Bump torchmetrics from 1.6.1 to 1.6.2 in /requirements (microsoft#2623)

* Bump torchmetrics from 1.6.1 to 1.6.2 in /requirements

Bumps [torchmetrics](https://github.com/Lightning-AI/torchmetrics) from 1.6.1 to 1.6.2.
- [Release notes](https://github.com/Lightning-AI/torchmetrics/releases)
- [Changelog](https://github.com/Lightning-AI/torchmetrics/blob/master/CHANGELOG.md)
- [Commits](Lightning-AI/torchmetrics@v1.6.1...v1.6.2)

---
updated-dependencies:
- dependency-name: torchmetrics
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <[email protected]>

* Remove type ignores

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Adam J. Stewart <[email protected]>

Author: dependabot[bot]

.pre-commit-config.yaml

@@ -29,9 +29,9 @@ repos:
           - pillow>=10.4.0
           - pytest>=6.1.2
           - scikit-image>=0.22.0
-          - timm>=1.0.14
+          - timm>=1.0.15
           - torch>=2.6
-          - torchmetrics>=0.10
+          - torchmetrics>=1.6.2
           - torchvision>=0.18
         exclude: (build|data|dist|logo|logs|output)/
   - repo: https://github.com/pre-commit/mirrors-prettier

requirements/required.txt

@@ -18,6 +18,6 @@ segmentation-models-pytorch==0.4.0
 shapely==2.0.7
 timm==1.0.15
 torch==2.6.0
-torchmetrics==1.6.1
+torchmetrics==1.6.2
 torchvision==0.21.0
 typing-extensions==4.12.2

torchgeo/trainers/instance_segmentation.py

@@ -117,7 +117,7 @@ def configure_metrics(self) -> None:
            * 'Macro' averaging gives equal weight to each class, and is useful for
              balanced performance assessment across imbalanced classes.
         """
-        metrics = MetricCollection([MeanAveragePrecision(iou_type=('bbox', 'segm'))])  # type: ignore[arg-type]
+        metrics = MetricCollection([MeanAveragePrecision(iou_type=('bbox', 'segm'))])
         self.val_metrics = metrics.clone(prefix='val_')
         self.test_metrics = metrics.clone(prefix='test_')