def apply_crop3d(input: torch.Tensor, params: Dict[str, torch.Tensor], flags: Dict[str, torch.Tensor]) -> torch.Tensor:
r"""Apply cropping by src bounding box and dst bounding box.
Args:
input (torch.Tensor): Tensor to be transformed with shape :math:`(*, C, D, H, W)`.
params (Dict[str, torch.Tensor]):
- params['src']: The applied cropping src matrix :math: `(*, 8, 3)`.
- params['dst']: The applied cropping dst matrix :math: `(*, 8, 3)`.
flags (Dict[str, torch.Tensor]):
- params['interpolation']: Integer tensor. NEAREST = 0, BILINEAR = 1.
- params['align_corners']: Boolean tensor.
Returns:
torch.Tensor: The cropped input.
Note:
BBox order: front-top-left, front-top-right, front-bottom-right, front-bottom-left, back-top-left,
back-top-right, back-bottom-right, back-bottom-left. The coordinates must be in x, y, z order.
"""
resample_mode: str = Resample.get(flags['interpolation'].item()).name.lower() # type: ignore
align_corners: bool = cast(bool, flags['align_corners'].item())
return crop_by_boxes3d(
input, params['src'], params['dst'], resample_mode, align_corners=align_corners)
def apply_crop3d(input: torch.Tensor, params: Dict[str, torch.Tensor],
flags: Dict[str, torch.Tensor]) -> torch.Tensor:
r"""Apply cropping by src bounding box and dst bounding box.
Order: front-top-left, front-top-right, front-bottom-right, front-bottom-left, back-top-left,
back-top-right, back-bottom-right, back-bottom-left. The coordinates must be in x, y, z order.
- params['src']: The applied cropping src matrix :math: `(*, 8, 3)`.
- params['dst']: The applied cropping dst matrix :math: `(*, 8, 3)`.
flags (Dict[str, torch.Tensor]):
- params['interpolation']: Integer tensor. NEAREST = 0, BILINEAR = 1.
- params['align_corners']: Boolean tensor.
Returns:
torch.Tensor: The cropped input.
"""
input = _transform_input3d(input)
_validate_input_dtype(
input, accepted_dtypes=[torch.float16, torch.float32, torch.float64])
resample_mode: str = Resample.get(
flags['interpolation'].item()).name.lower() # type: ignore
align_corners: bool = cast(bool, flags['align_corners'].item())
return crop_by_boxes3d(input,
params['src'],
params['dst'],
resample_mode,
align_corners=align_corners)