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.

You almost did it. You were tricked by the fact that abs(imagem-255) will give a wrong result since your dtype is an unsigned integer. You have to do (255-imagem) in order to keep the integers unsigned:

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

You can also invert the image using the bitwise_not function of OpenCV:

imagem = cv2.bitwise_not(imagem)

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.