class_docstr: Default Mask RCNN validation transform.
  
  Parameters
  ----------
  short : int, default is 600
      Resize image shorter side to ``short``.
  max_size : int, default is 1000
      Make sure image longer side is smaller than ``max_size``.
  mean : array-like of size 3
      Mean pixel values to be subtracted from image tensor. Default is [0.485, 0.456, 0.406].
  std : array-like of size 3
      Standard deviation to be divided from image. Default is [0.229, 0.224, 0.225].
class_docstr_tok: ["Default","Mask","RCNN","validation","transform",".","Parameters","--","--","--","--","--","short",":","int",",","default","is","600","Resize","image","shorter","side","to","``","short","``",".","max_size",":","int",",","default","is","1000","Make","sure","image","longer","side","is","smaller","than","``","max_size","``",".","mean",":","array-like","of","size","3","Mean","pixel","values","to","be","subtracted","from","image","tensor",".","Default","is","[","0.485",",","0.456",",","0.406","]",".","std",":","array-like","of","size","3","Standard","deviation","to","be","divided","from","image",".","Default","is","[","0.229",",","0.224",",","0.225","]","."]
docstr: Apply transform to validation image/label.
docstr_tok: ["Apply","transform","to","validation","image\/label","."]
code: def __call__(self, src, label, mask):
      """Apply transform to validation image/label."""
      # resize shorter side but keep in max_size
      h, _, _ = src.shape
      img = timage.resize_short_within(
          src, self._short, self._max_size, interp=1
      )
      # no scaling ground-truth, return image scaling ratio instead
      im_scale = float(img.shape[0]) / h
  
      img = mx.nd.image.to_tensor(img)
      img = mx.nd.image.normalize(img, mean=self._mean, std=self._std)
      return img, mx.nd.array([img.shape[-2], img.shape[-1], im_scale])
  
imports: from __future__ import absolute_import
  import copy
  from random import randint
  import mxnet
  from ..None import bbox
  from ..None import image
  from ..None import mask
label_desc: Use image node_id 2 for calling the MaskRCNNDefaultValTransform obj's underlying member method code with example usage: obj.__call__(src, label, mask) and returns: img,  mx