File .zip yang di download cukup di extract dan disarankan tidak dilakukan perubahan pada folder ataupun file manapun

root_file = '/content/Gender_Final' # kalian nanti sesuaikan saja file path pada notebook kalian

# untuk mengetahui path root kalian bagaimana cukup klik kanan pada file Gender_Final, kemudian klik 'copy path', terakhir tinggal copy paste pada root_file.

import tensorflow as tf
import numpy as np
import os

def load_data(image_root = root_file, img_size=(64, 64), batch_size=32, as_numpy=True):
    train_dir = os.path.join(image_root, 'train')
    test_dir = os.path.join(image_root, 'val')

    train_ds = tf.keras.utils.image_dataset_from_directory(
        train_dir,
        labels='inferred',
        label_mode='binary',
        image_size=img_size,
        batch_size=batch_size,
        shuffle=True
    )

    test_ds = tf.keras.utils.image_dataset_from_directory(
        test_dir,
        labels='inferred',
        label_mode='binary',
        image_size=img_size,
        batch_size=batch_size,
        shuffle=False
    )

    if as_numpy:
        def to_numpy(dataset):
            x, y = [], []
            for imgs, labels in dataset:
                x.append(imgs.numpy())
                y.append(labels.numpy())
            x = np.concatenate(x, axis=0)
            y = np.concatenate(y, axis=0).reshape(-1, 1)
            return x.astype(np.uint8), y.astype(np.uint8)

        train_data = to_numpy(train_ds)
        test_data = to_numpy(test_ds)
        return train_data, test_data

    return train_ds, test_ds

(X_train, y_train), (X_test, y_test) = load_data()

Found 1845 files belonging to 2 classes.
Found 462 files belonging to 2 classes.