[Feature] Support LaPa Dataset

[Tau-J]

Motivation

• A 106-points Face landmark dataset
• support dataset class
• dataset description in docs
• dataset converter script
• unit test
• tests/data

Modification

BC-breaking (Optional)

Use cases (Optional)

Checklist

Before PR:

• I have read and followed the workflow indicated in the CONTRIBUTING.md to create this PR.
• Pre-commit or linting tools indicated in CONTRIBUTING.md are used to fix the potential lint issues.
• Bug fixes are covered by unit tests, the case that causes the bug should be added in the unit tests.
• New functionalities are covered by complete unit tests. If not, please add more unit tests to ensure correctness.
• The documentation has been modified accordingly, including docstring or example tutorials.

After PR:

• CLA has been signed and all committers have signed the CLA in this PR.

[codecov]

Codecov Report

Patch coverage: 100.00% and project coverage change: -0.03 ⚠️

Comparison is base (260d05c) 82.31% compared to head (8daec3b) 82.29%.

❗ Current head 8daec3b differs from pull request most recent head 3d593ec. Consider uploading reports for the commit 3d593ec to get more accurate results

Additional details and impacted files

@@             Coverage Diff             @@
##           dev-1.x    #2281      +/-   ##
===========================================
- Coverage    82.31%   82.29%   -0.03%     
===========================================
  Files          230      231       +1     
  Lines        13552    13576      +24     
  Branches      2301     2306       +5     
===========================================
+ Hits         11155    11172      +17     
- Misses        1866     1872       +6     
- Partials       531      532       +1     

Flag	Coverage Δ
unittests	82.29% <100.00%> (-0.03%)	⬇️

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

Impacted Files	Coverage Δ
mmpose/datasets/datasets/face/__init__.py	100.00% <100.00%> (ø)
mmpose/datasets/datasets/face/lapa_dataset.py	100.00% <100.00%> (ø)
mmpose/datasets/transforms/converting.py	92.68% <100.00%> (+5.72%)	⬆️

... and 2 files with indirect coverage changes

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