How can I convert an array of images to a 2D array in Python

Question

I have a numpy array of images in that shape:

(50000, 32, 32, 3)

50000 is the number of images
32, 32 are the height and width
3 are the RGB values with a range of 0-1

I would like to convert it to a 2D shape of:

(50000, 1024)

Here I would have 50000 images represented in one row, the RGB value would be converted to let's say an hexadecimal value I've went through a lot of conversion processes into stack overflow and I've found some. I know that if my array was a 3D array with an already converted value I could easily use reshape()function to convert it to 2D. Now what I'm searching is the easiest way to convert RGB values and reshape my array

Would this be possible in 1 or two lines or should I use an external function?

https://stackoverflow.com/questions/43001349/convert-numpy-array-of-rgb-values-to-hex-using-format-operator — taras, Mar 22 '19 at 11:30
@taras thanks didn't find this one that helps but doesn't resolve all my problem as I would like to see the best code for the whole process. I'm new to python so I'm afraid by playing with the arrays alone I won't take the best way possible — JSmith, Mar 22 '19 at 11:32

Jurgen Strydom · Accepted Answer · 2019-03-22T11:41:22.070

2

First convert the RGB values in the last dimension to the HEX value using whatever function you like. This SO answer may help.

Reshape then works on any number of dimensions:

import numpy as np

def rgb2hex(r, g, b):
    return '#%02x%02x%02x' % (r, g, b)

vfunc = np.vectorize(rgb2hex)

a = (np.random.uniform(0,1,(10,5,5,3))*255).astype(int)

c = vfunc(a[:,:,:,0], a[:,:,:,1], a[:,:,:,2])

c.reshape((10,25))

edited Mar 22 '19 at 11:41

answered Mar 22 '19 at 11:28

Jurgen Strydom

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thanks for the answer, but will it convert my RGB value? – JSmith Mar 22 '19 at 11:29
great could you show me the process of conversion please? for loop, one line for loop??? – JSmith Mar 22 '19 at 11:30
Just note that I made a fix. Please accept the answer if it helped. – Jurgen Strydom Mar 22 '19 at 11:41
Let us [continue this discussion in chat](https://chat.stackoverflow.com/rooms/190501/discussion-between-jurgen-strydom-and-jsmith). – Jurgen Strydom Mar 22 '19 at 12:16

dwjbosman · Answer 2 · 2019-03-22T12:36:00.353

1

The following combines the RGB values into a single value

x=np.zeros((100,32,32,3))
x[:,:,:,0] = np.trunc(x[:,:,:,0]) + np.trunc(x[:,:,:,1] *256) + np.trunc(x[:,:,:,2] *65535)
y=x[:,:,:,0]
print(y.shape)

The resulting shape of y: (100, 32, 32)

Next you can use the reshape function on y.

edited Mar 22 '19 at 12:36

answered Mar 22 '19 at 11:33

dwjbosman

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I've just tried your solution but I still the same shape with the 3 length array at the end. Thanks in advance – JSmith Mar 22 '19 at 11:40
I added some details. If I run the code I get a shape of 100,32,32 – dwjbosman Mar 22 '19 at 12:36

yatu · Answer 3 · 2019-03-22T11:48:49.770

In order to do so, you firstly need to reshape the ndarray (np.reshape):

a = np.random.randint(1,10,(500, 32, 32, 3))
a_r = np.reshape(a, (500, 1024, 3))
print(a_r.shape)
# (500, 1024, 3)

Now, in order to convert the RGB values along the last dimension to hexadecimal representation as you suggest, you could define a function that returns a hexadecimal representation of the three values with a simple string formatting:

def rgb_to_hex(x):
    return '#{:02X}{:02X}{:02X}'.format(*rgb.reshape(3))

In order to apply the conversion along all rows in the last axis, you can use np.apply_along_axis:

a_new = np.apply_along_axis(rgb2hex, axis=-1, arr=a_r).shape
print(a_new.shape)
# (500, 1024)

How can I convert an array of images to a 2D array in Python

3 Answers3