Using PIL to turn a RGB image into a pure black and white image

Question

I'm using the Python Imaging Library for some very simple image manipulation, however I'm having trouble converting a greyscale image to a monochrome (black and white) image. If I save after changing the image to greyscale (convert('L')) then the image renders as you would expect. However, if I convert the image to a monochrome, single-band image it just gives me noise as you can see in the images below. Is there a simple way to take a colour png image to a pure black and white image using PIL / python?

from PIL import Image 
import ImageEnhance
import ImageFilter
from scipy.misc import imsave
image_file = Image.open("convert_image.png") # open colour image
image_file= image_file.convert('L') # convert image to monochrome - this works
image_file= image_file.convert('1') # convert image to black and white
imsave('result_col.png', image_file)

Original Image Converted Image

From the [PIL documentation](http://www.pythonware.com/library/pil/handbook/image.htm): """When converting to a bilevel image (mode "1"), the source image is first converted to black and white. Resulting values larger than 127 are then set to white, and the image is dithered. To use other thresholds, use the point method.""" This sounds related, but I'm not familiar with PIL and image manipulation. — Casey Kuball, Feb 29 '12 at 21:31

unutbu · Accepted Answer · 2015-12-14T12:44:50.017

111

from PIL import Image 
image_file = Image.open("convert_image.png") # open colour image
image_file = image_file.convert('1') # convert image to black and white
image_file.save('result.png')

yields

enter image description here

edited Dec 14 '15 at 12:44

answered Feb 29 '12 at 21:32

unutbu

842,883
184
1,785
1,677

very bad output. Text is not recognizable( – Yaroslav Dukal Jul 12 '19 at 22:10
3

This is a grayscale image, not a bw image. – progyammer Jun 06 '20 at 04:52
7

@progyammer it is definitely black and white only. Dithering is not the same thing as grayscale; the image is created using 1-bit per pixel. grayscale typically uses 8 bits per pixel to give you shades between white (off) and black (on). – Martijn Pieters Sep 18 '20 at 21:03
1

@MartijnPieters You're right! It is a BW image. Didn't notice it cuz it looks gray when zoomed out :P – progyammer Sep 30 '20 at 09:05

maxschlepzig · Answer 2 · 2019-03-22T12:32:29.083

86

A PIL only solution for creating a bi-level (black and white) image with a custom threshold:

from PIL import Image
img = Image.open('mB96s.png')
thresh = 200
fn = lambda x : 255 if x > thresh else 0
r = img.convert('L').point(fn, mode='1')
r.save('foo.png')

With just

r = img.convert('1')
r.save('foo.png')

you get a dithered image.

From left to right the input image, the black and white conversion result and the dithered result:

You can click on the images to view the unscaled versions.

edited Mar 22 '19 at 12:32

answered Apr 29 '18 at 19:47

maxschlepzig

35,645
14
145
182

12

This should probably be the accepted answer-- it economically achieves the requested result without additional libraries. – Jose Nario Aug 09 '19 at 20:48
1

what if instead of white pixels we wanted them to be transparent? – Shmack Jan 09 '20 at 20:09
@ShanerM13 A black-and-white image has one bit for each pixel's color value: it can be 1 or 0. That leaves room for black and white but not a third option such as transparent (unless you're in charge of how the images get handled and can define one of those options to mean transparent in your application). – user2616155 Mar 07 '20 at 22:17
@user2616155 maybe a better question for me to ask, at least now, is how do I make the "background" white instead of black as the default? – Shmack Jun 18 '21 at 21:58

score 29 · Answer 3 · edited Nov 28 '17 at 17:28

Another option (which is useful e.g. for scientific purposes when you need to work with segmentation masks) is simply apply a threshold:

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""Binarize (make it black and white) an image with Python."""

from PIL import Image
from scipy.misc import imsave
import numpy


def binarize_image(img_path, target_path, threshold):
    """Binarize an image."""
    image_file = Image.open(img_path)
    image = image_file.convert('L')  # convert image to monochrome
    image = numpy.array(image)
    image = binarize_array(image, threshold)
    imsave(target_path, image)


def binarize_array(numpy_array, threshold=200):
    """Binarize a numpy array."""
    for i in range(len(numpy_array)):
        for j in range(len(numpy_array[0])):
            if numpy_array[i][j] > threshold:
                numpy_array[i][j] = 255
            else:
                numpy_array[i][j] = 0
    return numpy_array


def get_parser():
    """Get parser object for script xy.py."""
    from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
    parser = ArgumentParser(description=__doc__,
                            formatter_class=ArgumentDefaultsHelpFormatter)
    parser.add_argument("-i", "--input",
                        dest="input",
                        help="read this file",
                        metavar="FILE",
                        required=True)
    parser.add_argument("-o", "--output",
                        dest="output",
                        help="write binarized file hre",
                        metavar="FILE",
                        required=True)
    parser.add_argument("--threshold",
                        dest="threshold",
                        default=200,
                        type=int,
                        help="Threshold when to show white")
    return parser


if __name__ == "__main__":
    args = get_parser().parse_args()
    binarize_image(args.input, args.output, args.threshold)

It looks like this for ./binarize.py -i convert_image.png -o result_bin.png --threshold 200:

A one-liner for `binarize_array` (quicker too I guess) : `numpy.where(numpy_array > threshold=200, 255, 0)` — Jacquot, Jun 03 '16 at 14:40
This works perfectly for my google search of converting an image to black and white only... Thanks! — LampShade, Aug 22 '16 at 07:04
You don't need numpy for the binarization - [PIL is sufficient for this](https://stackoverflow.com/a/50090612/427158). — maxschlepzig, Apr 29 '18 at 19:49

score 7 · Answer 4 · answered Mar 08 '17 at 15:22

As Martin Thoma has said, you need to normally apply thresholding. But you can do this using simple vectorization which will run much faster than the for loop that is used in that answer.

The code below converts the pixels of an image into 0 (black) and 1 (white).

from PIL import Image
import numpy as np
import matplotlib.pyplot as plt

#Pixels higher than this will be 1. Otherwise 0.
THRESHOLD_VALUE = 200

#Load image and convert to greyscale
img = Image.open("photo.png")
img = img.convert("L")

imgData = np.asarray(img)
thresholdedData = (imgData > THRESHOLD_VALUE) * 1.0

plt.imshow(thresholdedData)
plt.show()

thresholdedData was giving me a black image. I replaced it with: `thresholdedData = np.where(imgData > THRESHOLD_VALUE, 255, 0)`. You can then use `Image.fromarray()` (I think it was) to load the image in PIL, then do .save(".bmp") to save it to your file system. So matplotlib is not required. — Shmack, Oct 11 '21 at 22:39

score 2 · Answer 5 · answered Jul 01 '19 at 19:02

A simple way to do it using python :

Python
import numpy as np
import imageio

image = imageio.imread(r'[image-path]', as_gray=True)

# getting the threshold value
thresholdValue = np.mean(image)

# getting the dimensions of the image
xDim, yDim = image.shape

# turn the image into a black and white image
for i in range(xDim):
    for j in range(yDim):
        if (image[i][j] > thresholdValue):
            image[i][j] = 255
        else:
            image[i][j] = 0

score 1 · Answer 6 · answered Jun 01 '21 at 11:50

1

this is how i did it its havd better results like a gray filter

from PIL import Image
img = Image.open("profile.png")
BaW = img.convert("L")
BaW.save("profileBaW.png")
BaW.show()

answered Jun 01 '21 at 11:50

Asghar Ale

51
2
6

Using PIL to turn a RGB image into a pure black and white image

6 Answers6

Linked