| 500 | backend = [TransformBackends.TORCH, TransformBackends.NUMPY] |
| 501 | |
| 502 | def __init__( |
| 503 | self, |
| 504 | roi_center: Sequence[int] | NdarrayOrTensor | None = None, |
| 505 | roi_size: Sequence[int] | NdarrayOrTensor | None = None, |
| 506 | roi_start: Sequence[int] | NdarrayOrTensor | None = None, |
| 507 | roi_end: Sequence[int] | NdarrayOrTensor | None = None, |
| 508 | roi_slices: Sequence[slice] | None = None, |
| 509 | ) -> None: |
| 510 | super().__init__(roi_center, roi_size, roi_start, roi_end, roi_slices) |
| 511 | for s in self.slices: |
| 512 | if s.start < 0 or s.stop < 0 or (s.step is not None and s.step < 0): |
| 513 | raise ValueError("Currently negative indexing is not supported for SpatialCropBox.") |
| 514 | |
| 515 | def __call__( # type: ignore[override] |
| 516 | self, boxes: NdarrayTensor, labels: Sequence[NdarrayOrTensor] | NdarrayOrTensor |