- class torchvision.datapoints.Mask(data: Any, *, dtype: Optional[dtype] = None, device: Optional[Union[device, str, int]] = None, requires_grad: Optional[bool] = None)[source]¶
torch.Tensorsubclass for segmentation and detection masks.
data (tensor-like, PIL.Image.Image) – Any data that can be turned into a tensor with
torch.as_tensor()as well as PIL images.
dtype (torch.dpython:type, optional) – Desired data type of the bounding box. If omitted, will be inferred from
device (torch.device, optional) – Desired device of the bounding box. If omitted and
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
torch.Tensor, the value is taken from it. Otherwise, defaults to
Getting started with transforms v2Getting started with transforms v2Datapoints FAQ