class_docstr: a standard bbox assigner based on max IoU, use ppdet's label_box 
  as backend.
  Args:
      positive_overlap (float): threshold for defining positive samples 
      negative_overlap (float): threshold for denining negative samples
      allow_low_quality (bool): whether to lower IoU thr if a GT poorly
          overlaps with candidate bboxes
code: def __call__(self, bboxes, gt_bboxes):
      matches, match_labels = label_box(
          bboxes,
          gt_bboxes,
          positive_overlap=self.positive_overlap,
          negative_overlap=self.negative_overlap,
          allow_low_quality=self.allow_low_quality,
          ignore_thresh=-1,
          is_crowd=None,
          assign_on_cpu=False,
      )
      return matches, match_labels
  
file_path: PaddleDetection/ppdet/modeling/assigners/max_iou_assigner.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from ppdet.core.workspace import register
  from ppdet.modeling.proposal_generator.target import label_box
label_desc: Use image node_id 2 for calling the MaxIoUAssigner obj's underlying member method code with example usage: obj.__call__(bboxes, gt_bboxes) and returns: matches,  match_labels