Creating a grayscale image from an array of values-CodePudding

I am trying to create a grayscale image from an array of values that range from 0 to 1. here is an example of two of the arrays I have.

[[0.48 0.4  0.56 0.32 0.52]
 [0.36 0.56 0.56 0.68 0.56]
 [0.32 0.72 0.88 0.44 0.56]
 [0.56 0.64 0.76 0.52 0.48]
 [0.32 0.88 0.56 0.52 0.4 ]]

[[0.33333333 0.22222222 0.33333333]
 [0.22222222 0.44444444 0.11111111]
 [0.44444444 0.11111111 0.11111111]]

the shape of the array is always a square and the the amount that the values deviate from 0.5 varies. I more or less want values of 1 to be white and 0 to be black. Is there a relatively simple way to do this using a module such as matplotlib or pillow? (it doesn't have to be one of those two).

I have tried following some tutorials, but they all used hexadecimal value lists or integer values and don't understand the method enough to make them work with floats.

CodePudding user response：

This is easily done with

CodePudding user response：

PIL can create a PIL Image directly from an array:

from PIL import Image
import numpy as np

# Make our randomness repeatable, and generate a 5x4 array of pixels
np.random.seed(42)
px = np.random.random((4,5))

That looks like this:

array([[0.37454012, 0.95071431, 0.73199394, 0.59865848, 0.15601864],
       [0.15599452, 0.05808361, 0.86617615, 0.60111501, 0.70807258],
       [0.02058449, 0.96990985, 0.83244264, 0.21233911, 0.18182497],
       [0.18340451, 0.30424224, 0.52475643, 0.43194502, 0.29122914]])

Now multiply up by 255, and subtract from 255 to invert, i.e. so that 0=black and 1=white, and make into PIL Image

p = Image.fromarray((255 - px*255).astype(np.uint8))

# We are finished, but enlarge for illustrative purposes
p = p.resize((50, 40), resample=Image.Resampling.NEAREST)
p.save('result.png')