def __init__(self,
                 origin_target_size=[800, 1333],
                 target_size=[],
                 interp=cv2.INTER_LINEAR,
                 use_flip=True):
        """
        Rescale image to the each size in target size, and capped at max_size.
        Args:
            origin_target_size (list): origin target size of image
            target_size (list): A list of target sizes of image.
            interp (int): the interpolation method.
            use_flip (bool): whether use flip augmentation.
        """
        super(MultiscaleTestResize, self).__init__()
        self.interp = interp
        self.use_flip = use_flip

        if not isinstance(target_size, Sequence):
            raise TypeError(
                "Type of target_size is invalid. Must be List or Tuple, now is {}".
                format(type(target_size)))
        self.target_size = target_size

        if not isinstance(origin_target_size, Sequence):
            raise TypeError(
                "Type of origin_target_size is invalid. Must be List or Tuple, now is {}".
                format(type(origin_target_size)))

        self.origin_target_size = origin_target_size

        Rescale image to the each size in target size, and capped at max_size.
        Args:
            origin_target_size (list): origin target size of image
            target_size (list): A list of target sizes of image.
            interp (int): the interpolation method.
            use_flip (bool): whether use flip augmentation.
        
ppdet/data/transform/operators.py