在 Python 和 OpenCV 中反转图像

Question

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.

Answer 1

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)

Answer 2

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

imagem = cv2.bitwise_not(imagem)

I liked this example.

Answer 3

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.

Answer 4

You can also do it with numpy.

import cv2
import numpy as np

image = cv2.imread('your_image', 0)
inverted = np.invert(image)

cv2.imwrite('inverted.jpg', inverted)

Answer 5

在 Python/OpenCV 中，我认为你想要：

img = cv2.absDiff(img, 255)

Answer 6

Why not use the first line in the question with numpy ?

inverted = np.abs(image - 255)

Just as simple as that. No iteration or any other function needed. numpy does that automatically for us :)

Answer 7

    def invert(self, image=None):
        if image is None:
            image = self.image

        image = image.astype("uint8") # --> pay attention to the image type
        inverted = np.invert(image)
        (thresh, im_bw) = cv2.threshold(inverted, 0, 1, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
        return im_bw

Answer 8

A, This script search pink skin pixel in the image.

It create a mask.

It set pink pixel to white and not pink pixels to black

B, Observe the 2 conditions mask>0 and mask==0

import cv2
import numpy as np

# specify desired bgr for mask
desired_color_brg1 = (0,0, 0) #black
desired_color_brg2 = (255,255, 255) #white




# read image in bgr and convert to hsv
path_main_image="../data/person.png"
main_img = cv2.imread(path_main_image)
main_img_hsv=cv2.cvtColor(main_img,cv2.COLOR_BGR2HSV)



# Define lower and uppper limits of what we call "pink skin color"
pink_low=np.array([0,10,60])
pink_hig=np.array([20,150,255])


#create mask
mask=cv2.inRange(main_img_hsv,pink_low,pink_hig)


# Change image to white where we found pink skin
main_img[mask>0]=desired_color_brg1
cv2.imwrite("../data/result1.png",main_img)


# Change image toblack where we NOT found pink skin
main_img[mask==0]=desired_color_brg2
cv2.imwrite("../data/result2.png",main_img)