Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

• Transformations based on Tensors
Obviously, there are conversion transforms to convert from tensor ToPILImage()
and from PIL image ToTensor().
Let’s start by using ToTensor() to convert a Numpy array (in PIL shape) to a
PyTorch tensor. We can create a "tensorizer" (for lack of a better name) and feed it
our example image (#7) in HWC shape:
tensorizer = ToTensor()
example_tensor = tensorizer(example_hwc)
example_tensor.shape
Output
torch.Size([1, 5, 5])
Cool, we got the expected CHW shape. So, its content should be easy to associate
with the underlying image:
example_tensor
Output
tensor([[[0., 1., 0., 0., 0.],
[0., 0., 1., 0., 0.],
[0., 0., 0., 1., 0.],
[0., 0., 0., 0., 1.],
[0., 0., 0., 0., 0.]]])
And indeed it is: Once again we can "see" the diagonal line. But, this time, its values
are not equal to 255; they are equal to 1.0 instead.
Torchvision | 275