使用Python Imaging Library（PIL），如何使用alpha通道組合圖像而不是另一個圖像？

Question

我有兩個圖像，都有alpha通道。 我想將一個圖像放在另一個圖像上，從而生成帶有alpha通道的新圖像，就像它們在圖層中呈現一樣。 我想用Python Imaging Library做到這一點，但是其他系統中的建議會很棒，即使原始數學也是一個好處; 我可以使用NumPy。

Answer 1

這似乎可以解決問題：

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")

Answer 2

Pillow 2.0現在包含一個執行此操作的alpha_composite函數。

img3 = Image.alpha_composite(img1, img2)

Answer 3

我在PIL中找不到alpha復合函數，所以這是我用numpy實現它的嘗試：

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

例如，鑒於這兩個圖像，

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')

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')

alpha_composite產生：

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