如何在python中随机化图像像素

我对计算视觉和Python很陌生，我无法真正弄清楚出了什么问题。我尝试随机化 RGB 图像中的所有图像像素，但结果证明我的图像完全错误，如下所示。有人可以解释一下吗？

from scipy import misc

import numpy as np
import matplotlib.pyplot as plt

#Loads an arbitrary RGB image from the misc library
rgbImg = misc.face()     

%matplotlib inline

#Display out the original RGB image 
plt.figure(1,figsize = (6, 4))
plt.imshow(rgbImg)
plt.show()

#Initialise a new array of zeros with the same shape as the selected RGB image 
rdmImg = np.zeros((rgbImg.shape[0], rgbImg.shape[1], rgbImg.shape[2]))
#Convert 2D matrix of RGB image to 1D matrix
oneDImg = np.ravel(rgbImg)

#Randomly shuffle all image pixels
np.random.shuffle(oneDImg)

#Place shuffled pixel values into the new array
i = 0 
for r in range (len(rgbImg)):
    for c in range(len(rgbImg[0])):
        for z in range (0,3):
            rdmImg[r][c][z] = oneDImg[i] 
            i = i + 1

print rdmImg
plt.imshow(rdmImg) 
plt.show()

original image

image of my attempt in randomizing image pixel

当你使用时，你不是在打乱像素，而是在打乱一切np.ravel() and np.shuffle()然后。

当你打乱像素时，你必须确保颜色、RGB 元组保持不变。

from scipy import misc

import numpy as np
import matplotlib.pyplot as plt

#Loads an arbitrary RGB image from the misc library
rgbImg = misc.face()

#Display out the original RGB image
plt.figure(1,figsize = (6, 4))
plt.imshow(rgbImg)
plt.show()

# doc on shuffle: multi-dimensional arrays are only shuffled along the first axis
# so let's make the image an array of (N,3) instead of (m,n,3)

rndImg2 = np.reshape(rgbImg, (rgbImg.shape[0] * rgbImg.shape[1], rgbImg.shape[2]))
# this like could also be written using -1 in the shape tuple
# this will calculate one dimension automatically
# rndImg2 = np.reshape(rgbImg, (-1, rgbImg.shape[2]))



#now shuffle
np.random.shuffle(rndImg2)

#and reshape to original shape
rdmImg = np.reshape(rndImg2, rgbImg.shape)

plt.imshow(rdmImg)
plt.show()

这是随机的浣熊，注意颜色。那里没有红色或蓝色。只是原来的，白色，灰色，绿色，黑色。

我删除的代码还存在一些其他问题：

• 不要使用嵌套的for循环，速度慢。

• 预分配与np.zeros不需要（如果你需要它，只需传递rgbImg.shape作为参数，无需解压单独的值）