Find unique tuples in 3D numpy array

Question

I am trying to find uniques tuples within a numpy array but am unable to. Based on other SO answer I tried np.unique while setting the value for the axis, but it's not providing me what I'm looking for. Here's an example:

I have the following array

b = np.array([[[255, 0, 0], [255, 0, 0]], [[255, 0, 0], [0, 0, 0]]])

I am looking for a way to tell me that it has two tuples in it: (255, 0, 0) and (0, 0, 0). Here are the results from using np.unique:

np.unique(b, axis=0)

array([[[255,   0,   0],
        [  0,   0,   0]],

       [[255,   0,   0],
        [255,   0,   0]]])


np.unique(b, axis=1)

array([[[255,   0,   0],
        [255,   0,   0]],

       [[  0,   0,   0],
        [255,   0,   0]]])

np.unique(b, axis=2)

array([[[  0, 255],
        [  0, 255]],

       [[  0, 255],
        [  0,   0]]])

How do I get it to return [255, 0, 0], [0, 0, 0]?

Frank Yellin · Accepted Answer · 2020-12-29 00:21:49Z

5

Make b into a Nx3 array first. Then use unique.

>>> np.unique(b.reshape(-1, 3), axis=0)
array([[  0,   0,   0],
       [255,   0,   0]])

answered Dec 29, 2020 at 0:21

Frank Yellin

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U13-Forward · Accepted Answer · 2020-12-29 00:22:05Z

0

Try using a list comprehension:

print(np.array([i for i in b if len(set(map(tuple, i))) == len(i)]))

Output:

[[[255   0   0]
  [  0   0   0]]]

answered Dec 29, 2020 at 0:22

U13-Forward

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