How to mask out the object from the image?

Question

I have a RGB image of 256X256 with the binary mask. I want to remove the object from the main image with the help of mask and keep the rest background.

I have tried with the below code but it didn't work.

Can anyone let me know where I made the mistake?

import cv2
import numpy as np

# read image
img = cv2.imread('image.jpg')

mask2 = cv2.imread('mask.jpg') / 1
# mask by multiplication, clip to range 0 to 255 and make integer
result2 = (img * mask2).clip(0, 255).astype(np.uint8)



# save results
cv2.imwrite('result.png', result1)

Image, Mask:

Output I want, The result I am getting:

Answer 1

You need to use cv2.bitwise_and for your problem. It performs 'AND' operation between your img and mask in a bitwise manner.

• For white region in the mask , corresponding img region is preserved
• For white region in the mask , corresponding img region is occluded

Code:

img = cv2.imread(r'C:\Users\524316\Desktop\Stack\eye\eye.jpg')
mask = cv2.imread(r'C:\Users\524316\Desktop\Stack\eye\mask.jpg', 0)

# invert the mask
th = cv2.threshold(mask,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)[1]

# preserve the background
res = cv2.bitwise_and(img, img, mask = th)

Result:

Answer 2

You don't need Otsu thresholding, just ordinary thresholding, with a sensible threshold. Your "mask" image is a JPEG. Lossy compression causes it to not be entirely black or white.

Once you have the mask, you just need to learn about masking operations. That is a feature of numpy I'm using here:

im = cv.imread("VgAjK.jpg")
maskim = cv.imread("ZKKkp.jpg", cv.IMREAD_GRAYSCALE)

im[maskim >= 128] = 255 # "remove", paint over with white

You multiplied... that might have worked (except inverted) if your arrays had the right value ranges.