cyclegan.py 文件源码

def build_batch_reader(paths_image, batch_size):
    """
    """
    file_name_queue = tf.train.string_input_producer(paths_image)

    reader_key, reader_val = tf.WholeFileReader().read(file_name_queue)

    # decode a raw input image
    image = tf.image.decode_jpeg(reader_val, channels=3)

    # to float32 and -1.0 ~ +1.0
    image = tf.cast(image, dtype=tf.float32) / 127.5 - 1.0

    # scale up to increase training data
    image = tf.image.resize_images(image, [264, 264])

    # crop to 256 x 256 for the model.
    # also, a batch need concreate image size
    image = tf.random_crop(image, size=[256, 256, 3])

    # random horizontal flipping to increase training data
    image = tf.image.random_flip_left_right(image)

    # create bacth
    return tf.train.batch(tensors=[image], batch_size=batch_size)