Add Corrector transformation

[wonjuleee]

Summary

<style> </style>

anomaly type	info	task	type	target	method
MissingLabelCategories	Metadata (ex. LabelCategories) should be defined	common	error	cat	add
MissingAnnotation	No annotation found for an Item	common	warning	item	remove
MissingAttribute	An attribute key is missing for an Item	common	warning	item	add
UndefinedLabel	A label not defined in the metadata is found for an item	common	error	cat - label	add
UndefinedAttribute	An attribute not defined in the metadata is found for an item	common	error	cat - attr	add
MultiLabelAnnotations	Item needs a single label	classification	error	item	remove
NegativeLength	The width or height of bounding box is negative	detection	error	ann	remove
InvalidValue	There’s invalid (ex. inf, nan) value for bounding box info.	detection	error	ann	remove
FarFromLabelMean	An annotation has an too small or large value than average for a label	detection, segmentation	warning	ann	remove
FarFromAttrMean	An annotation has an too small or large value than average for an attribute	detection, segmentation	warning	ann	remove
LabelDefinedButNotFound	A label is defined, but not found actually	common	warning
AttributeDefinedButNotFound	An attribute is defined, but not found actually	common	warning
OnlyOneLabel	The dataset consists of only label	common	info
OnlyOneAttributeValue	The dataset consists of only attribute value	common	info
FewSamplesInLabel	The number of samples in a label might be too low	common	info
FewSamplesInAttribute	The number of samples in an attribute might be too low	common	info
ImbalancedLabels	There is an imbalance in the label distribution	common	info
ImbalancedAttribute	There is an imbalance in the attribute distribution	common	info
ImbalancedDistInLabel	Values (ex. bbox width) are not evenly distributed for a label	detection, segmentation	info
ImbalancedDistInAttribute	Values (ex. bbox width) are not evenly distributed for an attribute	detection, segmentation	info

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 the description of my changes into CHANGELOG.​
• I have updated the documentation accordingly

License

• I submit my code changes under the same MIT 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: MIT

[codecov-commenter]

Codecov Report

Patch coverage: 70.66% and project coverage change: +0.09 🎉

Comparison is base (1c15093) 78.53% compared to head (d4780fc) 78.63%.

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #1006      +/-   ##
===========================================
+ Coverage    78.53%   78.63%   +0.09%     
===========================================
  Files          233      233              
  Lines        26770    26855      +85     
  Branches      5325     5357      +32     
===========================================
+ Hits         21025    21118      +93     
+ Misses        4496     4493       -3     
+ Partials      1249     1244       -5     

Flag	Coverage Δ
macos-11_Python-3.8	77.64% <70.66%> (+0.10%)	⬆️
ubuntu-20.04_Python-3.8	78.61% <70.66%> (+0.09%)	⬆️
windows-2019_Python-3.8	78.52% <70.66%> (+0.09%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
datumaro/plugins/transforms.py	75.28% <69.86%> (-0.86%)	⬇️
datumaro/components/validator.py	100.00% <100.00%> (ø)
datumaro/plugins/validators.py	94.82% <100.00%> (+4.65%)	⬆️

... and 1 file with indirect coverage changes

☔ View full report in Codecov by Sentry.
📢 Do you have feedback about the report comment? Let us know in this issue.

[review-notebook-app]

Check out this pull request on 

See visual diffs & provide feedback on Jupyter Notebooks.

---

Powered by ReviewNB

[vinnamkim]

LGTM.

[cih9088]

Suggested change

	A user can should feed into validation_reports.json from validator to correct the dataset.
	A user should feed `validation_reports.json` from validator to correct the dataset.