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

[BETA] torch.Tensor subclass for images.

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 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.

Examples using Image:

Datapoints FAQ

Datapoints FAQ

Getting started with transforms v2

Getting started with transforms v2

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