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