Rename panoptic seg related and Realse instance seg related for Mask2Former

[chhluo]

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Motivation

1. Rename configs for panoptic segmentation.
2. Release configs, logs and checkpoints for instance segmentation. For instance segmentation, We have trained the models for many times with the algorithm we implemented (see PR 7571), and the performance of the trained models is relatively stable (+- 0.2), and there is a certain gap between the performance of the models we trained and the results mentioned in the paper. However, the performance of the model trained with the official code are unstable, and the performance may be lower than the target results (see issue).
3. fix bug in gather_models.py

Modification

1. Rename configs for panoptic segmentation: mask2former_xxx_coco.py -> mask2former_xxx_coco-panoptic.py. mask2former_xxx_coco.py is for instance segmentation, while mask2former_xxx_coco-panoptic.py for panoptic segmentation.

BC-breaking (Optional)

Rename configs for panoptic segmentation: mask2former_xxx_coco.py -> mask2former_xxx_coco-panoptic.py. mask2former_xxx_coco.py is for instance segmentation, while mask2former_xxx_coco-panoptic.py for panoptic segmentation.

Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases here, and update the documentation.

Checklist

1. Pre-commit or other linting tools are used to fix the potential lint issues.
2. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects, like MMDet or MMCls.
4. The documentation has been modified accordingly, like docstring or example tutorials.

[codecov]

Codecov Report

Merging #8032 (a6719dc) into dev (c32894e) will increase coverage by 0.05%.
The diff coverage is n/a.

❗ Current head a6719dc differs from pull request most recent head f8c575f. Consider uploading reports for the commit f8c575f to get more accurate results

@@            Coverage Diff             @@
##              dev    #8032      +/-   ##
==========================================
+ Coverage   64.51%   64.56%   +0.05%     
==========================================
  Files         360      359       -1     
  Lines       29233    29155      -78     
  Branches     4954     4938      -16     
==========================================
- Hits        18859    18825      -34     
+ Misses       9370     9329      -41     
+ Partials     1004     1001       -3     

Flag	Coverage Δ
unittests	64.55% <ø> (+0.06%)	⬆️

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

Impacted Files	Coverage Δ
mmdet/utils/setup_env.py	88.00% <0.00%> (-4.00%)	⬇️
mmdet/core/bbox/assigners/sim_ota_assigner.py	80.00% <0.00%> (-3.64%)	⬇️
mmdet/models/roi_heads/mask_heads/maskiou_head.py	87.35% <0.00%> (-2.30%)	⬇️
mmdet/datasets/builder.py	52.08% <0.00%> (-1.05%)	⬇️
mmdet/utils/__init__.py	100.00% <0.00%> (ø)
mmdet/utils/memory.py
...ds/panoptic_fusion_heads/maskformer_fusion_head.py	76.92% <0.00%> (+1.09%)	⬆️
mmdet/models/detectors/maskformer.py	70.00% <0.00%> (+1.42%)	⬆️
mmdet/core/bbox/samplers/random_sampler.py	80.55% <0.00%> (+5.55%)	⬆️
mmdet/models/utils/panoptic_gt_processing.py	100.00% <0.00%> (+8.33%)	⬆️

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[Levine66]

Hey, thanks for all of your work for Mask2Former. Recently, i am learning the code of MPFomer, which is modified from Mask2Former, and the only differences between MPFormer and Mask2Fomer are in mask2former_transformer_decoder.py and criterion.py which construct the MP training queries and loss function. I would like to convert the code from Detectron2 to MMDetection, but i am confused that I can't find the part(mask2former_transformer_decoder.py) they modified in MMDetection, it makes me hard to rewrite the code in MMDetection. So i would like to ask you guys to give me some advices to implement thisk work your time permits.

[chhluo]

@Levine66, Code related to transformer decoder is in https://github.com/open-mmlab/mmdetection/blob/2.x/mmdet/models/utils/transformer.py.