CODEWITHSUNDEEP
pythonimagebinaryconverters
Hasmik Khachatryan
Hasmik Khachatryan

Reputation: 23

B&W image to binary array

I want to convert my b&w image(.png) to binary array(black is 1 white is 0). I have written some code, but it's not working. Error says: argument 2 to map() must support iteration. Here is my code:

from PIL import Image
from resizeimage import resizeimage
import sys

def threshold(col):
    s = sum(col) 
    return int(s > 255 * 3 // 2)

img = Image.open("filename.png")

ratio = float((img.size[1]) / (img.size[0]))

img = resizeimage.resize_cover(img, [100, int(ratio * 100)])

pixels = img.getdata()
binary = list(map(threshold, img))

array2d = [binary[i * img.size[0] : (i+1) * img.size[0]] for i in range(img.size[1])]
print('\n'.join(''.join(map(str, line)) for line in array2d))

Here is the image:

example image

Upvotes: 2

Views: 8001

Answers (2)

panda-byte
panda-byte

Reputation: 594

You could also do this:

from PIL import Image
import numpy as np

image = Image.open('bw_circle.png').convert('1')
binary = bytes(np.packbits(~np.array(image)))

Upvotes: 0

Fiver
Fiver

Reputation: 10167

You need to convert your image to grayscale first, since PIL opens it as RGB. Then, invert the 0 & 255 values. Then, you can convert the non-zero values to 1. Here's one way:

from PIL import Image
import numpy as np

img = Image.open('bw_circle.png').convert('L')

np_img = np.array(img)
np_img = ~np_img  # invert B&W
np_img[np_img > 0] = 1

And an alternative way using PIL for the inversion:

from PIL import Image, ImageOps
import numpy as np

img = Image.open('bw_circle.png').convert('L')
img_inverted = ImageOps.invert(img)

np_img = np.array(img_inverted)
np_img[np_img > 0] = 1

Upvotes: 2

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