Yuan Xu --- .../installing-openvino-raspbian.md | 117 +++++++++++++----- 1 file changed, 83 insertions(+), 34 deletions(-) diff --git a/docs/install_guides/installing-openvino-raspbian.md b/docs/install_guides/installing-openvino-raspbian.md index 52c273d1efb..c5466f1b4f8 100644 --- a/docs/install_guides/installing-openvino-raspbian.md +++ b/docs/install_guides/installing-openvino-raspbian.md @@ -1,4 +1,4 @@ -# Install OpenVINO™ toolkit for Raspbian OS {#openvino_docs_install_guides_installing_openvino_raspbian} +# Install OpenVINO™ Runtime for Raspbian OS {#openvino_docs_install_guides_installing_openvino_raspbian} @sphinxdirective .. note:: @@ -7,13 +7,13 @@ * There is also an open-source version of OpenVINO™ that can be compiled for arch64 (see `build instructions `_). @endsphinxdirective -## Development and Target Platforms +## Development and Target Systems @sphinxdirective .. tab:: Operating Systems - * Raspbian Buster, 32-bit - * Raspbian Stretch, 32-bit + * Raspbian Buster, ARM, 32-bit + * Raspbian Stretch, ARM, 32-bit .. tab:: Hardware @@ -26,38 +26,37 @@ .. tab:: Software Requirements * CMake 3.7.2 or higher - * Python 3.7-3.8, 32-bit + * Python 3.7 - 3.10, 32-bit @endsphinxdirective -## Overview - -This guide provides step-by-step instructions on how to install the Intel® Distribution of OpenVINO™ toolkit for Raspbian OS. The following steps will be covered: - -1. Install the Intel® Distribution of OpenVINO™ Toolkit -2. Install External Software Dependencies -3. Configure the Environment -4. Add USB rules for an Intel® Neural Compute Stick 2 device (Optional) -6. Learn About Workflow for Raspberry Pi (Optional) - -## Step 1: Install the Intel® Distribution of OpenVINO™ Toolkit +## Step 1: Download and Install OpenVINO Runtime 1. Open the Terminal or your preferred console application. -2. Go to the directory in which you downloaded the Intel® Distribution of OpenVINO™ toolkit. This document assumes this is your `~/Downloads` directory. If not, replace `~/Downloads` with the directory where the file is located. +2. Create an installation folder for OpenVINO. If the folder already exists, skip this step. + ```sh + sudo mkdir -p /opt/intel + ``` + > **NOTE**: 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 [OpenVINO package repository](https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/linux/). ```sh cd ~/Downloads/ + sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/linux/l_openvino_toolkit_debian9_arm_2022.2.0.7713.af16ea1d79a_armhf.tgz -O openvino_2022.2.0.7713.tgz ``` - By default, the package file is saved as `l_openvino_toolkit_runtime_raspbian_p_.tgz`. -3. Create an installation folder. +4. Extract the archive file and move it to the installation folder: ```sh - sudo mkdir -p /opt/intel/openvino_2022 + sudo tar -xf openvino_2022.2.0.7713.tgz + sudo mv l_openvino_toolkit_debian9_arm_2022.2.0.7713.af16ea1d79a_armhf /opt/intel/openvino_2022.2.0.7713 ``` -4. Unpack the archive: +5. For simplicity, it is useful to create a symbolic link as below: ```sh - sudo tar -xf l_openvino_toolkit_runtime_raspbian_p_.tgz --strip 2 -C /opt/intel/openvino_2022 + sudo ln -s openvino_2022.2.0.7713 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. -Now the OpenVINO™ toolkit components are installed. Additional configuration steps are still required. Continue to the next sections to install External Software Dependencies, configure the environment and set up USB rules. + +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, for example, `/home//intel/`, OpenVINO is then installed in `/home//intel/openvino_2022`. The path to the `openvino_2022` directory is also referred as `` throughout the OpenVINO documentation. ## Step 2: Install External Software Dependencies @@ -70,29 +69,79 @@ CMake is installed. Continue to the next section to set the environment variable ## Step 3: Set the Environment Variables -You must update several environment variables before you can compile and run OpenVINO™ toolkit applications. Run the following script to temporarily set the environment variables: +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 is not `/opt/intel/openvino_2022`, use the correct one instead. + ```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 `setupvars.sh` of your choice. +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. -> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source /opt/intel/openvino_2022/bin/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. +> **NOTE**: The above command must be re-run every time you start a new terminal session. To set up Linux to automatically run the command every time a new terminal is opened, open `~/.bashrc` 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 `.bashrc` is not recommended when you have multiple OpenVINO versions on your machine and want to switch among them. -The environment variables are set. Next, you can download some additional tools. +The environment variables are set. Continue to the next section if you want to download any additional components. -## Step 4 (Optional): Add USB Rules for an Intel® Neural Compute Stick 2 device +### Step 4 (Optional): Install Additional Components + +If you want to use your model for inference, the model must be converted to the .bin and .xml Intermediate Representation (IR) files that are used as input by OpenVINO Runtime. To get the optimized models, you can use one of the following options: + +* Download public and Intel's pre-trained models from the [Open Model Zoo](https://github.com/openvinotoolkit/open_model_zoo) using [Model Downloader tool](@ref omz_tools_downloader). For more information on pre-trained models, see [Pre-Trained Models Documentation](@ref omz_models_group_intel). + - 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). + +* Convert the models using the Model Optimizer. Model Optimizer is provided with OpenVINO Development Tools. + - 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. See the [Install OpenVINO Development Tools](installing-model-dev-tools.md) page for step-by-step installation instructions. + + +## Step 5 (Optional): Add USB Rules for an Intel® Neural Compute Stick 2 device @sphinxdirective -Only if you want to perform inference on Intel® Neural Compute Stick 2, follow the steps on :ref:`NCS2 Setup Guide `. +To perform inference on Intel® Neural Compute Stick 2, follow the steps in :ref:`NCS2 Setup Guide `. @endsphinxdirective -## Step 5 (Optional): Workflow for Raspberry Pi +## What's Next? +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. -If you want to use your model for inference, the model must be converted to the .bin and .xml Intermediate Representation (IR) files that are used as input by OpenVINO Runtime. The installation on Raspberry Pi only includes OpenVINO Runtime. Model Optimizer is available on [pypi.org](https://pypi.org/project/openvino-dev/). To get the optimized models, you can use one of the following options: +@sphinxdirective +.. tab:: Get started with Python -* Download public and Intel's pre-trained models from the [Open Model Zoo](https://github.com/openvinotoolkit/open_model_zoo) using [Model Downloader tool](@ref omz_tools_downloader). For more information on pre-trained models, see [Pre-Trained Models Documentation](@ref omz_models_group_intel) + Try the `Python Quick Start Example `_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser. -* Convert the models using the Model Optimizer. + .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif + :width: 400 + + Visit the :ref:`Tutorials ` page for more Jupyter Notebooks to get you started with OpenVINO, such as: + + * `OpenVINO Python API Tutorial `_ + * `Basic image classification program with Hello Image Classification `_ + * `Convert a PyTorch model and use it for image background removal `_ + +.. tab:: Get started with C++ + + Try the `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 + :width: 400 + + Visit the :ref:`Samples ` page for other C++ example applications to get you started with OpenVINO, such as: + + * `Basic object detection with the Hello Reshape SSD C++ sample `_ + * `Automatic speech recognition C++ sample `_ + +@endsphinxdirective + +To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md). + +## Additional Resources +@sphinxdirective + +* :ref:`Troubleshooting Guide for OpenVINO Installation & Configuration ` +* Converting models for use with OpenVINO™: :ref:`Model Optimizer User Guide ` +* 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`_ +.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit + +@endsphinxdirective