Comments (1)
That would be a great improvement @maximsch2, and from the gist it already seems like you have nearly done the hard work. Please feel free to send a PR :]
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Related Issues (20)
- The default value of `compute_with_cache` should be `True` . HOT 2
- Bug in ERGAS HOT 2
- Ordinal classification metrics HOT 1
- Binary Classification Expected Calibration Error HOT 2
- `intersection_over_union` error HOT 2
- Clarify that nan is supported in zero_division HOT 4
- Add `_filter_kwargs` in `ClasswiseWrapper` metric wrapper HOT 3
- `MetricTracker` use `higher_is_better` as default for maximize HOT 2
- Unpredictable class order when `panoptic_quality(..., return_per_class=True)`
- torchmetrics Accuracy HOT 8
- BootStrapper.reset() does not reset properly
- segmentation.MeanIoU is wrong HOT 3
- DataLoader worker is killed in Docker HOT 4
- MeanAveragePrecision - bug in `max_detection_thresholds` HOT 3
- Documentation of ERGAS HOT 1
- Support for DLM (AIM) metric HOT 1
- Error for index tensor verification in GeneralizedDice if target is zeros HOT 1
- Incorrect caching (`m._compute`) of metrics inside a `MetricCollection` if `compute_groups` are used and `.compute` is called twice HOT 1
- Classification Report, maybe with the option to select even more metrics HOT 1
- `MeanAveragePrecision.tm_to_coco` example fails with `IndexError: list index out of range` HOT 1
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