如何将 mnist 数据转换为 RGB 格式？

Question

我正在尝试将 MNIST 数据集转换为 RGB 格式，每个图像的实际形状是 (28, 28)，但我需要 (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
)

但我收到以下错误：

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

Answer 1

您应该将重塑的 3D [28x28x1] 图像存储在数组中：

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

转换时，将另一个数组设置为函数的返回值tf.image.grayscale_to_rgb()：

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

matplotlib最后，使用和从生成的张量图像中绘制一个示例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)

完整代码：

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)