Writing a 3D numpy array into a slice of a larger 3D array using a 2D mask

Question

I have two 3D numpy arrays, each representing an image (x, y, rgb). I want to write the smaller image into the larger image, except for any magenta pixels (255, 0, 255). I know how to generate a 2D mask representing all the magenta pixels -- how can I use this 2D mask in a 3D array operation?

user707650 · Accepted Answer · 2016-04-09 01:30:08Z

2

Here is one example. It's not precisely accurate (all values are one or two), but gives the idea. Hopefully this works in your situation:

image1 = np.ones((5,5,16))
image2 = 2 * np.ones((3,3,16))
mask = np.array([[0, 1, 1], [0, 0, 1], [1, 0, 0]])
x, y = np.where(mask)
image1[1:4,1:4,:][x,y,:] = image2[x,y,:]

(1:4,1:4 is the position of the subimage inside the larger image.)

answered Apr 9, 2016 at 1:30

user707650

Sign up to request clarification or add additional context in comments.

1 Comment

Tom Quinn Over a year ago

For those trying to use this in numpypy, it won't work -- apparently 1-arg where isn't implemented yet. Is there another method that pypy has a better chance of supporting?

Collectives™ on Stack Overflow

Writing a 3D numpy array into a slice of a larger 3D array using a 2D mask

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related