Fix label_to_idx for hierarchical classification

[GalyaZalesskaya]

Summary

Issue CVS-132079

Change label_to_idx to represent the model outputs order.
For h-cls the labels order from model outputs and label_scema differ that caused fixes like PR#2440

The problem that after moving OpenVINO inference to Model API side, Model API required adding function to fix labels order for h-cls.

So I fixed label_to_idx dict to update label order without changes in Model API.
Updated order for labels and label_ids in .XML <model_info> meta to adjust to model outputs for Geti to pick saliency maps of the correct class index.

Validation on Geti passed

How to test

Checklist

• I have added unit tests to cover my changes.​
• I have added integration tests to cover my changes.​
• I have added e2e tests for validation.
• I have added the description of my changes into CHANGELOG in my target branch (e.g., CHANGELOG in develop).​
• I have updated the documentation in my target branch accordingly (e.g., documentation in develop).
• I have linked related issues.

License

• I submit my code changes under the same Apache License that covers the project.
  Feel free to contact the maintainers if that's a concern.
• I have updated the license header for each file (see an example below).

# Copyright (C) 2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0

[codecov]

Codecov Report

Attention: 2 lines in your changes are missing coverage. Please review.

Comparison is base (1a91b0b) 79.62% compared to head (9dd1254) 79.61%.

Files	Patch %	Lines
...lgorithms/classification/adapters/openvino/task.py	75.00%	1 Missing ⚠️
...ortable_code/prediction_to_annotation_converter.py	87.50%	1 Missing ⚠️

Additional details and impacted files

@@                Coverage Diff                 @@
##           releases/1.4.0    #2906      +/-   ##
==================================================
- Coverage           79.62%   79.61%   -0.01%     
==================================================
  Files                 506      506              
  Lines               38313    38317       +4     
==================================================
+ Hits                30505    30507       +2     
- Misses               7808     7810       +2     

Flag	Coverage Δ
py310	79.59% <92.30%> (-0.01%)	⬇️
py38	79.57% <92.30%> (-0.01%)	⬇️
py39	79.56% <92.30%> (-0.02%)	⬇️

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[GalyaZalesskaya]

@sovrasov @chuneuny-emily @sungmanc Can you please check if all suggestions are resolved?