Posted on Apr 28 • Edited on May 13
ToPILImage in PyTorch (2)

*Memos:
My post explains ToPILImage() about no arguments.
My post explains ToPILImage() about mode argument (2).
My post explains ToPILImage() about mode argument (3).
My post explains ToPILImage() about mode argument (4).
ToPILImage() can convert an Image([..., C, H, W]), tensor or ndarray to a PIL(Pillow library) image([H, W, C]) and doesn't scale its values to [0.0, 1.0] as shown below. *It's about mode argument (1):
from torchvision.datasets import OxfordIIITPet from torchvision.transforms.v2 import ToPILImage, ToImage, PILToTensor import torch Image_data = OxfordIIITPet( root="data", transform=ToImage() ) Tensor_data = OxfordIIITPet( root="data", transform=PILToTensor() ) tp = ToPILImage() tp = ToPILImage(mode="RGB") tp(Image_data[0]) tp(Tensor_data[0]) # (<PIL.Image.Image image mode=RGB size=394x500>, 0)  print(tp(Image_data[0][0])) print(tp(Tensor_data[0][0])) # <PIL.Image.Image image mode=RGB size=394x500 at 0x1A808BB8560>  tp = ToPILImage(mode="YCbCr") tp(Image_data[0]) tp(Tensor_data[0]) # (<PIL.Image.Image image mode=YCbCr size=394x500>, 0)  print(tp(Image_data[0][0])) print(tp(Tensor_data[0][0])) # <PIL.Image.Image image mode=YCbCr size=394x500 at 0x1A80D360530>  tp = ToPILImage(mode="HSV") tp(Image_data[0]) tp(Tensor_data[0]) # (<PIL.Image.Image image mode=HSV size=394x500>, 0)  print(tp(Image_data[0][0])) print(tp(Tensor_data[0][0])) # <PIL.Image.Image image mode=HSV size=394x500 at 0x1A80D362180>  tp = ToPILImage() tp = ToPILImage(mode="I") tp((torch.tensor([[[0]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=I size=1x1>, 0)  tp = ToPILImage(mode="LA") tp((torch.tensor([[[0]], [[1]]]), 0)) # int64 tp((torch.tensor([[[0]], [[1]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=LA size=1x1>, 0)  tp = ToPILImage(mode="RGB") tp((torch.tensor([[[0]], [[1]], [[2]]]), 0)) tp((torch.tensor([[[0]], [[1]], [[2]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=RGB size=1x1>, 0)  tp = ToPILImage(mode="YCbCr") tp((torch.tensor([[[0]], [[1]], [[2]]]), 0)) tp((torch.tensor([[[0]], [[1]], [[2]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=YCbCr size=1x1>, 0)  tp = ToPILImage(mode="HSV") tp((torch.tensor([[[0]], [[1]], [[2]]]), 0)) tp((torch.tensor([[[0]], [[1]], [[2]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=HSV size=1x1>, 0)  tp = ToPILImage(mode="RGBA") tp((torch.tensor([[[0]], [[1]], [[2]], [[3]]]), 0)) tp((torch.tensor([[[0]], [[1]], [[2]], [[3]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=RGBA size=1x1>, 0)  tp = ToPILImage(mode="CMYK") tp((torch.tensor([[[0]], [[1]], [[2]], [[3]]]), 0)) tp((torch.tensor([[[0]], [[1]], [[2]], [[3]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=CMYK size=1x1>, 0)  tp = ToPILImage(mode="RGBX") tp((torch.tensor([[[0]], [[1]], [[2]], [[3]]]), 0)) tp((torch.tensor([[[0]], [[1]], [[2]], [[3]]], dtype=torch.int32), 0)) # (<PIL.Image.Image image mode=RGBX size=1x1>, 0)  tp = ToPILImage() tp = ToPILImage(mode="L") tp((torch.tensor([[[0.]]]), 0)) # float32 tp((torch.tensor([[[0.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=L size=1x1>, 0)  tp = ToPILImage() tp = ToPILImage(mode="LA") tp((torch.tensor([[[0.]], [[1.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=LA size=1x1>, 0)  tp = ToPILImage() tp = ToPILImage(mode="RGB") tp((torch.tensor([[[0.]], [[1.]], [[2.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]], [[2.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=RGB size=1x1>, 0)  tp = ToPILImage(mode="YCbCr") tp((torch.tensor([[[0.]], [[1.]], [[2.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]], [[2.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=YCbCr size=1x1>, 0)  tp = ToPILImage(mode="HSV") tp((torch.tensor([[[0.]], [[1.]], [[2.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]], [[2.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=HSV size=1x1>, 0)  tp = ToPILImage() tp = ToPILImage(mode="RGBA") tp((torch.tensor([[[0.]], [[1.]], [[2.]], [[3.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]], [[2.]], [[3.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=RGBA size=1x1>, 0)  tp = ToPILImage(mode="CMYK") tp((torch.tensor([[[0.]], [[1.]], [[2.]], [[3.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]], [[2.]], [[3.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=CMYK size=1x1>, 0)  tp = ToPILImage(mode="RGBX") tp((torch.tensor([[[0.]], [[1.]], [[2.]], [[3.]]]), 0)) tp((torch.tensor([[[0.]], [[1.]], [[2.]], [[3.]]], dtype=torch.float64), 0)) # (<PIL.Image.Image image mode=RGBX size=1x1>, 0)  tp = ToPILImage(mode="LA") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]]]), 0)) # complex64 tp((torch.tensor([[[0.+0.j]], [[1.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=LA size=1x1>, 0)  tp = ToPILImage(mode="RGB") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]]]), 0)) tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=RGB size=1x1>, 0)  tp = ToPILImage(mode="YCbCr") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]]]), 0)) tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=YCbCr size=1x1>, 0)  tp = ToPILImage(mode="HSV") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]]]), 0)) tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=HSV size=1x1>, 0)  tp = ToPILImage(mode="RGBA") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]], [[3.+0.j]]]), 0)) tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]], [[3.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=RGBA size=1x1>, 0)  tp = ToPILImage(mode="CMYK") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]], [[3.+0.j]]]), 0)) tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]], [[3.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=CMYK size=1x1>, 0)  tp = ToPILImage(mode="RGBX") tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]], [[3.+0.j]]]), 0)) tp((torch.tensor([[[0.+0.j]], [[1.+0.j]], [[2.+0.j]], [[3.+0.j]]], dtype=torch.complex128), 0)) # (<PIL.Image.Image image mode=RGBX size=1x1>, 0)  tp = ToPILImage(mode="LA") tp((torch.tensor([[[True]], [[False]]]), 0)) # bool # (<PIL.Image.Image image mode=LA size=1x1>, 0)  tp = ToPILImage(mode="RGB") tp((torch.tensor([[[True]], [[False]], [[True]]]), 0)) # (<PIL.Image.Image image mode=RGB size=1x1>, 0)  tp = ToPILImage(mode="YCbCr") tp((torch.tensor([[[True]], [[False]], [[True]]]), 0)) # (<PIL.Image.Image image mode=YCbCr size=1x1>, 0)  tp = ToPILImage(mode="HSV") tp((torch.tensor([[[True]], [[False]], [[True]]]), 0)) # (<PIL.Image.Image image mode=HSV size=1x1>, 0)  tp = ToPILImage(mode="RGBA") tp((torch.tensor([[[True]], [[False]], [[True]], [[False]]]), 0)) # (<PIL.Image.Image image mode=RGBA size=1x1>, 0)  tp = ToPILImage(mode="CMYK") tp((torch.tensor([[[True]], [[False]], [[True]], [[False]]]), 0)) # (<PIL.Image.Image image mode=CMYK size=1x1>, 0)  tp = ToPILImage(mode="RGBX") tp((torch.tensor([[[True]], [[False]], [[True]], [[False]]]), 0)) # (<PIL.Image.Image image mode=RGBX size=1x1>, 0)
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ToPILImage in PyTorch (2)

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