Select segmented color images using an array with mask in bulk and imshow

Question

I am new to the numpy masked array data structure and I want to use it to work with segmented color images.

When I use matplotlibs plt.imshow (masked_gray_image, "gray") to display a gray masked image, invalid regions will appear transparent, which is what I want. However, when I do the same for color images, it does not seem to work. Interestingly, the data point cursor will not show the rgb [r, g, b] values, but empty [], but still the color values ​​are displayed instead of transparent.

Am I doing something wrong or is it not already provided for in matplotlib imshow?

import numpy as np
import matplotlib.pyplot as plt
from scipy.misc import face

img_col = face() #example image from scipy 
img_gray = np.dot(img_col[...,:3], [0.299, 0.587, 0.114]) #convert to gray
threshold = 25 
mask2D = img_gray < threshold # some exemplary mask 
mask3D = np.atleast_3d(mask2D)*np.ones_like(img_col) # expand to 3D with broadcasting...
# using numpy masked array to specify where data is valid
m_img_gray = np.ma.masked_where( mask2D, img_gray)
m_img_col  = np.ma.masked_where( mask3D, img_col)

fig,axes=plt.subplots(1,4,num=2,clear=True)
axes[0].imshow(mask2D.astype(np.float32)) # plot mask
axes[0].set_title("simple mask")
axes[1].imshow(m_img_gray,"gray") #plot gray verison => works 
axes[1].set_title("(works)\n masked gray")
axes[2].imshow(m_img_col)  #plot color version, => does not work
axes[2].set_title("(doesn't work)\n masked color")

# manually adding mask as alpha channel to show what I want
axes[3].imshow( np.append( m_img_col.data, 255*(1-(0 < np.sum(m_img_col.mask ,axis=2,keepdims=True) ).astype(np.uint8) ),axis=2) )
axes[3].set_title("(desired) \n alpha channel set manually")

Here is an example image:

[]: ...

Answer 1

, matplotlib, 255, True:

m_img_col.data[m_img_col.mask]=255

,