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همانطور که در زیر آمده است می توانید با تصویر PIL ، Pytorch Tensor و Numpy Array تبدیل کنید:
from torchvision.datasets import OxfordIIITPet
origin_data = OxfordIIITPet(
root="data",
transform=None
)
import matplotlib.pyplot as plt
plt.figure(figsize=[7, 9])
plt.title(label="s500_394origin_data", fontsize=14)
plt.imshow(X=origin_data[0][0])
plt.show()
تصویر PIL[H, W, C] => تانسور Pytorch[C, H, W] => آرایه numpy[H, W, C] => تصویر PIL[H, W, C]:
from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import PILToTensor, ToPILImage
import numpy as np
origin_data = OxfordIIITPet(
root="data",
transform=None
)
ptt = PILToTensor()
pytorchimagetensor = ptt(origin_data[0][0])
# tensor([[[ 37, 35, 36, ..., 247, 249, 249],
# [ 35, 35, 37, ..., 246, 248, 249],
# ...,
# [ 28, 28, 27, ..., 59, 65, 76]],
# [[ 20, 18, 19, ..., 248, 248, 248],
# [ 18, 18, 20, ..., 247, 247, 248],
# ...,
# [ 27, 27, 27, ..., 94, 106, 117]],
# [[ 12, 10, 11, ..., 253, 253, 253],
# [ 10, 10, 12, ..., 251, 252, 253],
# ...,
# [ 35, 35, 35, ..., 214, 232, 223]]], dtype=torch.uint8)
numpyimagearray = pytorchimagetensor.permute(1, 2, 0).numpy()
numpyimagearray = np.array(object=pytorchimagetensor.permute(1, 2, 0))
numpyimagearray = np.asarray(pytorchimagetensor.permute(1, 2, 0))
numpyimagearray
# array([[[ 37 20 12]
# [ 35 18 10]
# ...
# [249 248 253]]
# [[ 35 18 10]
# [ 35 18 10]
# ...
# [249 248 253]]
# [[ 35 18 10]
# [ 36 19 11]
# ...
# [250 249 254]]
# ...
# [[ 5 6 24]
# [ 4 5 23]
# ...
# [ 69 110 224]]
# [[ 4 3 19]
# [ 3 2 18]
# ...
# [ 64 108 229]]
# [[ 28 27 35]
# [ 28 27 35]
# ...
# [ 76 117 223]]], dtype=uint8)
tpi = ToPILImage()
pilimage = tpi(numpyimagearray)
import matplotlib.pyplot as plt
plt.figure(figsize=[7, 9])
plt.title(label="s500_394origin_data", fontsize=14)
plt.imshow(X=pilimage)
plt.show()
تصویر PIL[H, W, C] => آرایه numpy[H, W, C] => تانسور Pytorch[C, H, W] => تصویر PIL[H, W, C]:
from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import ToPILImage
import numpy as np
import torch
origin_data = OxfordIIITPet(
root="data",
transform=None
)
numpyimagearray = np.array(object=origin_data[0][0])
numpyimagearray = np.asarray(origin_data[0][0])
numpyimagearray
# array([[[ 37 20 12]
# [ 35 18 10]
# ...
# [249 248 253]]
# [[ 35 18 10]
# [ 35 18 10]
# ...
# [249 248 253]]
# [[ 35 18 10]
# [ 36 19 11]
# ...
# [250 249 254]]
# ...
# [[ 5 6 24]
# [ 4 5 23]
# ...
# [ 69 110 224]]
# [[ 4 3 19]
# [ 3 2 18]
# ...
# [ 64 108 229]]
# [[ 28 27 35]
# [ 28 27 35]
# ...
# [ 76 117 223]]], dtype=uint8)
pytorchimagetensor = torch.from_numpy(numpyimagearray).permute(dims=[2, 0, 1])
pytorchimagetensor = torch.tensor(numpyimagearray).permute(dims=[2, 0, 1])
pytorchimagetensor
# tensor([[[ 37, 35, 36, ..., 247, 249, 249],
# [ 35, 35, 37, ..., 246, 248, 249],
# ...,
# [ 28, 28, 27, ..., 59, 65, 76]],
# [[ 20, 18, 19, ..., 248, 248, 248],
# [ 18, 18, 20, ..., 247, 247, 248],
# ...,
# [ 27, 27, 27, ..., 94, 106, 117]],
# [[ 12, 10, 11, ..., 253, 253, 253],
# [ 10, 10, 12, ..., 251, 252, 253],
# ...,
# [ 35, 35, 35, ..., 214, 232, 223]]], dtype=torch.uint8)
tpi = ToPILImage()
pilimage = tpi(pytorchimagetensor)
import matplotlib.pyplot as plt
plt.figure(figsize=[7, 9])
plt.title(label="s500_394origin_data", fontsize=14)
plt.imshow(X=pilimage)
plt.show()
