Fix bug in segmentation postprocessing
# What does this PR do?
- Fixes bug in `MaskFormerFeatureExtractor.compute_segments()` that causes an error when label_ids_to_fuse is set to None during instance and panoptic segmentation post-processing. 
- Adds test to check if target labels are fused correctly


Fixes #20132


## Before submitting
- [X ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? 
https://github.com/huggingface/transformers/issues/20132



_The documentation is not available anymore as the PR was closed or merged._<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20198). All of your documentation changes will be reflected on that endpoint.<|||||>> Could you add a corresponding test for this?

Added a test to `test_feature_extraction_maskformer.py` to test label fusing, I think I covered all cases but the test might still be a bit flaky due to using dummy model outputs.<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20198). All of your documentation changes will be reflected on that endpoint.<|||||>@NielsRogge I thought this issue was fixed with the ImageProcessor PR but the MaskFormer instance segmentation post-processing issue still persists. I updated the PR and added a test for label fusing. Could you take another look and approve if everything looks good?<|||||>> PR looks good to me, except that modeling_vit.py should not be changed

The changes are reverted, could you take another look? <|||||>> Thanks for fixing!
> 
> However I'm still wondering how MaskFormer would solve instance segmentation datasets which have overlapping instances, like COCO

We have MaskFormer models trained on the  COCO panoptic and ADE semantic datasets, other models don't have model cards yet. But I can test it if one of the other models is trained on an instance segmentation dataset.

