Table of Contents
Shortcuts

# BoundingBoxes

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)

  [BETA] `torch.Tensor` subclass for bounding boxes.

  Note

  There should be only one `BoundingBoxes` instance 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 from `data`.

    - device (torch.device, optional) – Desired device of the bounding box. If omitted and `data` is a `torch.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 and `data` is a `torch.Tensor`, the value is taken from it. Otherwise, defaults to `False`.

## Docs

Access comprehensive developer documentation for PyTorch

View Docs

## Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

## Resources

Find development resources and get your questions answered

View Resources

To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.