I am trying to replace objects which I found using a mask with the original images pixels. I have a mask that shows black where the object is not detected and white if detected. I am then using the image in a where statement
image[np.where((image2 == [255,255,255].any(axis = 2))
I am stuck here and I have no idea how to change found white values to what the original image is (to use alongside other masks). I have tried image.shape
and this did not work.
Thanks.
Make a copy of the mask and then draw the original image over the white pixels of the mask from the white pixel coordinates. You can also check mask == 255
to compare element-wise. You don't need np.where because you can index arrays via the boolean mask created by mask == 255
.
out = mask.copy()
out[mask == 255] = original_image[mask == 255]
You can use bitwise operations. Try this:
replaced_image = cv2.bitwise_and(original_image,original_image,mask = your_mask)
Visit https://docs.opencv.org/3.3.0/d0/d86/tutorial_py_image_arithmetics.html to learn more about bitwise operations
import os
import cv2
from netpbmfile import imread
img_dir = '.'
mask_dir = '.'
new_bg = 'image.png'
def get_foreground(fg_image_name, mask_name, bg_image_name):
fg_image = cv2.imread(fg_image_name)
mask = imread(mask_name)
mask_inverse = (1-mask)
bg_image = cv2.imread(bg_image_name)
bg_image = cv2.resize(bg_image, (fg_image.shape[1], fg_image.shape[0]))
foregound = cv2.bitwise_and(fg_image, fg_image, mask=mask)
background = cv2.bitwise_and(bg_image, bg_image, mask=mask_inverse)
composite = foregound + background
return composite
image_fg = get_foreground(os.path.join(img_dir, "NP1_0.jpg"), os.path.join(mask_dir, "NP1_0_mask.pbm"), new_bg)
cv2.imwrite("foreground.jpg", image_fg)
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