[python] inverting image in Python with OpenCV

I want to load a color image, convert it to grayscale, and then invert the data in the file.

What I need: to iterate over the array in OpenCV and change every single value with this formula (it might be wrong but it seems reasonable for me):

img[x,y] = abs(img[x,y] - 255)

but I don't understand why doesn't it works:

def inverte(imagem, name):
    imagem = abs(imagem - 255)
    cv2.imwrite(name, imagem)


def inverte2(imagem, name):
    for x in np.nditer(imagem, op_flags=['readwrite']):
        x = abs(x - 255)
    cv2.imwrite(name, imagem)


if __name__ == '__main__':
    nome = str(sys.argv[1])
    image = cv2.imread(nome)
    gs_imagem = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    inverte(gs_imagem, "invertida.png")
    inverte2(gs_imagem, "invertida2.png")

I don't want to do an explicit loop (I am trying to be more pythonic). I can see that in one image that got a white background it turned black, but only this it doesn't looks like the other colors are having much (if any) change.

Alternatively, you could invert the image using the bitwise_not function of OpenCV:

imagem = cv2.bitwise_not(imagem)

I liked this example.

You can use "tilde" operator to do it:

import cv2
image = cv2.imread("img.png")
image = ~image
cv2.imwrite("img_inv.png",image)

This is because the "tilde" operator (also known as unary operator) works doing a complement dependent on the type of object

for example for integers, its formula is:

x + (~x) = -1

but in this case, opencv use an "uint8 numpy array object" for its images so its range is from 0 to 255

so if we apply this operator to an "uint8 numpy array object" like this:

import numpy as np
x1 = np.array([25,255,10], np.uint8) #for example
x2 = ~x1
print (x2)

we will have as a result:

[230 0 245]

because its formula is:

x2 = 255 - x1

and that is exactly what we want to do to solve the problem.