class_docstr: Default SSD validation transform.
  
  Parameters
  ----------
  width : int
      Image width.
  height : int
      Image height.
  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):
      """Apply transform to validation image/label."""
      # resize
      h, w, _ = src.shape
      img = timage.imresize(src, self._width, self._height, interp=9)
      bbox = tbbox.resize(
          label, in_size=(w, h), out_size=(self._width, self._height)
      )
  
      img = mx.nd.image.to_tensor(img)
      img = mx.nd.image.normalize(img, mean=self._mean, std=self._std)
      return img, bbox.astype(img.dtype)
  
imports: from __future__ import absolute_import
  import numpy
  import mxnet
  from ..None import bbox
  from ..None import image
  from ..None import experimental
  from ....utils import try_import_dali
label_desc: Use image node_id 2 for calling the SSDDefaultValTransform obj's underlying member method code with example usage: obj.__call__(src, label) and returns: img,  bbox