data_loader.py 文件源码

def _load_samples(csv_name, image_type):
    filename_queue = tf.train.string_input_producer(
        [csv_name])

    reader = tf.TextLineReader()
    _, csv_filename = reader.read(filename_queue)

    record_defaults = [tf.constant([], dtype=tf.string),
                       tf.constant([], dtype=tf.string)]

    filename_i, filename_j = tf.decode_csv(
        csv_filename, record_defaults=record_defaults)

    file_contents_i = tf.read_file(filename_i)
    file_contents_j = tf.read_file(filename_j)
    if image_type == '.jpg':
        image_decoded_A = tf.image.decode_jpeg(
            file_contents_i, channels=model.IMG_CHANNELS)
        image_decoded_B = tf.image.decode_jpeg(
            file_contents_j, channels=model.IMG_CHANNELS)
    elif image_type == '.png':
        image_decoded_A = tf.image.decode_png(
            file_contents_i, channels=model.IMG_CHANNELS, dtype=tf.uint8)
        image_decoded_B = tf.image.decode_png(
            file_contents_j, channels=model.IMG_CHANNELS, dtype=tf.uint8)

    return image_decoded_A, image_decoded_B