如何在python中随机化图像像素

Question

我对计算视觉和python还是陌生的，我无法真正弄清楚出了什么问题。我尝试将RGB图像中的所有图像像素随机化，但是事实证明我的图像完全错误，如下所示。有人可以说明一下吗？

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()

原始图片

我尝试将图像像素随机化的图像

Answer 1

将ngOnDestroy()更改为plt.imshow(rdmImg)
这可能与此问题https://github.com/matplotlib/matplotlib/issues/9391/

有关

Answer 2

您没有对像素进行改组，而是在随后使用np.ravel()和np.shuffle()时对所有内容进行了改组。

在对像素进行混洗时，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。只是原始的，白色，灰色，绿色，黑色。

我删除的代码还有其他问题：

• 请勿使用嵌套的for循环，慢点。

• 不需要使用np.zeros进行预分配（如果您需要的话，只需传递rgbImg.shape作为参数，而无需解压缩单独的值）