如何找到 numpy 数组中图像的差异？

Question

我正在尝试计算 2 张图像之间的差异。我希望得到一个整数作为我的结果，但我没有得到我期望的结果。

from imageio import imread
#https://raw.githubusercontent.com/glennford49/sampleImages/main/cat1.png
#https://raw.githubusercontent.com/glennford49/sampleImages/main/cat2.png
img1="cat1.png" # 183X276
img2="cat2.png" # 183x276
numpyImg1=[]
numpyImg2=[]
img1=imread(img1)
img2=imread(img2)
numpyImg1.append(img1)
numpyImg2.append(img2)
diff = numpyImg1[0] - numpyImg2[0] 
result = sum(abs(diff)) 

print("difference:",result)

打印：

# it prints an array of images rather than printing an interger only

目标：

difference: <int>

Answer 1

一张（彩色）图像是一个 3D 矩阵，所以您可以做的是使用 numpy.array(image) 将这些图像转换为 numpy 数组，然后您可以获得这两个 numpy数组。

最终答案将是一个 3 维数组

Answer 2

我相信numpy数组的维数不是1，你需要对数组的维数进行求和的次数才能有一个和值。

   [1,2,3]
    sum gives : 6

   [[1,2,3],[1,2,3]]
   sum gives : [2,4,6]
   doing a second sum opertion gives
     : 12 (single value)

您可能需要在打印数据之前再添加一个“sum(result)”（如果图像是二维的）。

例如：

     numpyImg2.append(img2)
     diff = numpyImg1[0] - numpyImg2[0] 
     result = sum(abs(diff)) 

     result = sum(result) >> Repeat

     print("difference:",result)

Answer 3

这是我在 rgb 通道中找到 2 个图像差异的答案。

如果要减去2张相同的图像，印刷：每像素差异：0

from numpy import sum
from imageio import imread

#https://github.com/glennford49/sampleImages/blob/main/cat2.png
#https://github.com/glennford49/sampleImages/blob/main/cat2.png
img1="cat1.png"
img2="cat2.png"
numpyImg1=[]
numpyImg2=[]
img1=imread(img1)
img2=imread(img2)
numpyImg1.append(img1)
numpyImg2.append(img2)
diff = numpyImg1[0] - numpyImg2[0] 
result = sum(diff/numpyImg1[0].size)
result = sum(abs(result.reshape(-1))) 
print("difference per pixel:",result)

Answer 4

您正在使用 Python 的内置 sum 函数，它也只对绝对计算执行求和 along the first dimension of a NumPy array. This is the reason why you are getting a 2D array as the output instead of the single integer you expect. Please use numpy.sum on your result instead which will internally flatten a multi-dimensional NumPy array then sum over the results. In addition, you might as well use numpy.abs:

import numpy as np

result = np.sum(np.abs(diff))

使用 numpy.sum 意味着您不再需要在使用答案中的内置 sum 函数之前将数组重塑为扁平化表示。对于未来的开发，始终对要对 NumPy 数组执行的任何算术运算使用 NumPy 方法。它可以防止意外行为，例如您刚才看到的。

如何找到 numpy 数组中图像的差异？

How to find the difference of images in numpy arrays?

python

numpy

opencv

python-imaging-library

scikit-image