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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]

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