Adding alpha channel to RGB array using numpy

Question

I have an image array in RGB space and want to add the alpha channel to be all zeros. Specifically, I have a numpy array with shape (205, 54, 3) and I want to change the shape to (205, 54, 4) with the additional spot in the third dimension being all 0.0's. Which numpy operation would achieve this?

Answer 1

You could use one of the stack functions (stack/hstack/vstack/dstack/concatenate) to join multiple arrays together.

numpy.dstack( ( your_input_array, numpy.zeros((205, 54)) ) )

Answer 2

If you have your current image as rgb variable then just use:

rgba = numpy.concatenate((rgb, numpy.zeros((205, 54, 1))), axis=2)

Concatenate function merge rgb and zeros array together. Zeros function creates array of zeros. We set axis to 2 what means we merge in the thirde dimensions. Note: axis are counted from 0.

Answer 3

np array style, stack on depth dimension(channel dimension, 3rd dimension):

rgba = np.dstack((rgb, np.zeros(rgb.shape[:-1])))

but you should use OpenCV function:

rgba = cv2.cvtColor(rgb, cv2.COLOR_RGB2RGBA)

Answer 4

not sure if your still looking for an answer.

recently i am looking to achieve the exact same thing you are looking to do with numpy because i needed to force a 24 bit depth png into a 32. I agree that it makes sense to use dstack, but i couldnt get it to work. i used insert instead and it seems to achieved my goal.

# for your code it would look like the following:
rgba = numpy.insert(
    rgb,
    3, #position in the pixel value [ r, g, b, a <-index [3]  ]
    255, # or 1 if you're going for a float data type as you want the alpha to be fully white otherwise the entire image will be transparent.
    axis=2, #this is the depth where you are inserting this alpha channel into
)

hope this helps, good luck.