How can i transform my binary numpy list of arrays to an image?

Question

[[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 1 1 1 0 0 0 0 0 1 1 0 0 3 3 0 0 0 4 4 0 0 0 5 5 5 5 0 0 2 2 2 2 2 0 2 2 2 2 2 0 0 0 6 6 6 6 6 6 0 6 6 6 6]
 [0 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 0 5 5 5 5 5 5 0 2 2 2 2 2 2 2 2 2 2 2 2 0 0 6 6 6 6 6 6 6 6 6 6 6]
 [1 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 5 5 5 0 0 5 5 5 0 2 2 0 0 2 2 0 0 0 2 2 0 0 6 6 0 0 6 6 6 0 0 6 6]
 [1 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 5 5 5 5 0 0 0 0 0 2 2 0 2 2 2 0 0 0 2 2 2 0 6 6 0 0 0 6 6 0 0 6 6]
 [1 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 0 5 5 5 5 5 5 0 0 2 2 0 2 2 2 0 0 0 2 2 2 0 6 6 0 0 0 6 6 0 0 6 6]
 [0 1 1 0 0 0 0 0 0 7 0 0 0 3 3 0 0 0 4 4 0 0 0 0 5 5 5 5 5 0 2 2 0 2 2 2 0 0 0 2 2 2 0 6 6 0 0 0 6 6 0 0 6 6]]

As a first step I want the pixels different than 0 to be white and the 0 pixels to be black.what i did to transform the none 0 values all to 1:

binary_transform = np.array(labels).astype(bool).astype(int)

and it worked then i want to transform the list of arrays of 1s and 0s to image, what i tried:

from PIL import Image

img = Image.fromarray(binary_transform, '1')
img.save('image.png')

the docs for Image.fromarray can be found here https://pillow.readthedocs.io/en/3.1.x/reference/Image.html

It didn't work then i tried the following:

import png

png.from_array(binary_transform, 'L').save('image.png')

Referring to the docs 'L' is for grayscale while i want binary but i didn't see a binary option, the docs https://pythonhosted.org/pypng/png.html

and i got this error ValueError: bitdepth (64) must be a positive integer <= 16

Mark Setchell · Accepted Answer · 2018-06-19 15:28:01Z

3

Though you don't say that explicitly, the fact that you said "As a first step...", makes me think you are heading towards a greyscale palette image:

import numpy as np
from PIL import Image
labels=[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
 [0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
 [0,0,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
 [0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
 [0,1,1,1,0,0,0,0,0,1,1,0,0,3,3,0,0,0,4,4,0,0,0,5,5,5,5,0,0,2,2,2,2,2,0,2,2,2,2,2,0,0,0,6,6,6,6,6,6,0,6,6,6,6],
 [0,1,1,0,0,0,0,0,0,0,0,0,0,3,3,0,0,0,4,4,0,0,5,5,5,5,5,5,0,2,2,2,2,2,2,2,2,2,2,2,2,0,0,6,6,6,6,6,6,6,6,6,6,6],
 [1,1,1,0,0,0,0,0,0,0,0,0,0,3,3,0,0,0,4,4,0,5,5,5,0,0,5,5,5,0,2,2,0,0,2,2,0,0,0,2,2,0,0,6,6,0,0,6,6,6,0,0,6,6],
 [1,1,1,0,0,0,0,0,0,0,0,0,0,3,3,0,0,0,4,4,0,5,5,5,5,0,0,0,0,0,2,2,0,2,2,2,0,0,0,2,2,2,0,6,6,0,0,0,6,6,0,0,6,6],
 [1,1,1,0,0,0,0,0,0,0,0,0,0,3,3,0,0,0,4,4,0,0,5,5,5,5,5,5,0,0,2,2,0,2,2,2,0,0,0,2,2,2,0,6,6,0,0,0,6,6,0,0,6,6],
 [0,1,1,0,0,0,0,0,0,7,0,0,0,3,3,0,0,0,4,4,0,0,0,0,5,5,5,5,5,0,2,2,0,2,2,2,0,0,0,2,2,2,0,6,6,0,0,0,6,6,0,0,6,6]]
binary_transform = np.array(labels).astype(np.uint8)
img = Image.fromarray(binary_transform, 'P')
img.save('image.png')

Note that I have resized and contrast-stretched the image for display purposes.

If you really only want a true binary, black and white image, use:

binary_transform = np.array(labels).astype(np.uint8)
binary_transform[binary_transform>0] = 255
img = Image.fromarray(binary_transform, 'L')
img.save('image.png')

edited Jun 19, 2018 at 15:28

answered Jun 19, 2018 at 14:57

Mark Setchell

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2 Comments

Nelly Over a year ago

Actually no it's not a grayscale image, it's the output of the connected components function applied to a grayscale image(cv2.connectedComponents)

Mark Setchell Over a year ago

I guessed that it was Connected Components labelling :-)

T. Ray · Accepted Answer · 2018-06-19 15:25:03Z

3

If I understand you right, you want the image to appear binary, i.e., just black and white, no grey. If that's the case, OpenCV is your friend:

import cv2
import numpy as np

binary_transform = np.array(labels).astype(np.uint8)

_,thresh_img = cv2.threshold(binary_transform, 0, 255, cv2.THRESH_BINARY)

cv2.imwrite('image.png', thresh_img)

Of course PIL will work as well, you just need to adjust your non-zero values.

binary_transform = np.array(labels).astype(np.uint8)
binary_transform[binary_transform > 0] = 255

img = Image.fromarray(binary_transform, 'L')
img.save('image.png')

edited Jun 19, 2018 at 15:25

answered Jun 19, 2018 at 15:16

T. Ray

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1 Comment

Mark Setchell Over a year ago

Cool, and +1 for doing it two different ways!

Warren Weckesser · Accepted Answer · 2018-06-19 19:02:09Z

The other answers (all good!) use OpenCV or PIL. Here's how you could create the image using numpngw, a small library that I wrote to create PNG files from numpy arrays.

First, here's my data for the example:

In [173]: x
Out[173]: 
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 1, 1, 1, 1, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 1, 1, 1, 1, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 1, 1, 1, 1, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 1, 1, 1, 1, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 0],
 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]

Create the image using numpngw.write_png():

In [174]: import numpy as np

In [175]: import numpngw

In [176]: numpngw.write_png("foo.png", (np.array(x) > 0).astype(np.uint8), bitdepth=1)

Here's the image:

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