docstr: create anchor target
  
  Parameters
  ----------
  anchor_stride : int
      anchor stride
  anchor_ratios : tuple
      anchor ratios
  train_search_size : int
      train search size
  train_output_size : int
      train output size
  train_thr_high : float
      Positive anchor threshold
  train_thr_low : float
      Negative anchor threshold
  train_pos_num : int
      Number of Positive
  train_neg_num : int
      Number of Negative
  train_total_num : int
      total number
docstr_tok: ["create","anchor","target","Parameters","--","--","--","--","--","anchor_stride",":","int","anchor","stride","anchor_ratios",":","tuple","anchor","ratios","train_search_size",":","int","train","search","size","train_output_size",":","int","train","output","size","train_thr_high",":","float","Positive","anchor","threshold","train_thr_low",":","float","Negative","anchor","threshold","train_pos_num",":","int","Number","of","Positive","train_neg_num",":","int","Number","of","Negative","train_total_num",":","int","total","number"]
code: def __init__(
      self,
      anchor_stride,
      anchor_ratios,
      train_search_size,
      train_output_size,
      train_thr_high=0.6,
      train_thr_low=0.3,
      train_pos_num=16,
      train_neg_num=16,
      train_total_num=64,
  ):
      """create anchor target
  
      Parameters
      ----------
      anchor_stride : int
          anchor stride
      anchor_ratios : tuple
          anchor ratios
      train_search_size : int
          train search size
      train_output_size : int
          train output size
      train_thr_high : float
          Positive anchor threshold
      train_thr_low : float
          Negative anchor threshold
      train_pos_num : int
          Number of Positive
      train_neg_num : int
          Number of Negative
      train_total_num : int
          total number
      """
      self.anchor_stride = anchor_stride
      self.anchor_ratios = anchor_ratios
      self.anchor_scales = [8]
      self.anchors = Anchors(
          self.anchor_stride, self.anchor_ratios, self.anchor_scales
      )
      self.train_search_size = train_search_size
      self.train_output_size = train_output_size
  
      self.anchors.generate_all_anchors(
          im_c=self.train_search_size // 2, size=self.train_output_size
      )
      self.train_thr_high = train_thr_high
      self.train_thr_low = train_thr_low
      self.train_pos_num = train_pos_num
      self.train_neg_num = train_neg_num
      self.train_total_num = train_total_num
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import json
  import logging
  import os
  import numpy
  from mxnet.gluon.data import dataset
  from gluoncv.utils.filesystem import try_import_cv2
  from gluoncv.model_zoo.siamrpn.siamrpn_tracker import corner2center, center2corner
  from gluoncv.model_zoo.siamrpn.siamrpn_tracker import Center, Anchors
  from gluoncv.data.transforms.track import SiamRPNaugmentation
  from gluoncv.utils.bbox import bbox_iou
label_desc: Use image node_id 1 to create a new AnchorTarget object  with example: obj = AnchorTarget(anchor_stride, anchor_ratios, train_search_size, train_output_size, train_thr_high, train_thr_low, train_pos_num, train_neg_num, train_total_num)