feat(hesai): implement mask-based pruning filter for Hesai

[mojomex]

PR Type

• New Feature

Related Links

• feat: mask-based pruning filter (vendor independent) #250 -- based on this PR

Description

⚠️ #250 has to be merged first ⚠️

This PR implements the mask-based pruning filter introduced in #250 for all Hesai sensors. For more specifics on sensor configuration changes and filter behavior, see #250.

Review Procedure

• Test whether pointcloud output is as expected when not specifying a filter
• Try and create a downsample mask, e.g. in GIMP, and see if it works expected

Pre-Review Checklist for the PR Author

PR Author should check the checkboxes below when creating the PR.

• Assign PR to reviewer

Checklist for the PR Reviewer

Reviewers should check the checkboxes below before approval.

• Commits are properly organized and messages are according to the guideline
• (Optional) Unit tests have been written for new behavior
• PR title describes the changes

Post-Review Checklist for the PR Author

PR Author should check the checkboxes below before merging.

• All open points are addressed and tracked via issues or tickets

CI Checks

• Build and test for PR: Required to pass before the merge.

[mojomex]

🟢 Self-Evaluation

🟢 Performance

Take-aways:

• Performance impact is near 0 or negative (as in, performance improves when using the filter)
  • A disabled filter, and a filter that keeps all points, perform as well as the baseline before this PR
  • A filter discarding 50 % of points improves mean decode time by 7.4 %
  • A filter discarding all points improves mean decode time by 30.3 %

The below performance measurements have been performed with a modified decoder that measures timings of the convert_returns function and accumulates them for one scan. The filter for invalid points (distance == 0) has been disabled, as have other distance checks, to keep the number of input points artificially high ("worst-case"). The decoded number of points per cloud was around 460.000 which is around 2/3 of the maximum possible output in high-res+dual-return mode for OT128.

label	('total_time', 'count')	('total_time', 'mean')	('total_time', 'std')	('total_time', 'min')	('total_time', '50%')	('total_time', 'max')
baseline	942	10.3296	0.390481	9.06057	10.3843	12.149
disabled	941	10.1409	0.296578	9.07079	10.0777	10.852
discard_all	941	7.19801	0.175469	6.94406	7.22401	7.68576
discard_half	940	9.56162	0.22284	9.16713	9.4687	10.6639
keep_all	940	10.2512	0.278572	9.13494	10.172	10.8176

[codecov]

Codecov Report

Attention: Patch coverage is 58.69565% with 57 lines in your changes missing coverage. Please review.

Project coverage is 27.62%. Comparing base (97959dd) to head (cb20367).
Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
..._decoders_common/point_filters/downsample_mask.hpp	66.66%	15 Missing and 2 partials ⚠️
nebula_ros/src/hesai/hesai_ros_wrapper.cpp	0.00%	17 Missing ⚠️
...oders/tests/point_filters/test_downsample_mask.cpp	79.59%	0 Missing and 10 partials ⚠️
...s/nebula_decoders_hesai/decoders/hesai_decoder.hpp	40.00%	4 Missing and 2 partials ⚠️
nebula_ros/src/hesai/decoder_wrapper.cpp	0.00%	5 Missing ⚠️
.../nebula_decoders/nebula_decoders_common/angles.hpp	0.00%	0 Missing and 1 partial ⚠️
...ecoders/src/nebula_decoders_hesai/hesai_driver.cpp	66.66%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #251      +/-   ##
==========================================
+ Coverage   26.07%   27.62%   +1.54%     
==========================================
  Files         101      107       +6     
  Lines        9232     9580     +348     
  Branches     2213     2387     +174     
==========================================
+ Hits         2407     2646     +239     
- Misses       6436     6484      +48     
- Partials      389      450      +61     

Flag	Coverage Δ
differential	27.62% <58.69%> (?)
total	?

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