How to do tensor binary erosion operation in Pytorch

1

Suppose I have a tensor a, are there any pytorch (binary) erosion operations that can give tensor like b, so basically similar to scipy.ndimage.binary_erosion

print(a)
tensor([[0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0]])

print(b)
tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
        [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0],
        [0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0],
        [0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0],
        [0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0],
        [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
        [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
2

Hi Qimin!

If I understand your example tensors correctly, you want the following:

If a pixel and its 4-connected (NSEW) pixels are all 1, the resulting pixel
value should be 1 and 0 otherwise.

Build a 3x3 convolution kernel with zeros in the corners and ones for the
center and 4-connected entries. Initialize the weight of a Conv2d (no bias)
with this kernel, pad the border of your input tensor, convolve it, and test
the resulting pixels against 5: == 5 → 1 and < 5 → 0.

Best.

K. Frank

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