Numpy: Convert RGB flat array to matrix

Question

I have an array containing the RGB values of all pixels in an image. Supposing a 4x4 image, the array is of size 48, where the first 16 values are the red values, the next 16 are the green and the last 16 are the blue:

[r0, r1, ..., r15, g0, g1, ..., g15, b0, b1, ..., b14, b15]

Now I want to convert that array to a 4x4 matrix with depth 3 in this form:

[[[r0, g0, b0], ..., [r3, g3, b3]],
  ...
 [[r12, g12, b12], ..., [r15, g15, b15]]]

To do so, I am doing a reshape + transpose + reshape:

import matplotlib.pyplot as plt

N = 4
numpy.random.seed(0)
rrggbb = numpy.random.randint(0, 255, size=N*N*3, dtype='uint8')
imgmatrix = rrggbb.reshape((3, -1)).transpose().reshape((N, N, 3))

plt.imshow(imgmatrix)
plt.show()

Is there a more efficient/short way to do that? (i.e.: with less reshaping/transposing)

akuiper · Accepted Answer · 2017-04-20 15:09:24Z

2

Here is an option with one step less:

rrggbb.reshape((3, N, N)).transpose((1,2,0))

(rrggbb.reshape((3, N, N)).transpose((1,2,0)) == imgmatrix).all()
# True

Or you can use np.moveaxis to move axis 0 to the last axis:

np.moveaxis(rrggbb.reshape((3, N, N)), 0, -1)

(np.moveaxis(rrggbb.reshape((3, N, N)), 0, -1) == imgmatrix).all()
#True

edited Apr 20, 2017 at 15:09

answered Apr 20, 2017 at 15:00

akuiper

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4 Comments

Peque Over a year ago

Thanks, my mind was telling me there was something not very efficient in there... ^^

akuiper Over a year ago

Hmm. Not an expert, but I guess your approach should be as efficient, since reshape is almost costless, which just Gives a new shape to an array without changing its data., the transpose is moving data around.

Peque Over a year ago

Well, less efficient as it is 3 operations vs 2, but even CPU-time-wise, your implementation seems to be faster (about 30% for small images, which is my use case actually).

akuiper Over a year ago

Interesting. Thanks for sharing the timing result.

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