17

I have two images, both with alpha channels. I want to put one image over the other, resulting in a new image with an alpha channel, just as would occur if they were rendered in layers. I would like to do this with the Python Imaging Library, but recommendations in other systems would be fantastic, even the raw math would be a boon; I could use NumPy.

Brian Burns
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Kris Kowal
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  • this worked for me: im.paste(image, box, mask) http://stackoverflow.com/questions/5324647/how-to-merge-a-transparant-png-image-with-another-image-using-pil – Gonzo Dec 16 '11 at 14:13

3 Answers3

31

This appears to do the trick:

from PIL import Image
bottom = Image.open("a.png")
top = Image.open("b.png")

r, g, b, a = top.split()
top = Image.merge("RGB", (r, g, b))
mask = Image.merge("L", (a,))
bottom.paste(top, (0, 0), mask)
bottom.save("over.png")
sam
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Kris Kowal
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    @~unutbu No, yours works better. I've incorporated your solution in my project. – Kris Kowal Aug 02 '10 at 03:08
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    Just tried this one and (a) it works quite nicely, at least for the quick-and-dirty task I'm doing and (b) doesn't require numpy to be installed. Note the comment above though. – dpjanes Jun 20 '11 at 11:16
25

Pillow 2.0 now contains an alpha_composite function that does this. 

img3 = Image.alpha_composite(img1, img2)
olt
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19

I couldn't find an alpha composite function in PIL, so here is my attempt at implementing it with numpy:

import numpy as np
from PIL import Image

def alpha_composite(src, dst):
    '''
    Return the alpha composite of src and dst.

    Parameters:
    src -- PIL RGBA Image object
    dst -- PIL RGBA Image object

    The algorithm comes from http://en.wikipedia.org/wiki/Alpha_compositing
    '''
    # http://stackoverflow.com/a/3375291/190597
    # http://stackoverflow.com/a/9166671/190597
    src = np.asarray(src)
    dst = np.asarray(dst)
    out = np.empty(src.shape, dtype = 'float')
    alpha = np.index_exp[:, :, 3:]
    rgb = np.index_exp[:, :, :3]
    src_a = src[alpha]/255.0
    dst_a = dst[alpha]/255.0
    out[alpha] = src_a+dst_a*(1-src_a)
    old_setting = np.seterr(invalid = 'ignore')
    out[rgb] = (src[rgb]*src_a + dst[rgb]*dst_a*(1-src_a))/out[alpha]
    np.seterr(**old_setting)    
    out[alpha] *= 255
    np.clip(out,0,255)
    # astype('uint8') maps np.nan (and np.inf) to 0
    out = out.astype('uint8')
    out = Image.fromarray(out, 'RGBA')
    return out

For example given these two images,

img1 = Image.new('RGBA', size = (100, 100), color = (255, 0, 0, 255))
draw = ImageDraw.Draw(img1)
draw.rectangle((33, 0, 66, 100), fill = (255, 0, 0, 128))
draw.rectangle((67, 0, 100, 100), fill = (255, 0, 0, 0))
img1.save('/tmp/img1.png')

enter image description here 

img2 = Image.new('RGBA', size = (100, 100), color = (0, 255, 0, 255))
draw = ImageDraw.Draw(img2)
draw.rectangle((0, 33, 100, 66), fill = (0, 255, 0, 128))
draw.rectangle((0, 67, 100, 100), fill = (0, 255, 0, 0))
img2.save('/tmp/img2.png')

enter image description here

alpha_composite produces:

img3 = alpha_composite(img1, img2)
img3.save('/tmp/img3.png')

enter image description here

unutbu
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