Source code for torchvision.transforms.v2._meta
from typing import Any, Dict, Union
from torchvision import tv_tensors
from torchvision.transforms.v2 import functional as F, Transform
[docs]class ConvertBoundingBoxFormat(Transform):
"""[BETA] Convert bounding box coordinates to the given ``format``, eg from "CXCYWH" to "XYXY".
.. v2betastatus:: ConvertBoundingBoxFormat transform
Args:
format (str or tv_tensors.BoundingBoxFormat): output bounding box format.
Possible values are defined by :class:`~torchvision.tv_tensors.BoundingBoxFormat` and
string values match the enums, e.g. "XYXY" or "XYWH" etc.
"""
_transformed_types = (tv_tensors.BoundingBoxes,)
def __init__(self, format: Union[str, tv_tensors.BoundingBoxFormat]) -> None:
super().__init__()
if isinstance(format, str):
format = tv_tensors.BoundingBoxFormat[format]
self.format = format
def _transform(self, inpt: tv_tensors.BoundingBoxes, params: Dict[str, Any]) -> tv_tensors.BoundingBoxes:
return F.convert_bounding_box_format(inpt, new_format=self.format) # type: ignore[return-value]
[docs]class ClampBoundingBoxes(Transform):
"""[BETA] Clamp bounding boxes to their corresponding image dimensions.
The clamping is done according to the bounding boxes' ``canvas_size`` meta-data.
.. v2betastatus:: ClampBoundingBoxes transform
"""
_transformed_types = (tv_tensors.BoundingBoxes,)
def _transform(self, inpt: tv_tensors.BoundingBoxes, params: Dict[str, Any]) -> tv_tensors.BoundingBoxes:
return F.clamp_bounding_boxes(inpt) # type: ignore[return-value]