* feat: add with_nms() method to KeyPoints class Derive axis-aligned bounding boxes from valid keypoints and delegate to box_non_max_suppression for filtering. Requires detection_confidence; supports class-aware and class-agnostic modes.
- Add overlap_metric: OverlapMetric = OverlapMetric.IOU param to KeyPoints.with_nms() for API parity with Detections.with_nms()
- Integrate self.visible into keypoint validity: valid = valid & self.visible when visible is not None
- Pass overlap_metric through to box_non_max_suppression
- Fix docstring: add Defaults to for threshold/class_agnostic, threshold range constraint, overlap_metric arg
- Add UnReleased changelog entry
- Add 5 new test cases: all-zero-skeleton-passes-through, visible-mask-excludes-keypoints-from-bbox, single-valid-keypoint-zero-area-bbox, threshold boundary 0.0/1.0
- Add missing raises test: no-detection-confidence-class-agnostic
- Update `with_nms` method to raise `ValueError` instead of `AssertionError` for missing required fields (`detection_confidence`, `class_id` when `class_agnostic=False`).
- Adjust corresponding test to check for `ValueError` with match argument.
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Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
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