class_docstr: Base class for instance masks.
class_docstr_tok: ["Base","class","for","instance","masks","."]
docstr: Rescale masks as large as possible while keeping the aspect ratio.
  For details can refer to `mmcv.imrescale`.
  
  Args:
      scale (tuple[int]): The maximum size (h, w) of rescaled mask.
      interpolation (str): Same as :func:`mmcv.imrescale`.
  
  Returns:
      BaseInstanceMasks: The rescaled masks.
docstr_tok: ["Rescale","masks","as","large","as","possible","while","keeping","the","aspect","ratio",".","For","details","can","refer","to","`","mmcv.imrescale","`",".","Args",":","scale","(","tuple","[","int","]",")",":","The","maximum","size","(","h",",","w",")","of","rescaled","mask",".","interpolation","(","str",")",":","Same","as",":","func",":","`","mmcv.imrescale","`",".","Returns",":","BaseInstanceMasks",":","The","rescaled","masks","."]
code: def rescale(self, scale, interpolation="nearest"):
      """Rescale masks as large as possible while keeping the aspect ratio.
      For details can refer to `mmcv.imrescale`.
  
      Args:
          scale (tuple[int]): The maximum size (h, w) of rescaled mask.
          interpolation (str): Same as :func:`mmcv.imrescale`.
  
      Returns:
          BaseInstanceMasks: The rescaled masks.
      """
      pass
  
imports: from abc import ABCMeta, abstractmethod
  import cv2
  import mmcv
  import numpy
  import pycocotools.mask
  import torch
  from mmcv.ops.roi_align import roi_align
label_desc: Use image node_id 1 for calling the BaseInstanceMasks obj's underlying member method code with example usage: obj.rescale(scale, interpolation) without return types