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Update Raspbian OS installation for 22/3 (#14628)

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* update Raspbian OS installation

* test formatting

* fix formatting

* Apply suggestions from code review

* update version number & package names
This commit is contained in:
Yuan Xu
2022-12-22 12:59:03 +08:00
committed by GitHub
parent 578e979334
commit 0990540083
1 changed files with 64 additions and 29 deletions
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93
docs/install_guides/installing-openvino-raspbian.md
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@@ -12,12 +12,12 @@
@sphinxdirective
.. tab:: Operating Systems
* Raspbian Buster, ARM, 32-bit
* Raspbian Stretch, ARM, 32-bit
* Raspbian Buster, ARM, 32-bit & 64-bit
* Raspbian Stretch, ARM, 32-bit & 64-bit
.. tab:: Hardware
* Raspberry Pi board with ARM ARMv7-A CPU architecture. Check that `uname -m` returns `armv7l`.
* Raspberry Pi board with ARM ARMv7-A CPU architecture. To check that, run `uname -m` to see if it returns `armv7l`.
* Intel® Neural Compute Stick 2, which as one of the Intel® Movidius™ Visual Processing Units (VPUs)
.. note::
@@ -32,33 +32,68 @@
## <a name="install-openvino"></a>Step 1: Download and Install OpenVINO Runtime
@sphinxdirective
1. Open the Terminal or your preferred console application.
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/<USER>/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
```
.. code-block:: 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/<USER>/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/2022.3/linux/>`_.
.. tab:: ARM 32-bit
.. code-block:: sh
cd ~/Downloads/
sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3/linux/l_openvino_toolkit_debian9_2022.3.0.9052.9752fafe8eb_armhf.tgz -O openvino_2022.3.0.tgz
.. tab:: ARM 64-bit
.. code-block:: sh
cd ~/Downloads/
sudo wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3/linux/l_openvino_toolkit_debian9_2022.3.0.9052.9752fafe8eb_arm64.tgz -O openvino_2022.3.0.tgz
4. Extract the archive file and move it to the installation folder:
```sh
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
```
5. Install required system dependencies on Linux. To do this, OpenVINO provides a script in the extracted installation directory. Run the following command:
```sh
sudo -E ./install_dependencies/install_openvino_dependencies.sh
```
6. For simplicity, it is useful to create a symbolic link as below:
```sh
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.
.. tab:: ARM 32-bit
.. code-block:: sh
sudo tar -xf openvino_2022.3.0.tgz
sudo mv l_openvino_toolkit_debian9_2022.3.0.9052.9752fafe8eb_armhf /opt/intel/openvino_2022.3.0
.. tab:: ARM 64-bit
.. code-block:: sh
sudo tar -xf openvino_2022.3.0.tgz
sudo mv l_openvino_toolkit_debian9_2022.3.0.9052.9752fafe8eb_arm64 /opt/intel/openvino_2022.3.0
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
sudo -E ./install_dependencies/install_openvino_dependencies.sh
6. For simplicity, it is useful to create a symbolic link as below:
.. code-block:: sh
sudo ln -s openvino_2022.3.0 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.
@endsphinxdirective
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/<USER>/intel/`, OpenVINO is then installed in `/home/<USER>/intel/openvino_2022`. The path to the `openvino_2022` directory is also referred as `<INSTALL_DIR>` throughout the OpenVINO documentation.
@@ -110,16 +145,16 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
@sphinxdirective
.. tab:: Get started with Python
Try the `Python Quick Start Example <https://docs.openvino.ai/nightly/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.
Try the `Python Quick Start Example <https://docs.openvino.ai/2022.3/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.
.. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
:width: 400
Visit the :ref:`Tutorials <notebook tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
* `OpenVINO Python API Tutorial <https://docs.openvino.ai/nightly/notebooks/002-openvino-api-with-output.html>`_
* `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/nightly/notebooks/001-hello-world-with-output.html>`_
* `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/nightly/notebooks/205-vision-background-removal-with-output.html>`_
* `OpenVINO Python API Tutorial <https://docs.openvino.ai/2022.3/notebooks/002-openvino-api-with-output.html>`_
* `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2022.3/notebooks/001-hello-world-with-output.html>`_
* `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2022.3/notebooks/205-vision-background-removal-with-output.html>`_
.. tab:: Get started with C++