Lightning-AI / Lightning-AI/torchmetrics
One-sided empty inputs are weighted inconsistently in intersection metrics
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- Dominant language
- Python
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Description
I ran into two related one-sided empty cases in the class-based IoU, GIoU, DIoU, and CIoU metrics.
With `respect_labels=False`, one perfect match plus two unmatched boxes returns `0.2` instead of `1/3`. With `class_metrics=True`, predictions against an empty target also raise.
I checked #2805 and #2806. Those fixed the original empty-input behavior, but these cases remain. I have a small fix and regression tests ready across all four metrics, both empty directions, both label modes, and class metrics on/off :)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the class-based IoU, GIoU, DIoU, and CIoU metric implementations and their existing tests. Reproduce both one-sided empty-input cases with respect_labels and class_metrics enabled and disabled, then add regression coverage for both empty directions; done means all four metrics return the intended values without raising.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, testing-qa
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 68/100