class_docstr: Default validation transform for AlphaPose.
  
  Parameters
  ----------
  num_joints : int
      Number of joints defined by dataset
  joint_pairs: list
      Paired Joints for horizontal flipping
  image_size : tuple of int
      Image size, as (height, width).
  sigma : float
      Gaussian sigma for the heatmap generation.
code: def __call__(self, src, label, img_path):
      src = src.asnumpy()
      bbox = label["bbox"]
      assert len(bbox) == 4
      score = label.get("score", 1)
      img, scale_box = detector_to_alpha_pose(
          src,
          class_ids=mx.nd.array([[0.0]]),
          scores=mx.nd.array([[1.0]]),
          bounding_boxs=mx.nd.array(np.array([bbox])),
          output_shape=self._image_size,
      )
  
      return img[0], scale_box, score, img_path
  
file_path: gluon-cv/gluoncv/data/transforms/presets/alpha_pose.py
imports: from __future__ import absolute_import
  import random
  import numpy
  import mxnet
  from ..pose import random_sample_bbox, count_visible, random_crop_bbox
  from ..pose import drawGaussian, transformBox, cv_cropBox, cv_rotate, detector_to_alpha_pose
label_desc: Use image node_id 2 for calling the AlphaPoseDefaultValTransform obj's underlying member method code with example usage: obj.__call__(src, label, img_path) and returns: img,  scale_box,  score,  img_path