I believe it is the ToTensor change that is disrupting the values. Here are the values of an image before ToTensor being applied:
[[257.10788 257.09265 257.07593 ... 252.98647 252.97443 252.96442]
 [257.09814 257.08295 257.06628 ... 252.99252 252.98094 252.97125]
 [257.0885  257.07336 257.0568  ... 252.99867 252.98766 252.97833]
 ...
 [255.94922 255.93744 255.92479 ... 253.86107 253.8524  253.84364]
 [255.95549 255.94397 255.93147 ... 253.86275 253.85414 253.84538]
 [255.96043 255.94917 255.93686 ... 253.86534 253.85675 253.84795]]

and the values after:
tensor([[[0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         [0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         [0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         ...,
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647],
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647],
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647]],

        [[0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         [0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         [0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         ...,
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647],
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647],
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647]],

        [[0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         [0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         [0.9804, 0.9804, 0.9804,  ..., 0.9725, 0.9725, 0.9725],
         ...,
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647],
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647],
         [0.9725, 0.9725, 0.9725,  ..., 0.9647, 0.9647, 0.9647]]])

As you can see the tensor values come in blocks of the same number which is what is resulting in the change but I’m not sure why this is the case.