Created KITTI dataset for segmentation in autonomous driving scenario

[TimoK93]

Note that this PR is a modified version of the withdrawn PR #1748

Motivation

In the last years, panoptic segmentation has become more into the focus in reseach. Weber et al. [Link] have published a quite nice dataset, which is in the same style like Cityscapes, but for KITTI sequences. Since Cityscapes and KITTI-STEP share the same classes and also a comparable domain (dashcam view), interesting investigations, e.g. about relations in the domain e.t.c. can be done.

Note that KITTI-STEP provices panoptic segmentation annotations which are out of scope for mmsegmentation.

Modification

Mostly, I added the new dataset and dataset preparation file. To simplify the first usage of the new dataset, I also added configs for the dataset, segformer and deeplabv3plus.

BC-breaking (Optional)

No BC-breaking

Use cases (Optional)

Researchers want to test their new methods, e.g. for interpretable AI in the context of semantic segmentation. They want to show, that their method is reproducible on comparable datasets. Thus, they can compare Cityscapes and KITTI-STEP.

[MeowZheng]

thanks again for your contribution. we are working on reviewing it.

[codecov]

Codecov Report

Patch coverage: 36.84% and project coverage change: -0.22 ⚠️

Comparison is base (ae78cb9) 88.13% compared to head (aa64995) 87.91%.

❗ Current head aa64995 differs from pull request most recent head e168393. Consider uploading reports for the commit e168393 to get more accurate results

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2730      +/-   ##
==========================================
- Coverage   88.13%   87.91%   -0.22%     
==========================================
  Files         149      150       +1     
  Lines        9183     9221      +38     
  Branches     1539     1544       +5     
==========================================
+ Hits         8093     8107      +14     
- Misses        835      859      +24     
  Partials      255      255              

Flag	Coverage Δ
unittests	87.91% <36.84%> (-0.22%)	⬇️

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Impacted Files	Coverage Δ
mmseg/datasets/kitti_step.py	35.13% <35.13%> (ø)
mmseg/datasets/__init__.py	100.00% <100.00%> (ø)

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