使用opencv的matlplotlib提供具有相同像素值的不同图像

Question

I've been trying to modify the pixels of an image slightly, but the colors are getting distorted. So, I multiplied every pixel with 1 and saw the result.

Here's my code

import numpy as np
from matplotlib import pyplot as plt
import cv2

mud1 = cv2.imread('mud.jpeg')
print mud1.shape

mask = np.random.random_integers(1,1,size=(81,81,3))

print mask.shape
print mask[21][21][2]
print mud1[21][21][2]
mud1new = np.multiply(mud1,mask)
print mud1new[21][21][2]

plt.subplot(121),plt.imshow(mud1),plt.title('Original')
plt.xticks([]), plt.yticks([])
plt.subplot(122),plt.imshow(mud1new),plt.title('Masked')
plt.xticks([]), plt.yticks([])
plt.savefig('problem.jpeg')
plt.show()

The pixels remain unchanged but somehow the image I see is different.

Answer 1

The issue is because np.random.random_integers returns objects that are int64 whereas your loaded image is uint8 so when you multiply the two together, mud1new becomes an int64 array. When using imshow , it expects the following types

• MxN – values to be mapped (float or int)
• MxNx3 – RGB (float or uint8)
• MxNx4 – RGBA (float or uint8)

To fix this, you should cast mud1new as a uint8 prior to display with imshow

mud1new = mud1new.astype(np.unit8)
plt.imshow(mud1new)

You could also convert mud1new to a float but that would require that all of your values should be between 0 and 1 so you'd have to divide everything by 255.

The value for each component of MxNx3 and MxNx4 float arrays should be in the range 0.0 to 1.0.

mud1new_float = mud1new.astype(np.float) / 255.0;
plt.imshow(mud1new_float)