resnet_common.py 文件源码

def _deserialize_image_record(cls, record):
        feature_map = {
            'image/encoded': tf.FixedLenFeature([], tf.string, ''),
            'image/class/label': tf.FixedLenFeature([1], tf.int64, -1),
            'image/class/text': tf.FixedLenFeature([], tf.string, ''),
            'image/object/bbox/xmin': tf.VarLenFeature(dtype=tf.float32),
            'image/object/bbox/ymin': tf.VarLenFeature(dtype=tf.float32),
            'image/object/bbox/xmax': tf.VarLenFeature(dtype=tf.float32),
            'image/object/bbox/ymax': tf.VarLenFeature(dtype=tf.float32)
        }
        with tf.name_scope('deserialize_image_record'):
            obj = tf.parse_single_example(record, feature_map)
            imgdata = obj['image/encoded']
            label = tf.cast(obj['image/class/label'], tf.int32)
            bbox = tf.stack([obj['image/object/bbox/%s' % x].values
                             for x in ['ymin', 'xmin', 'ymax', 'xmax']])
            bbox = tf.transpose(tf.expand_dims(bbox, 0), [0, 2, 1])
            text = obj['image/class/text']
            return imgdata, label, bbox, text