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):
"""[BETA] Convert a PIL Image or ndarray to tensor and scale the values accordingly.
.. v2betastatus:: ToTensor transform
.. warning::
:class:`v2.ToTensor` is deprecated and will be removed in a future release.
Please use instead ``transforms.Compose([transforms.ToImageTensor(), transforms.ConvertImageDtype()])``.
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: https://github.com/pytorch/vision/tree/main/references/segmentation
"""
_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 `transforms.Compose([transforms.ToImageTensor(), transforms.ConvertImageDtype()])`."
)
super().__init__()
def _transform(self, inpt: Union[PIL.Image.Image, np.ndarray], params: Dict[str, Any]) -> torch.Tensor:
return _F.to_tensor(inpt)