code: def random_sample_bbox(ul, br, w, h, im_width, im_height):
      """Take random sample"""
      patch_scale = random.uniform(0, 1)
      if patch_scale > 0.85:
          ratio = float(h) / w
          if w < h:
              patch_w = patch_scale * w
              patch_h = patch_w * ratio
          else:
              patch_h = patch_scale * h
              patch_w = patch_h / ratio
          xmin = ul[0] + random.uniform(0, 1) * (w - patch_w)
          ymin = ul[1] + random.uniform(0, 1) * (h - patch_h)
          xmax = xmin + patch_w + 1
          ymax = ymin + patch_h + 1
      else:
          xmin = max(
              1,
              min(
                  ul[0] + np.random.normal(-0.0142, 0.1158) * w,
                  im_width - 3,
              ),
          )
          ymin = max(
              1,
              min(
                  ul[1] + np.random.normal(0.0043, 0.068) * h,
                  im_height - 3,
              ),
          )
          xmax = min(
              max(
                  xmin + 2, br[0] + np.random.normal(0.0154, 0.1337) * w
              ),
              im_width - 3,
          )
          ymax = min(
              max(
                  ymin + 2,
                  br[1] + np.random.normal(-0.0013, 0.0711) * h,
              ),
              im_height - 3,
          )
  
      ul[0] = xmin
      ul[1] = ymin
      br[0] = xmax
      br[1] = ymax
      return ul, br
  
imports: from __future__ import absolute_import
  from __future__ import division
  import math
  import random
  import numpy
  import mxnet
  from mxnet import nd, image
  from mxnet.gluon.data.vision import transforms
  from ...utils.filesystem import try_import_cv2
label_desc: Use image node_id 18 for calling a global function with example usage: random_sample_bbox(ul, br, w, h, im_width, im_height) and returns: ul,  br