mnist fashion output for 7, 8, 9 images from test dataset in python

To output the images of class 7, 8, and 9 from the Fashion MNIST test dataset in Python, you can use the following code snippet:

main.py
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.datasets import fashion_mnist

# Load the Fashion MNIST dataset
(_, _), (X_test, y_test) = fashion_mnist.load_data()

# Get the indices of images with labels 7, 8, and 9
class_indices = np.where(np.isin(y_test, [7, 8, 9]))[0]

# Display the images with labels 7, 8, and 9
plt.figure(figsize=(10, 5))
for i, index in enumerate(class_indices[:3]):
    plt.subplot(1, 3, i+1)
    plt.imshow(X_test[index], cmap='gray')
    plt.title(f"Label: {y_test[index]}")
    plt.axis('off')
plt.tight_layout()
plt.show()
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This code snippet uses the fashion_mnist dataset from the tensorflow.keras.datasets module. It loads the test dataset and retrieves the indices of images with labels 7, 8, and 9 using np.where and np.isin functions. Then, it displays the first 3 images along with their corresponding labels using matplotlib.pyplot.imshow.

Make sure you have the tensorflow and matplotlib libraries installed in your Python environment.

Note that Fashion MNIST is a different dataset from the regular MNIST digits dataset, but the code provided can be easily adapted to the regular MNIST dataset by changing the label values accordingly.