class_docstr: Assign pixels at the center region of a bbox as positive.
  
  Each proposals will be assigned with `-1`, `0`, or a positive integer
  indicating the ground truth index.
  - -1: negative samples
  - semi-positive numbers: positive sample, index (0-based) of assigned gt
  
  Args:
      pos_scale (float): Threshold within which pixels are
        labelled as positive.
      neg_scale (float): Threshold above which pixels are
        labelled as positive.
      min_pos_iof (float): Minimum iof of a pixel with a gt to be
        labelled as positive. Default: 1e-2
      ignore_gt_scale (float): Threshold within which the pixels
        are ignored when the gt is labelled as shadowed. Default: 0.5
      foreground_dominate (bool): If True, the bbox will be assigned as
        positive when a gt's kernel region overlaps with another's shadowed
        (ignored) region, otherwise it is set as ignored. Default to False.
code: def __init__(
      self,
      pos_scale,
      neg_scale,
      min_pos_iof=1e-2,
      ignore_gt_scale=0.5,
      foreground_dominate=False,
      iou_calculator=dict(type="BboxOverlaps2D"),
  ):
      self.pos_scale = pos_scale
      self.neg_scale = neg_scale
      self.min_pos_iof = min_pos_iof
      self.ignore_gt_scale = ignore_gt_scale
      self.foreground_dominate = foreground_dominate
      self.iou_calculator = build_iou_calculator(iou_calculator)
  
file_path: insightface/detection/scrfd/mmdet/core/bbox/assigners/center_region_assigner.py
imports: import torch
  from ..builder import BBOX_ASSIGNERS
  from ..iou_calculators import build_iou_calculator
  from .assign_result import AssignResult
  from .base_assigner import BaseAssigner
label_desc: Use image node_id 1 to create a new CenterRegionAssigner object from inherited base classes: BaseAssigner with example: obj = CenterRegionAssigner(pos_scale, neg_scale, min_pos_iof, ignore_gt_scale, foreground_dominate, iou_calculator)