Replace specific pixels by rgb with white color

Question

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

Answer 1

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.

Answer 2

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)