datapipe.py 文件源码

def read_my_file_format(filename_queue, resize_shape=None):
    """Sets up part of the pipeline that takes elements from the filename queue
    and turns it into a tf.Tensor of a batch of images.

    :param filename_queue:
        tf.train.string_input_producer object
    :param resize_shape:
        2 element list defining the shape to resize images to.
    """
    reader = tf.TFRecordReader()
    key, serialized_example = reader.read(filename_queue)
    features = tf.parse_single_example(
        serialized_example, features={
            'image/encoded': tf.FixedLenFeature([], tf.string),
            'image/height': tf.FixedLenFeature([], tf.int64),
            'image/channels': tf.FixedLenFeature([], tf.int64),
            'image/width': tf.FixedLenFeature([], tf.int64)})
    example = tf.image.decode_jpeg(features['image/encoded'], 3)
    processed_example = preprocessing(example, resize_shape)
    return processed_example