["python","arrays","opencv","numpy","image-processing"]
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) As recommended in the answer by Eric Olmon, you can also invert the image using the bitwise_not function of OpenCV: imagem = cv2.bitwise_not(imagem)