📚 Add OpenVINO Inference to getting started notebook.

[samet-akcay]

Description

• This PR updates the getting started notebook to include the OpenVINO inference. The primary goal is to quickly explain the connection between "anomalib" and "OpenVINO," particularly to people who are unfamiliar with either of these libraries.

Changes

• Bug fix (non-breaking change which fixes an issue)
• Refactor (non-breaking change which refactors the code base)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Checklist

• My code follows the pre-commit style and check guidelines of this project.
• I have performed a self-review of my code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing tests pass locally with my changes
• I have added a summary of my changes to the CHANGELOG (not for minor changes, docs and tests).

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Codecov Report

Patch and project coverage have no change.

Comparison is base (1407cfc) 86.77% compared to head (ded25a5) 86.77%.

❗ Current head ded25a5 differs from pull request most recent head b352d57. Consider uploading reports for the commit b352d57 to get more accurate results

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #897   +/-   ##
=======================================
  Coverage   86.77%   86.77%           
=======================================
  Files         165      165           
  Lines        6319     6319           
=======================================
  Hits         5483     5483           
  Misses        836      836           

Impacted Files	Coverage Δ
anomalib/data/utils/augmenter.py	98.48% <0.00%> (ø)
anomalib/pre_processing/tiler.py	100.00% <0.00%> (ø)
anomalib/models/csflow/torch_model.py	91.86% <0.00%> (ø)
anomalib/models/rkde/region_extractor.py	85.41% <0.00%> (ø)
anomalib/models/ganomaly/lightning_model.py	100.00% <0.00%> (ø)
anomalib/deploy/inferencers/torch_inferencer.py	87.23% <0.00%> (ø)

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[djdameln]

Why do we show OpenVINO inference here, and not PL inference. Isn't PL inference the recommended way to run inference?