使用PIL将RGBA PNG转换为RGB

Question

我使用PIL将Django上传的透明PNG图像转换为JPG文件。输出看起来坏了。

源文件

代码

Image.open(object.logo.path).save('/tmp/output.jpg', 'JPEG')

或者

Image.open(object.logo.path).convert('RGB').save('/tmp/output.png')

结果

从这两个方面来看，生成的图像如下所示：

有办法解决这个问题吗？我想要白色的背景，透明的背景。

---

解决方案

多亏了这些出色的答案，我想出了以下函数集合：

import Image
import numpy as np


def alpha_to_color(image, color=(255, 255, 255)):
    """Set all fully transparent pixels of an RGBA image to the specified color.
    This is a very simple solution that might leave over some ugly edges, due
    to semi-transparent areas. You should use alpha_composite_with color instead.

    Source: http://stackoverflow.com/a/9166671/284318

    Keyword Arguments:
    image -- PIL RGBA Image object
    color -- Tuple r, g, b (default 255, 255, 255)

    """ 
    x = np.array(image)
    r, g, b, a = np.rollaxis(x, axis=-1)
    r[a == 0] = color[0]
    g[a == 0] = color[1]
    b[a == 0] = color[2] 
    x = np.dstack([r, g, b, a])
    return Image.fromarray(x, 'RGBA')


def alpha_composite(front, back):
    """Alpha composite two RGBA images.

    Source: http://stackoverflow.com/a/9166671/284318

    Keyword Arguments:
    front -- PIL RGBA Image object
    back -- PIL RGBA Image object

    """
    front = np.asarray(front)
    back = np.asarray(back)
    result = np.empty(front.shape, dtype='float')
    alpha = np.index_exp[:, :, 3:]
    rgb = np.index_exp[:, :, :3]
    falpha = front[alpha] / 255.0
    balpha = back[alpha] / 255.0
    result[alpha] = falpha + balpha * (1 - falpha)
    old_setting = np.seterr(invalid='ignore')
    result[rgb] = (front[rgb] * falpha + back[rgb] * balpha * (1 - falpha)) / result[alpha]
    np.seterr(**old_setting)
    result[alpha] *= 255
    np.clip(result, 0, 255)
    # astype('uint8') maps np.nan and np.inf to 0
    result = result.astype('uint8')
    result = Image.fromarray(result, 'RGBA')
    return result


def alpha_composite_with_color(image, color=(255, 255, 255)):
    """Alpha composite an RGBA image with a single color image of the
    specified color and the same size as the original image.

    Keyword Arguments:
    image -- PIL RGBA Image object
    color -- Tuple r, g, b (default 255, 255, 255)

    """
    back = Image.new('RGBA', size=image.size, color=color + (255,))
    return alpha_composite(image, back)


def pure_pil_alpha_to_color_v1(image, color=(255, 255, 255)):
    """Alpha composite an RGBA Image with a specified color.

    NOTE: This version is much slower than the
    alpha_composite_with_color solution. Use it only if
    numpy is not available.

    Source: http://stackoverflow.com/a/9168169/284318

    Keyword Arguments:
    image -- PIL RGBA Image object
    color -- Tuple r, g, b (default 255, 255, 255)

    """ 
    def blend_value(back, front, a):
        return (front * a + back * (255 - a)) / 255

    def blend_rgba(back, front):
        result = [blend_value(back[i], front[i], front[3]) for i in (0, 1, 2)]
        return tuple(result + [255])

    im = image.copy()  # don't edit the reference directly
    p = im.load()  # load pixel array
    for y in range(im.size[1]):
        for x in range(im.size[0]):
            p[x, y] = blend_rgba(color + (255,), p[x, y])

    return im

def pure_pil_alpha_to_color_v2(image, color=(255, 255, 255)):
    """Alpha composite an RGBA Image with a specified color.

    Simpler, faster version than the solutions above.

    Source: http://stackoverflow.com/a/9459208/284318

    Keyword Arguments:
    image -- PIL RGBA Image object
    color -- Tuple r, g, b (default 255, 255, 255)

    """
    image.load()  # needed for split()
    background = Image.new('RGB', image.size, color)
    background.paste(image, mask=image.split()[3])  # 3 is the alpha channel
    return background

性能

简单的非合成alpha_to_color函数是最快的解决方案，但由于它不处理半透明区域，因此会留下难看的边界。

纯PIL和numpy复合溶液的结果都很好，但是alpha_composite_with_color比pure_pil_alpha_to_color（79.6msec）快得多（8.93msec）。如果numpy在您的系统上可用，那就是方法。（更新：新的pure PIL版本是所有提到的解决方案中速度最快的。）

$ python -m timeit "import Image; from apps.front import utils; i = Image.open(u'logo.png'); i2 = utils.alpha_to_color(i)"
10 loops, best of 3: 4.67 msec per loop
$ python -m timeit "import Image; from apps.front import utils; i = Image.open(u'logo.png'); i2 = utils.alpha_composite_with_color(i)"
10 loops, best of 3: 8.93 msec per loop
$ python -m timeit "import Image; from apps.front import utils; i = Image.open(u'logo.png'); i2 = utils.pure_pil_alpha_to_color(i)"
10 loops, best of 3: 79.6 msec per loop
$ python -m timeit "import Image; from apps.front import utils; i = Image.open(u'logo.png'); i2 = utils.pure_pil_alpha_to_color_v2(i)"
10 loops, best of 3: 1.1 msec per loop

Answer 1

这是一个简单得多的版本-不知道它的性能如何。主要基于我在构建对sorl缩略图的RGBA -> JPG + BG支持时发现的一些django片段。

from PIL import Image

png = Image.open(object.logo.path)
png.load() # required for png.split()

background = Image.new("RGB", png.size, (255, 255, 255))
background.paste(png, mask=png.split()[3]) # 3 is the alpha channel

background.save('foo.jpg', 'JPEG', quality=80)

结果@80%

结果@50%