Replace a range of colors with a specific color in python

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@Missing, I tried " image[np.where((image==[0,0,0]).all(axis=2))] = [255,255,255] ", but returns " AttributeError: 'bool' object has no attribute 'all' ", so I guess it another way, image[np.where((image==[0,0,0])).all(axis=2)] = [255,255,255], but still telling me a error "AttributeError: 'tuple' object has no attribute 'all' "

Your first attemp should work correctly. Did you import numpy correctly as np? Do you use your image or the image i created with np.zeros?

import cv2
import numpy as np

    image = np.zeros((400,400,3), dtype="uint8")
    raw = image.copy()
    image[np.where((image==[0,0,0]).all(axis=2))] = [255,255,255]
    cv2.imshow('Test', image)
    cv2.imshow('Test2', raw)
    if cv2.waitKey() == ord('q'):
        cv2.destroyAllWindows()

This is the complete code for the example and it turns a black image into a white one.

Hi, @Missing, actually it works for the original image but it is strange that the resulted mask from inRange() can't be performed on same operation`enter code here.

frame = cv2.imread("/home/ad/Desktop/1.png")
lower_black = np.array([0,0,0], dtype = "uint16")
upper_black = np.array([70,70,70], dtype = "uint16")
black_mask = cv2.inRange(frame, lower_black, upper_black)
frame[np.where((frame == [0,0,0]).all(axis = 2))] = [0,255,255]     # it works
black_mask[np.where((black_mask == [0,0,0]).all(axis = 2))] = [0,255,255]   # it doesn't work

Hey, yes because your original image is in RGB color format. The masked image is just black and white, so you just have one color channel. Change your code to:

black_mask[np.where((black_mask == [0]).all(axis = 1))] = [255]

@Missing, thanks for reminding me this. I tried the approach, it works but only partially, there is some parts not being transformed. Any ideas? I have updated in the main content.

Okay my fault. The problem here is that the call to numpy.all() tests whether the condition is true for the whole array, meaning it checks if every pixel in an image row is black and that is obviously not true in your case. So try it without the numpy.all() function. Just use

black_mask[np.where(black_mask == [0])] = [255]

Thanks a lot, @Missing, it works perfectly and I learned a lot! if you can add it to the answer, I can score it. :)