predictions3.py

test_pred = model.predict(test_images)
test_pred = np.argmax(test_pred,axis=1)
test_actual = np.argmax(test_labels,axis=1)

rnd_idx = random.sample(range(0,400),8)

class_labels = {i:class_name for (class_name,i) in class_name_labels.items()}

for i,idx in enumerate(rnd_idx):
    plt.imshow(test_images[idx])
    plt.title("Actual: {}\nPredicted: {}".format(class_labels[test_actual[idx]],class_labels[test_pred[idx]]))
    plt.grid(None)
    plt.show()
    pass