使用PIL,您可以antialias by supersampling。例如,
import numpy as np
from PIL import Image
from PIL import ImageDraw
scale = 2
width, height = 300, 200
img = Image.new('L', (width, height), 0)
draw = ImageDraw.Draw(img)
draw.line([(50, 50), (250, 150)], fill=255, width=10)
img = img.resize((width//scale, height//scale), Image.ANTIALIAS)
img.save('/tmp/antialiased.png')
antialiased = np.asarray(img)
print(antialiased[25:35, 25:35])
# [[252 251 250 255 255 237 127 18 0 0]
# [255 251 253 254 251 255 255 237 127 18]
# [184 255 255 254 252 254 251 255 255 237]
# [ 0 72 184 255 255 254 252 254 251 255]
# [ 1 0 0 72 184 255 255 254 252 254]
# [ 0 3 1 0 0 72 184 255 255 254]
# [ 0 0 0 3 1 0 0 72 184 255]
# [ 0 0 0 0 0 3 1 0 0 72]
# [ 0 0 0 0 0 0 0 3 1 0]
# [ 0 0 0 0 0 0 0 0 0 3]]
img = Image.new('L', (width//scale, height//scale), 0)
draw = ImageDraw.Draw(img)
draw.line([(25, 25), (125, 75)], fill=255, width=5)
img.save('/tmp/aliased.png')
aliased = np.asarray(img)
print(aliased[25:35, 25:35])
# [[255 255 255 255 255 255 255 0 0 0]
# [255 255 255 255 255 255 255 255 255 0]
# [255 255 255 255 255 255 255 255 255 255]
# [ 0 0 255 255 255 255 255 255 255 255]
# [ 0 0 0 0 255 255 255 255 255 255]
# [ 0 0 0 0 0 0 255 255 255 255]
# [ 0 0 0 0 0 0 0 0 255 255]
# [ 0 0 0 0 0 0 0 0 0 0]
# [ 0 0 0 0 0 0 0 0 0 0]
# [ 0 0 0 0 0 0 0 0 0 0]]
antialiased.png:
![enter image description here](https://i.stack.imgur.com/R934T.png)
aliased.png
![enter image description here](https://i.stack.imgur.com/mj4Vf.png)