使用PIL将RGBA PNG转换为RGB [英] Convert RGBA PNG to RGB with PIL
问题描述
我正在使用PIL将用Django上传的透明PNG图片转换为JPG文件.输出看起来坏了.
I'm using PIL to convert a transparent PNG image uploaded with Django to a JPG file. The output looks broken.
Image.open(object.logo.path).save('/tmp/output.jpg', 'JPEG')
或
Image.open(object.logo.path).convert('RGB').save('/tmp/output.png')
结果
两种方式下,生成的图像如下所示:
Result
Both ways, the resulting image looks like this:
是否可以解决此问题?我想使用白色背景,而以前是透明背景.
Is there a way to fix this? I'd like to have white background where the transparent background used to be.
由于给出了很好的答案,我提出了以下函数集合:
Thanks to the great answers, I've come up with the following function collection:
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,但由于它不能处理半透明区域,因此留下了丑陋的边框.
Performance
The simple non-compositing alpha_to_color
function is the fastest solution, but leaves behind ugly borders because it does not handle semi transparent areas.
纯PIL和numpy合成解决方案均可提供出色的结果,但是alpha_composite_with_color
(8.93毫秒)比pure_pil_alpha_to_color
(79.6毫秒)快得多. 如果您的系统上有numpy,那就可以了.(更新:新的纯PIL版本是所有提到的解决方案中最快的.)
Both the pure PIL and the numpy compositing solutions give great results, but alpha_composite_with_color
is much faster (8.93 msec) than pure_pil_alpha_to_color
(79.6 msec). If numpy is available on your system, that's the way to go. (Update: The new pure PIL version is the fastest of all mentioned solutions.)
$ 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
推荐答案
这里的版本要简单得多-不确定性能如何.大量基于我在构建RGBA -> JPG + BG
对单一缩略图的支持时发现的一些django代码段.
Here's a version that's much simpler - not sure how performant it is. Heavily based on some django snippet I found while building RGBA -> JPG + BG
support for sorl thumbnails.
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%
Result @ 50%
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