ViewImage_Data Set_deepLearning.py

from keras.datasets import cifar10
import matplotlib.pyplot as plt

# List of names for each CIFAR10 class
cifar10_class_names = {
    0: "Plane",
    1: "Car",
    2: "Bird",
    3: "Cat",
    4: "Deer",
    5: "Dog",
    6: "Frog",
    7: "Horse",
    8: "Boat",
    9: "Truck"
}

# Load the entire data set
(x_train, y_train), (x_test, y_test) = cifar10.load_data()

# Loop through each picture in the data set
for i in range(1000):
    # Grab an image from the data set
    sample_image = x_train[i]
    # Grab the image's expected class id
    image_class_number = y_train[i][0]
    # Look up the class name from the class id
    image_class_name = cifar10_class_names[image_class_number]

    # Draw the image as a plot
    plt.imshow(sample_image)
    # Label the image
    plt.title(image_class_name)
    # Show the plot on the screen
    plt.show()