How can i convert mnist data to RGB format?

Question

I am trying to convert MNIST dataset to RGB format, the actual shape of each image is (28, 28), but i need (28, 28, 3).

import numpy as np
import tensorflow as tf

mnist = tf.keras.datasets.mnist
(x_train, _), (x_test, _) = mnist.load_data()

X = np.concatenate([x_train, x_test])
X = X / 127.5 - 1

X.reshape((70000, 28, 28, 1))

tf.image.grayscale_to_rgb(
    X,
    name=None
)

But i get the following error:

ValueError: Dimension 1 in both shapes must be equal, but are 84 and 3. Shapes are [28,84] and [28,3].

Answer 1

You should store the reshaped 3D [28x28x1] images in an array:

X = X.reshape((70000, 28, 28, 1))

When converting, set an other array to the return value of the tf.image.grayscale_to_rgb() function :

X3 = tf.image.grayscale_to_rgb(
X,
name=None
)

Finally, to plot out one example from the resulting tensor images with matplotlib and tf.session():

import matplotlib.pyplot as plt

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    image_to_plot = sess.run(image)
    plt.figure()
    plt.imshow(image_to_plot)
    plt.grid(False)

The complete code:

import numpy as np
import tensorflow as tf

mnist = tf.keras.datasets.mnist
(x_train, _), (x_test, _) = mnist.load_data()

X = np.concatenate([x_train, x_test])
X = X / 127.5 - 1

# Set reshaped array to X 
X = X.reshape((70000, 28, 28, 1))

# Convert images and store them in X3
X3 = tf.image.grayscale_to_rgb(
    X,
    name=None
)

# Get one image from the 3D image array to var. image
image = X3[0,:,:,:]

# Plot it out with matplotlib.pyplot
import matplotlib.pyplot as plt

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    image_to_plot = sess.run(image)
    plt.figure()
    plt.imshow(image_to_plot)
    plt.grid(False)