class_docstr: Training targets generator for Single-shot Object Detection.
  
  Parameters
  ----------
  iou_thresh : float
      IOU overlap threshold for maximum matching, default is 0.5.
  neg_thresh : float
      IOU overlap threshold for negative mining, default is 0.5.
  negative_mining_ratio : float
      Ratio of hard vs positive for negative mining.
  stds : array-like of size 4, default is (0.1, 0.1, 0.2, 0.2)
      Std value to be divided from encoded values.
class_docstr_tok: ["Training","targets","generator","for","Single-shot","Object","Detection",".","Parameters","--","--","--","--","--","iou_thresh",":","float","IOU","overlap","threshold","for","maximum","matching",",","default","is","0.5.","neg_thresh",":","float","IOU","overlap","threshold","for","negative","mining",",","default","is","0.5.","negative_mining_ratio",":","float","Ratio","of","hard","vs","positive","for","negative","mining",".","stds",":","array-like","of","size","4",",","default","is","(","0.1",",","0.1",",","0.2",",","0.2",")","Std","value","to","be","divided","from","encoded","values","."]
code: def __init__(
      self,
      iou_thresh=0.5,
      neg_thresh=0.5,
      negative_mining_ratio=3,
      stds=(0.1, 0.1, 0.2, 0.2),
      **kwargs,
  ):
      super(SSDTargetGenerator, self).__init__(**kwargs)
      self._matcher = CompositeMatcher(
          [
              BipartiteMatcher(share_max=False),
              MaximumMatcher(iou_thresh),
          ]
      )
      if negative_mining_ratio > 0:
          self._sampler = OHEMSampler(
              negative_mining_ratio, thresh=neg_thresh
          )
          self._use_negative_sampling = True
      else:
          self._sampler = NaiveSampler()
          self._use_negative_sampling = False
      self._cls_encoder = MultiClassEncoder()
      self._box_encoder = NormalizedBoxCenterEncoder(stds=stds)
      self._center_to_corner = BBoxCenterToCorner(split=False)
  
file_path: gluon-cv/gluoncv/model_zoo/ssd/target.py
imports: from __future__ import absolute_import
  from mxnet import nd
  from mxnet.gluon import Block
  from ...nn.matcher import CompositeMatcher, BipartiteMatcher, MaximumMatcher
  from ...nn.sampler import OHEMSampler, NaiveSampler
  from ...nn.coder import MultiClassEncoder, NormalizedBoxCenterEncoder
  from ...nn.bbox import BBoxCenterToCorner
label_desc: Use image node_id 1 to create a new SSDTargetGenerator object from inherited base classes: Block with example: obj = SSDTargetGenerator(iou_thresh, neg_thresh, negative_mining_ratio, stds)