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Why plt.imshow() doesn't display the image?

I am a newbie to keras, and when I tried to run my first keras program on my linux, something just didn't go as I wish. Here is my python code:

import numpy as np
np.random.seed(123)
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Convolution2D, MaxPooling2D
from keras.utils import np_utils
from keras.datasets import mnist
(X_train,y_train),(X_test,y_test) = mnist.load_data()
print X_train.shape
from matplotlib import pyplot as plt
plt.imshow(X_train[0])

The last sentence doesn't display anything. I copied those codes from a tutorial with out any modification. And there is nothing wrong with the backend of matplotlib on my computer. I have tested that through the code below.

import matplotlib.pyplot as plt

data = [[0, 0.25], [0.5, 0.75]]

fig, ax = plt.subplots()
im = ax.imshow(data, cmap=plt.get_cmap('hot'), interpolation='nearest',
               vmin=0, vmax=1)
fig.colorbar(im)
plt.show()

https://i.stack.imgur.com/2r6Lw.png

Moreover, I can get X_train[0] printed and it seems nothing wrong. So what could be the reason for that? Why the imshow() function in my first code didn't display anything?

Try adding plt.show() at the end of your code snippet.
This problem often comes up when you copy code from Jupyter

M
Marcin Możejko

The solution was as simple as adding plt.show() at the end of the code snippet:

import numpy as np
np.random.seed(123)
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Convolution2D, MaxPooling2D
from keras.utils import np_utils
from keras.datasets import mnist
(X_train,y_train),(X_test,y_test) = mnist.load_data()
print X_train.shape
from matplotlib import pyplot as plt
plt.imshow(X_train[0])
plt.show()

This just avoid answering WHY while getting 168 upvote...Strange
March 2021. The same thing is still missing in the tutorial tensorflow.org/tutorials/images/transfer_learning
s
shaik moeed

plt.imshow just finishes drawing a picture instead of printing it. If you want to print the picture, you just need to add plt.show.


From that point of view, it would be better and less confusing to rename the "imshow" to "imdraw". Don't you agree?
@AramParonikyan matplotlib is layers upon layers of confusion and hellish design. One day people will move onto a better library (cv2 is even more confusing)
W
WestCoastProjects

plt.imshow displays the image on the axes, but if you need to display multiple images you use show() to finish the figure. The next example shows two figures:

import numpy as np
from keras.datasets import mnist
(X_train,y_train),(X_test,y_test) = mnist.load_data()
from matplotlib import pyplot as plt
plt.imshow(X_train[0])
plt.show()
plt.imshow(X_train[1])
plt.show()

In Google Colab, if you comment out the show() method from previous example just a single image will display (the later one connected with X_train[1]).

Here is the content from the help:

plt.show(*args, **kw)
        Display a figure.
        When running in ipython with its pylab mode, display all
        figures and return to the ipython prompt.

        In non-interactive mode, display all figures and block until
        the figures have been closed; in interactive mode it has no
        effect unless figures were created prior to a change from
        non-interactive to interactive mode (not recommended).  In
        that case it displays the figures but does not block.

        A single experimental keyword argument, *block*, may be
        set to True or False to override the blocking behavior
        described above.



plt.imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, shape=None, filternorm=1, filterrad=4.0, imlim=None, resample=None, url=None, hold=None, data=None, **kwargs)
        Display an image on the axes.

Parameters
----------
X : array_like, shape (n, m) or (n, m, 3) or (n, m, 4)
    Display the image in `X` to current axes.  `X` may be an
    array or a PIL image. If `X` is an array, it
    can have the following shapes and types:

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

    The value for each component of MxNx3 and MxNx4 float arrays
    should be in the range 0.0 to 1.0. MxN arrays are mapped
    to colors based on the `norm` (mapping scalar to scalar)
    and the `cmap` (mapping the normed scalar to a color).

R
Rajat

If you want to print the picture using imshow() you also execute plt.show()


The phrasing is confusing. For an answer it seems rather thin on details and explanation. Could you please edit to elaborate. It currently seems like something which was posted in the middle of writing it...
How is this different from what has been already said in the 3 answers above?