如果 numpy 在您的机器上可用，请尝试执行以下操作:

If numpy is available on your machine, try doing something like:

import numpy as np
from PIL import Image

im = Image.open('fig1.png')
data = np.array(im)

r1, g1, b1 = 0, 0, 0 # Original value
r2, g2, b2 = 255, 255, 255 # Value that we want to replace it with

red, green, blue = data[:,:,0], data[:,:,1], data[:,:,2]
mask = (red == r1) & (green == g1) & (blue == b1)
data[:,:,:3][mask] = [r2, g2, b2]

im = Image.fromarray(data)
im.save('fig1_modified.png')

它会使用多一点 (3x) 的内存，但它应该会更快(~5x，但对于更大的图像更多).

It will use a bit (3x) more memory, but it should be considerably (~5x, but more for bigger images) faster.

另请注意，如果您只有 RGB(而不是 RGBA)图像，则上面的代码比需要的代码稍微复杂一些.但是，此示例将单独保留 alpha 波段，而更简单的版本则不会.

Also note that the code above is slightly more complicated than it needs to be if you only have RGB (and not RGBA) images. However, this example will leave the alpha band alone, whereas a simpler version wouldn't have.