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