Mask¶

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

torch.Tensor subclass for segmentation and detection masks.

Parameters:

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. If omitted, will be inferred from data.
device (torch.device, optional) – Desired device. If omitted and data is a torch.Tensor, the device is taken from it. Otherwise, the mask is constructed on the CPU.
requires_grad (bool, optional) – Whether autograd should record operations. If omitted and data is a torch.Tensor, the value is taken from it. Otherwise, defaults to False.

Examples using Mask:

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