Source code for torchvision.transforms.v2._deprecated

import warnings
from typing import Any, Dict, Union

import numpy as np
import PIL.Image
import torch
from torchvision.transforms import functional as _F

from torchvision.transforms.v2 import Transform

[docs]class ToTensor(Transform): """[DEPRECATED] Use ``v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])`` instead. Convert a PIL Image or ndarray to tensor and scale the values accordingly. .. warning:: :class:`v2.ToTensor` is deprecated and will be removed in a future release. Please use instead ``v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])``. Output is equivalent up to float precision. This transform does not support torchscript. Converts a PIL Image or numpy.ndarray (H x W x C) in the range [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0] if the PIL Image belongs to one of the modes (L, LA, P, I, F, RGB, YCbCr, RGBA, CMYK, 1) or if the numpy.ndarray has dtype = np.uint8 In the other cases, tensors are returned without scaling. .. note:: Because the input image is scaled to [0.0, 1.0], this transformation should not be used when transforming target image masks. See the `references`_ for implementing the transforms for image masks. .. _references: """ _transformed_types = (PIL.Image.Image, np.ndarray) def __init__(self) -> None: warnings.warn( "The transform `ToTensor()` is deprecated and will be removed in a future release. " "Instead, please use `v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])`." "Output is equivalent up to float precision." ) super().__init__() def _transform(self, inpt: Union[PIL.Image.Image, np.ndarray], params: Dict[str, Any]) -> torch.Tensor: return _F.to_tensor(inpt)


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