If I download the CIFAR 10 Images in Keras via:
(x_train, y_train), (x_test, y_test) = cifar10.load_data() # Getting shape x_train.shape >>> (50000, 32, 32, 3)
I can then plot each image by doing:
# Plot RGB image plt.imshow(x_train) # Plot only one colour-channel e.g. R plt.imshow(x_train[:,:,0])
Now I get the MNIST images via Keras by doing:
(X_train, y_train), (X_test, y_test) = mnist.load_data() # getting shape X_train.shape >>> (60000, 28, 28)
However it doesn’t have a depth channel which should be 1 as it’s grayscale. If I reshape it using:
X_train = X_train.reshape(X_train.shape,28,28,1)
I can get the Neural Net to work but I can not plot it anymore. What is the correct way to reshape it so that I can still plot things?
If you reshape the training and testing set, you have to reshape the images back to plot them.
X_train = X_train.reshape(X_train.shape, 28, 28, 1) X_test = X_test.reshape(X_test.shape, 28, 28, 1) ... plt.imshow(X_train[num].reshape(28,28))
Answered By – Farhan
Answer Checked By – Clifford M. (AngularFixing Volunteer)