How to append the list's values to a 3D array - python and opencv

Question

As I have no much knowledge in opencv, the question might be silly. Anyways my question is, I have a set of 30 images and I am calculating the mean of Red, Green and Blue channles for all the 30 images and stored them in 3 different lists, now what I want is to append these 3 different list values into a 3D array as:

[B_mean,
 G_mean,
 R_mean]

This is my BGR mean values:

blue mean [25, 28, 66, 63, 59, 70, 64, 38, 33, 39, 22, 37, 48, 4, 13, 12, 6, 3, 22, 18, 23, 21, 22, 31, 38, 21, 34, 26, 21, 30]
green mean [27, 29, 68, 66, 63, 69, 66, 45, 48, 41, 38, 41, 41, 22, 21, 9, 7, 25, 35, 28, 37, 36, 35, 32, 36, 20, 27, 24, 18, 25]
read mean [25, 26, 70, 69, 71, 67, 66, 42, 45, 31, 40, 43, 37, 32, 33, 37, 30, 34, 34, 24, 28, 32, 30, 33, 36, 26, 24, 30, 24, 26]

like 3 rows and 30 columns. so how am I going to get this?

Thanks!

It sounds like you want a 2d array, ie a (3, 30) array. A 3d array would have a shape like (2, 3, 30). — Bi Rico
– Bi Rico, Commented Feb 21, 2014 at 18:46

Bi Rico · Accepted Answer · 2014-02-21 18:49:06Z

1

Just use numpy.array:

import numpy as np

red = range(0, 30)
blue = range(10, 40)
green = range(20, 50)
array = np.array([red, green, blue])
print array.shape
# (3, 30)

answered Feb 21, 2014 at 18:49

Bi Rico

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Clint Powell · Accepted Answer · 2014-02-21 17:50:01Z

0

It's actually a two-dimensional array if you only have rows and columns.

mylist = [[1,2,3], [1,2,3]]
mylist.append([1,2,3])

This will create a list of three RGB pairs (1, 2, 3) in this case.

Edit

After re-reading your question, a more specific solution would be (given three lists of colors):

mylist = []
for i in range(0, 30):
   mylist.append([red[i], green[i], blue[i]])

edited Feb 21, 2014 at 17:50

answered Feb 21, 2014 at 17:44

Clint Powell

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runDOSrun · Accepted Answer · 2014-02-21 17:56:43Z

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matrix = [[mean for mean in chan]  for chan in [red, green, blue]]

This is how you initialize a multidimensional Array in Python.

Edit: I should mention that using numpy is the preferred way unless you're writing something one-time-use-only.

edited Feb 21, 2014 at 17:56

answered Feb 21, 2014 at 17:50

runDOSrun

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