I have an np array with shape (100,28,28)
I would like to turn it to (100,32,32,3)
by padding with zero's and adding dimensions
I tried np.newaxis which got me as far as (100,28,28,1)
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2 Answers
There is not enough information about how you want the padding to be done, so I'll suppose an image processing setup:
- Padding on both edges of the array
- Array must be replicated along the newly added dimension
Setup
import numpy as np
N, H, W, C = 100, 28, 28, 3
x = np.ones((N, H, W))
1. Padding
# (before, after)
padN = (0, 0)
padH = (2, 2)
padW = (2, 2)
x_pad = np.pad(x, (padN, padH, padW))
assert x_pad.shape == (N + sum(padN), H + sum(padH), W + sum(padW))
2. Replicate along a new dimensions
x_newd = np.repeat(x_pad[..., None], repeats=C, axis=-1)
assert x_newd.shape == (*x_pad.shape, C)
assert np.all(x_newd[..., 0] == x_newd[..., 1])
assert np.all(x_newd[..., 1] == x_newd[..., 2])
Comments
You can try the resize function on your array. This is the code I tried.
arr = np.ones((100,28,28))
arr.resize((100, 32, 32, 3))
print(arr)
The newly added items are all 0s.
