segregated_datasets.py

from keras.applications.vgg16 import VGG16

#Create dataset.  The file_paths method shows train_ds and val_ds are mutually exclusive.
train_ds = tf.keras.utils.image_dataset_from_directory(
  './images/train/',
  labels='inferred',
  shuffle=True,
  seed=8,
  image_size=(224, 224),
  batch_size=32)

val_ds = tf.keras.utils.image_dataset_from_directory(
  './images/valid/',
  labels='inferred',
  shuffle=True,
  seed=8,
  image_size=(224, 224),
  batch_size=32)

class_names = train_ds.class_names
plt.figure(figsize=(10, 10))
for images, labels in train_ds.take(1):
    for i in range(6):
        ax = plt.subplot(3, 3, i + 1)
        plt.imshow(images[i].numpy().astype("uint8"))  #uint is 0 to 255.
        plt.title(class_names[labels[i]]); plt.axis("off");