import tensorflow as tf

    features = {'member/name': tf.io.FixedLenFeature([], tf.string),
                'member/encoded': tf.io.FixedLenFeature([], tf.string),
                'member/age': tf.io.FixedLenFeature([], tf.int64),
                'member/height': tf.io.VarLenFeature(tf.float32),
                'member/prefer_prods': tf.io.VarLenFeature(tf.int64)}
    features = tf.io.parse_single_example(example_proto, features)
    images = tf.image.decode_png(features['member/encoded'], channels=3)
    # 注意png原本有4個channel，但執行到下面的處理會出錯，所以前一行先降成3個channel。
    images = tf.image.random_brightness(images, 0.1)
    images = tf.image.random_saturation(images, 0.7, 1.3)
    images = tf.image.random_contrast(images, 0.6, 1.5)
    images = tf.image.random_flip_left_right(images)
