preprocess.py

import tensorflow as tf

IMG_SIZE = (224, 224)
BATCH_SIZE = 16

TRAIN_DIR = "dataset/train"
VAL_DIR = "dataset/validation"
TEST_DIR = "dataset/test"

def load_datasets():
    train_ds = tf.keras.preprocessing.image_dataset_from_directory(
        TRAIN_DIR,
        image_size=IMG_SIZE,
        batch_size=BATCH_SIZE,
        label_mode="binary",
        shuffle=True
    )

    val_ds = tf.keras.preprocessing.image_dataset_from_directory(
        VAL_DIR,
        image_size=IMG_SIZE,
        batch_size=BATCH_SIZE,
        label_mode="binary",
        shuffle=False
    )

    test_ds = tf.keras.preprocessing.image_dataset_from_directory(
        TEST_DIR,
        image_size=IMG_SIZE,
        batch_size=BATCH_SIZE,
        label_mode="binary",
        shuffle=False
    )

    return train_ds, val_ds, test_ds