Method __call__

monai/transforms/croppad/array.py:518–529

Apply the transform to `img`, assuming `img` is channel-first and slicing doesn't apply to the channel dim.

(self, img: torch.Tensor, lazy: bool | None = None)

        return super().compute_slices(roi_center=roi_center, roi_size=roi_size)

    def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:  # type: ignore[override]
        """
        Apply the transform to `img`, assuming `img` is channel-first and
        slicing doesn't apply to the channel dim.

        """
        lazy_ = self.lazy if lazy is None else lazy
        return super().__call__(
            img=img,
            slices=self.compute_slices(img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]),
            lazy=lazy_,
        )


class CenterScaleCrop(Crop):