对两个黑白图像进行异或运算

问题描述

从用PIL模块创建的两个图像im1和im2开始，我们有相应的黑白图像，

Starting with two images im1 and im2 created with the PIL module, we have the corresponding black and white images,

bw_im1 = im1.convert('1')

和

bw_im2 = im2.convert('1')

bw_im2和bw_im2的每个像素为0或256.

Each pixel of bw_im2 and bw_im2 is either 0 or 256.

假设bw_im2和bw_im2的大小相同.

我的工作

我编写了以下 stub/概念证明 Python程序，但担心使用代码(解包/翻译)会很复杂.可能会有更直接有效的方法来处理两个图像中的像素.

I wrote the following stub / proof of concept Python program, but worried that using the code (unpacking/translating over) would be complicated. There might be a more direct and efficient way to process the pixels in the two images.

import numpy as np

M = np.zeros((2, 3))
M[0,2] = 255
M[1,0] = 255
M[1,1] = 255
print(M)

N = np.zeros((2, 3))
N = np.zeros((2, 3))
N[0,2] = 255
N[1,1] = 255
N[1,2] = 255
print(N)

list_M = list(M)
list_N = list(N)
xor_signal = 0
for row in range(0, len(list_M)):
    for col in range(0,len(list_M[row])):
        xor_signal = xor_signal + int(bool(list_M[row][col]) !=  bool(list_N[row][col]))

print(xor_signal)

输出

[[  0.   0. 255.]
 [255. 255.   0.]]
[[  0.   0. 255.]
 [  0. 255. 255.]]
2

推荐答案

您可以像这样使用PIL的 ImageChops :

You can use PIL's ImageChops like this:

#!/usr/local/bin/python3
import numpy as np
from PIL import Image, ImageChops

# Open images
im1 = Image.open("im1.png")
im2 = Image.open("im2.png")

result = ImageChops.logical_xor(im1,im2)
result.save('result.png')

因此，如果您从以下两个开始:

So, if you start with these two:

结果将是:

当然，如果您是物理学家，则可以这样写;-)

Of course, if you are a physicist, you can write that like this ;-)

#!/usr/local/bin/python3
from PIL import Image, ImageChops
ImageChops.logical_xor(Image.open("im1.png"), Image.open("im2.png")).save('result.png')

---

或者您可以像这样使用Numpy的XOR:

---

Or you can use Numpy's XOR like this:

#!/usr/local/bin/python3
import numpy as np
from PIL import Image

# Open images
im1 = Image.open("im1.png")
im2 = Image.open("im2.png")

# Make into Numpy arrays
im1np = np.array(im1)*255
im2np = np.array(im2)*255

# XOR with Numpy
result = np.bitwise_xor(im1np, im2np).astype(np.uint8)

# Convert back to PIL image and save
Image.fromarray(result).save('result.png')

您可以通过在末尾添加像素来求和:

You can sum the pixels by adding this at the end:

print('Sum: {}'.format(np.sum(result)))

---

或者您不必费心编写任何Python，只需在终端中输入以下 ImageMagick 命令:

---

Or you can not bother writing any Python and just type the following ImageMagick command into your Terminal:

magick im1.png im2.png -evaluate-sequence xor result.png

如果您使用的是v6或更早的版本，请改用以下内容:

If you are using v6, or older, use the following instead:

convert im1.png im2.png -evaluate-sequence xor result.png

这篇关于对两个黑白图像进行异或运算的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！