There is an image like that

I used a website to detect the rgb of the background and it is 42,44,54. Aiming at replacing the pixels with that rgb to white Here's my try but I didn't get the expected output

import cv2
import numpy as np

# Load image
im = cv2.imread('Sample.png')

# Make all perfectly green pixels white
im[np.all(im == (42,44,54), axis=-1)] = (255, 255, 255)

# Save result
cv2.imwrite('Output.png',im)

I have searched again and found the following code (works to somewhat)

from PIL import Image

img = Image.open("Sample.png")
img = img.convert("RGB")

datas = img.getdata()

new_image_data = []
for item in datas:
    # change all white (also shades of whites) pixels to yellow
    if item[0] in list(range(42, 44)):
        new_image_data.append((255, 255, 255))
    else:
        new_image_data.append(item)
        
# update image data
img.putdata(new_image_data)

# save new image
img.save("Output.png")

# show image in preview
img.show()

I need also to change any other rgb to be black except white pixels. Simply to get all colored characters into black after removing the background color

I am stil trying (waiting for experts to contribute and offer a better solution). The following is quite good but not so perfect till now

from PIL import Image
import numpy as np

img = Image.open("Sample.png")
width = img.size[0]
height = img.size[1]

for i in range(0,width):
    for j in range(0,height):
        data = img.getpixel((i,j))
        if (data[0]>=36 and data[0]<=45) and (data[1]>=38 and data[1]<=45) and (data[2]>=46 and data[2]<=58):
            img.putpixel((i,j),(255, 255, 255))
        if (data[0]==187 and data[1]==187 and data[2]==191):
            img.putpixel((i,j),(255, 255, 255))

img.save("Output.png")

I thought of converting the image to grayscale using Pillow

from PIL import Image

img = Image.open('Sample.png').convert('LA')
img.save('Grayscale.png')

The image became cleared but how to replace rgb pixels in such mode? I tried the same previous code and changed the rgb values but didn't work and there are errors as the mode is L

CodePudding user response：

You can do both steps in one go:

from PIL import Image

def is_background(item, bg):
    # Tweak the ranges if the result is still unsatisfying 
    return (item[0] in range(bg[0] - 20, bg[0]   20)) or \
           (item[1] in range(bg[1] - 20, bg[1]   20)) or \
           (item[2] in range(bg[2] - 20, bg[2]   20))

img = Image.open("Sample.png")
img = img.convert("RGB")
datas = img.getdata()

bg = [42, 44, 54] # Background RGB color
new_image_data = []
for item in datas:
    # change all background to white and keep all white
    if is_background(item, bg) or item == (255, 255, 255):
        new_image_data.append((255, 255, 255))
    else:
        # change non-background and non-white to black
        new_image_data.append((0, 0, 0))


img.putdata(new_image_data)
img.save("Output.png")
img.show()

Here is the result.

Note that:

• We need is_background because the background is not of the exact same color, there is a very slight variation

• This method of detecting background is very basic and there are much more sophisticated ones.

CodePudding user response：

The issue is OpenCV follows BGR format and your pixel value is RGB. Fix that as follows.

# Make all perfectly green pixels white
im[np.all(im == (54,44,42), axis=-1)] = (255, 255, 255)