如何在Python中随机化图像像素

Question

我是计算视觉和Python的新手，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()

原始图像

我尝试随机化图像像素的图像

Answer 1

np.ravel()你不是在打乱像素，而是在使用时和之后打乱一切np.shuffle()。

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。

• np.zeros不需要预分配（如果您需要它，只需rgbImg.shape作为参数传递，无需解压单独的值）