Function differences with torchvision.transforms.ToPILImage
torchvision.transforms.ToPILImage
class torchvision.transforms.ToPILImage(
mode=None
)
For more information, see torchvision.transforms.ToPILImage.
mindspore.dataset.vision.ToPIL
class mindspore.dataset.vision.ToPIL
For more information, see mindspore.dataset.vision.ToPIL.
Differences
PyTorch: Converts a tensor or numpy array to PIL Image. The input can be a torch Tensor in the format of <C, H, W>, or a numpy array in the format of <H, W, C>.
MindSpore: The input is a decoded numpy array, which is converted into a PIL type image.
Code Example
import numpy as np
import torch as T
from torchvision.transforms import ToPILImage
import mindspore.dataset.vision as vision
# In MindSpore, ToPIL transform the numpy.ndarray to PIL Image.
image = np.random.random((64,64))
img = vision.ToPIL()(image)
img.show()
# Out:
# window of PIL image
# In torch, ToPILImage transforms the input to PIL Image.
image = T.randn((64, 64))
img = ToPILImage()(image)
img.show()
# Out:
# window of PIL image