model.py 文件源码

def read_and_decode(filename_queue):
    reader = tf.TFRecordReader()
    _, serialized_example = reader.read(filename_queue)
    features = tf.parse_single_example(
            serialized_example,
            features={
                'image_raw': tf.FixedLenFeature([], tf.string),
            })

    image = tf.decode_raw(features['image_raw'], tf.uint8)
    image.set_shape(128 * 128 * 3)
    image = tf.reshape(image, [128, 128, 3])

    image = tf.cast(image, tf.float32) * (2. / 255) - 1.

    return image