ToDtype

class torchvision.transforms.v2.ToDtype(dtype: Union[dtype, Dict[Union[Type, str], Optional[dtype]]], scale: bool = False)

[BETA] Converts the input to a specific dtype, optionally scaling the values for images or videos.

Note

The ToDtype transform is in Beta stage, and while we do not expect disruptive breaking changes, some APIs may slightly change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753.

Note

ToDtype(dtype, scale=True) is the recommended replacement for ConvertImageDtype(dtype).

Parameters:

• dtype (torch.dtype or dict of TVTensor -> torch.dtype) – The dtype to convert to. If a torch.dtype is passed, e.g. torch.float32, only images and videos will be converted to that dtype: this is for compatibility with ConvertImageDtype. A dict can be passed to specify per-tv_tensor conversions, e.g. dtype={tv_tensors.Image: torch.float32, tv_tensors.Mask: torch.int64, "others":None}. The “others” key can be used as a catch-all for any other tv_tensor type, and None means no conversion.

• scale (bool, optional) – Whether to scale the values for images or videos. See Dtype and expected value range. Default: False.

Examples using ToDtype:

Getting started with transforms v2

Getting started with transforms v2

Transforms v2: End-to-end object detection/segmentation example

Transforms v2: End-to-end object detection/segmentation example

How to use CutMix and MixUp

How to use CutMix and MixUp