BoundingBoxes — Torchvision 0.22 documentation (original) (raw)

class torchvision.tv_tensors.BoundingBoxes(data: Any, *, format: Union[BoundingBoxFormat, str], canvas_size: Tuple[int, int], dtype: Optional[dtype] = None, device: Optional[Union[device, str, int]] = None, requires_grad: Optional[bool] = None)[source]¶

torch.Tensor subclass for bounding boxes with shape [N, 4].

Note

There should be only one BoundingBoxesinstance per sample e.g. {"img": img, "bbox": BoundingBoxes(...)}, although one BoundingBoxes object can contain multiple bounding boxes.

Parameters:

• data – Any data that can be turned into a tensor with torch.as_tensor().
• format (BoundingBoxFormat, str) – Format of the bounding box.
• canvas_size (two-tuple of python:ints) – Height and width of the corresponding image or video.
• dtype (torch.dpython:type , optional) – Desired data type of the bounding box. If omitted, will be inferred fromdata.
• device (torch.device, optional) – Desired device of the bounding box. If omitted and data is atorch.Tensor, the device is taken from it. Otherwise, the bounding box is constructed on the CPU.
• requires_grad (bool, optional) – Whether autograd should record operations on the bounding box. If omitted anddata is a torch.Tensor, the value is taken from it. Otherwise, defaults to False.

Examples using BoundingBoxes: