使用 PIL 将 RGBA PNG 转换为 RGB

Question

我正在使用 PIL 将通过 Django 上传的透明 PNG 图像转换为 JPG 文件。输出看起来损坏了。

源文件

代码

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，生成的图像如下所示：

有办法解决这个问题吗？我想要白色背景，以前是透明背景。

---

解决方案

感谢出色的答案，我提出了以下函数集合：

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，但留下了丑陋的边框，因为它不处理半透明地区。

纯 PIL 和 numpy 合成解决方案都给出了很好的结果，但 alpha_composite_with_color 比 pure_pil_alpha_to_color (79.6 毫秒) 快得多 (8.93 毫秒)。 如果 numpy 在您的系统上可用，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。）

$ 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

这是一个更简单的版本 - 不确定它的性能如何。很大程度上基于我在构建 RGBA -> 时发现的一些 django 片段JPG + BG 支持 sorl 缩略图。

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%

Answer 2

通过使用 Image.alpha_composite，Yuji 'Tomita' Tomita 的解决方案变得更简单。如果 png 没有 Alpha 通道，此代码可以避免元组索引超出范围错误。

from PIL import Image

png = Image.open(img_path).convert('RGBA')
background = Image.new('RGBA', png.size, (255, 255, 255))

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

Answer 3

透明部分大多具有 RGBA 值（0,0,0,0）。由于JPG没有透明度，因此jpeg值设置为(0,0,0)，即黑色。

圆形图标周围有一些具有非零 RGB 值的像素，其中 A = 0。因此它们在 PNG 中看起来是透明的，但在 JPG 中看起来颜色很有趣。

您可以使用 numpy 将 A == 0 处的所有像素设置为 R = G = B = 255，如下所示：

import Image
import numpy as np

FNAME = 'logo.png'
img = Image.open(FNAME).convert('RGBA')
x = np.array(img)
r, g, b, a = np.rollaxis(x, axis = -1)
r[a == 0] = 255
g[a == 0] = 255
b[a == 0] = 255
x = np.dstack([r, g, b, a])
img = Image.fromarray(x, 'RGBA')
img.save('/tmp/out.jpg')

---

请注意，徽标还有一些半透明像素，用于平滑文字和图标周围的边缘。保存为 jpeg 会忽略半透明，使生成的 jpeg 看起来相当锯齿状。

使用 imagemagick 的 convert 命令可以得到更好的质量结果：

convert logo.png -background white -flatten /tmp/out.jpg

">

---

alpha 合成：

import Image
import numpy as np

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            

FNAME = 'logo.png'
img = Image.open(FNAME).convert('RGBA')
white = Image.new('RGBA', size = img.size, color = (255, 255, 255, 255))
img = alpha_composite(img, white)
img.save('/tmp/out.jpg')

Answer 4

这是纯 PIL 的解决方案。

def blend_value(under, over, a):
    return (over*a + under*(255-a)) / 255

def blend_rgba(under, over):
    return tuple([blend_value(under[i], over[i], over[3]) for i in (0,1,2)] + [255])

white = (255, 255, 255, 255)

im = Image.open(object.logo.path)
p = im.load()
for y in range(im.size[1]):
    for x in range(im.size[0]):
        p[x,y] = blend_rgba(white, p[x,y])
im.save('/tmp/output.png')

Answer 5

它没有坏。它完全按照你的指示去做；这些像素是黑色且完全透明。您将需要迭代所有像素并将完全透明的像素转换为白色。

Answer 6

import numpy as np
import PIL

def convert_image(image_file):
    image = Image.open(image_file) # this could be a 4D array PNG (RGBA)
    original_width, original_height = image.size

    np_image = np.array(image)
    new_image = np.zeros((np_image.shape[0], np_image.shape[1], 3)) 
    # create 3D array

    for each_channel in range(3):
        new_image[:,:,each_channel] = np_image[:,:,each_channel]  
        # only copy first 3 channels.

    # flushing
    np_image = []
    return new_image

Answer 7

已经给出了最好的答案：

from PIL import Image
img = Image.open("image.png")
bg = Image.new("RGBA",img.size,(255,255,255))
img = Image.alpha_composite(bg,img) # puts our image on top of white background
img.convert("RGB").save("image_rgb.png")

但在看到这些解决方案之前，我自己是这样做的。我分享它只是因为它是最容易理解其工作原理的。 （每个像素如何混合）

from PIL import Image
import numpy

data = numpy.array(Image.open("image.png"))
h,w = data.shape[:2]

def lerp(a,b,f): return [round(a[i]+(b[i]-a[i])*f) for i in (0,1,2)]

for x in range(w):
    for y in range(h):
        r,g,b,a = data[y][x]
        r,g,b = lerp((255,255,255),(r,g,b),a/255) # blend ontop of white based on alpha amount
        data[y][x] = (r,g,b,255)

Image.fromarray(data).convert("RGB").save("image_rgb.png")

我们所做的就是在白色（alpha = 0）和现有像素之间进行插值。 (alpha=255)

这两种解决方案创建的图像与您使用“画图”重新保存图像时获得的图像完全相同。 （您可以使用 (data1==data2).all() 进行检查）lerp() 函数中需要 round() 来准确地说。我将像素保存到浮点数组中，以查看与重新保存的图像中的像素相比得到的结果，并了解像素应如何舍入。 （即 180 vs 180.3 和 214 vs 213.7）四舍五入到最接近的值是有意义的。

现在我只需要知道如何准确地调整 Paint 的大小。

Answer 8

from PIL import Image
 
def fig2img ( fig ):
    """
    @brief Convert a Matplotlib figure to a PIL Image in RGBA format and return it
    @param fig a matplotlib figure
    @return a Python Imaging Library ( PIL ) image
    """
    # put the figure pixmap into a numpy array
    buf = fig2data ( fig )
    w, h, d = buf.shape
    return Image.frombytes( "RGBA", ( w ,h ), buf.tostring( ) )

def fig2data ( fig ):
    """
    @brief Convert a Matplotlib figure to a 4D numpy array with RGBA channels and return it
    @param fig a matplotlib figure
    @return a numpy 3D array of RGBA values
    """
    # draw the renderer
    fig.canvas.draw ( )
 
    # Get the RGBA buffer from the figure
    w,h = fig.canvas.get_width_height()
    buf = np.fromstring ( fig.canvas.tostring_argb(), dtype=np.uint8 )
    buf.shape = ( w, h, 4 )
 
    # canvas.tostring_argb give pixmap in ARGB mode. Roll the ALPHA channel to have it in RGBA mode
    buf = np.roll ( buf, 3, axis = 2 )
    return buf

def rgba2rgb(img, c=(0, 0, 0), path='foo.jpg', is_already_saved=False, if_load=True):
    if not is_already_saved:
        background = Image.new("RGB", img.size, c)
        background.paste(img, mask=img.split()[3]) # 3 is the alpha channel

        background.save(path, 'JPEG', quality=100)   
        is_already_saved = True
    if if_load:
        if is_already_saved:
            im = Image.open(path)
            return np.array(im)
        else:
            raise ValueError('No image to load.')

Answer 9

基于上面的示例：

它接收 RGBA 图像并返回将 alpha 通道转换为白色的 RGB 图像。

from PIL import Image

def imageAlphaToWhite(image):
    background = Image.new("RGBA", image.size, "WHITE")
    alpha_composite_img = Image.alpha_composite(background, image)
    rgb_img = alpha_composite_img.convert("RGB")
    return rgb_img