Enhance Panoptic Quality implementation #1527
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marcocaccin
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Feb 20, 2023
marcocaccin
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Feb 20, 2023
marcocaccin
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Feb 20, 2023
marcocaccin
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Feb 20, 2023
marcocaccin
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Feb 20, 2023
marcocaccin
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Feb 20, 2023
| raise TypeError(f"Expected argument `target` to be of type `torch.Tensor`, but got {type(target)}") | ||
| if preds.shape != target.shape: | ||
| raise ValueError( | ||
| f"Expected argument `preds` and `target` to have the same shape, but got {preds.shape} and {target.shape}" | ||
| ) | ||
| if preds.dim() != 3 or preds.shape[-1] != 2: | ||
| raise ValueError(f"Expected argument `preds` to have shape [height, width, 2], but got {preds.shape}") | ||
| if preds.dim() < 3: |
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Question: what's the best way to deal with an unknown number of spatial dimensions? Here I just say "anything > 0 is fine", but maybe we want to restrict to just point clouds and images (but why no voxels..., and so on)?
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That is veru good question, so lets play with it in follow-up PR :)
cc: @Lightning-AI/core-metrics
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Codecov Report
Additional details and impacted files@@ Coverage Diff @@
## master #1527 +/- ##
========================================
- Coverage 88% 37% -51%
========================================
Files 219 219
Lines 11473 11497 +24
========================================
- Hits 10069 4277 -5792
- Misses 1404 7220 +5816 |
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Co-authored-by: Nicki Skafte Detlefsen <[email protected]>
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What does this PR do?
Fixes #1511:
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