class_docstr: Default Faster-RCNN training transform.
  
  Parameters
  ----------
  short : int/tuple, default is 600
      Resize image shorter side to ``short``.
      Resize the shorter side of the image randomly within the given range, if it is a tuple.
  max_size : int, default is 1000
      Make sure image longer side is smaller than ``max_size``.
  net : mxnet.gluon.HybridBlock, optional
      The faster-rcnn network.
  
      .. hint::
  
          If net is ``None``, the transformation will not generate training targets.
          Otherwise it will generate training targets to accelerate the training phase
          since we push some workload to CPU workers instead of GPUs.
  
  mean : array-like of size 3
      Mean pixel values to be subtracted from image tensor. Default is [0.485, 0.456, 0.406].
  std : array-like of size 3
      Standard deviation to be divided from image. Default is [0.229, 0.224, 0.225].
  box_norm : array-like of size 4, default is (1., 1., 1., 1.)
      Std value to be divided from encoded values.
  num_sample : int, default is 256
      Number of samples for RPN targets.
  pos_iou_thresh : float, default is 0.7
      Anchors larger than ``pos_iou_thresh`` is regarded as positive samples.
  neg_iou_thresh : float, default is 0.3
      Anchors smaller than ``neg_iou_thresh`` is regarded as negative samples.
      Anchors with IOU in between ``pos_iou_thresh`` and ``neg_iou_thresh`` are
      ignored.
  pos_ratio : float, default is 0.5
      ``pos_ratio`` defines how many positive samples (``pos_ratio * num_sample``) is
      to be sampled.
  flip_p : float, default is 0.5
      Probability to flip horizontally, by default is 0.5 for random horizontal flip.
      You may set it to 0 to disable random flip or 1 to force flip.
  ashape : int, default is 128
      Defines shape of pre generated anchors for target generation
  multi_stage : boolean, default is False
      Whether the network output multi stage features.
class_docstr_tok: ["Default","Faster-RCNN","training","transform",".","Parameters","--","--","--","--","--","short",":","int\/tuple",",","default","is","600","Resize","image","shorter","side","to","``","short","``",".","Resize","the","shorter","side","of","the","image","randomly","within","the","given","range",",","if","it","is","a","tuple",".","max_size",":","int",",","default","is","1000","Make","sure","image","longer","side","is","smaller","than","``","max_size","``",".","net",":","mxnet.gluon.HybridBlock",",","optional","The","faster-rcnn","network",".","..","hint",":",":","If","net","is","``","None","``",",","the","transformation","will","not","generate","training","targets",".","Otherwise","it","will","generate","training","targets","to","accelerate","the","training","phase","since","we","push","some","workload","to","CPU","workers","instead","of","GPUs",".","mean",":","array-like","of","size","3","Mean","pixel","values","to","be","subtracted","from","image","tensor",".","Default","is","[","0.485",",","0.456",",","0.406","]",".","std",":","array-like","of","size","3","Standard","deviation","to","be","divided","from","image",".","Default","is","[","0.229",",","0.224",",","0.225","]",".","box_norm",":","array-like","of","size","4",",","default","is","(","1.",",","1.",",","1.",",","1",".",")","Std","value","to","be","divided","from","encoded","values",".","num_sample",":","int",",","default","is","256","Number","of","samples","for","RPN","targets",".","pos_iou_thresh",":","float",",","default","is","0.7","Anchors","larger","than","``","pos_iou_thresh","``","is","regarded","as","positive","samples",".","neg_iou_thresh",":","float",",","default","is","0.3","Anchors","smaller","than","``","neg_iou_thresh","``","is","regarded","as","negative","samples",".","Anchors","with","IOU","in","between","``","pos_iou_thresh","``","and","``","neg_iou_thresh","``","are","ignored",".","pos_ratio",":","float",",","default","is","0.5","``","pos_ratio","``","defines","how","many","positive","samples","(","``","pos_ratio","*","num_sample","``",")","is","to","be","sampled",".","flip_p",":","float",",","default","is","0.5","Probability","to","flip","horizontally",",","by","default","is","0.5","for","random","horizontal","flip",".","You","may","set","it","to","0","to","disable","random","flip","or","1","to","force","flip",".","ashape",":","int",",","default","is","128","Defines","shape","of","pre","generated","anchors","for","target","generation","multi_stage",":","boolean",",","default","is","False","Whether","the","network","output","multi","stage","features","."]
code: def _target_generator(self):
      if self._internal_target_generator is None:
          if self._net_none:
              return None
          from ....model_zoo.rcnn.rpn.rpn_target import (
              RPNTargetGenerator,
          )
  
          self._internal_target_generator = RPNTargetGenerator(
              num_sample=self._num_sample,
              pos_iou_thresh=self._pos_iou_thresh,
              neg_iou_thresh=self._neg_iou_thresh,
              pos_ratio=self._pos_ratio,
              stds=self._box_norm,
              **self._kwargs,
          )
          return self._internal_target_generator
      else:
          return self._internal_target_generator
  
imports: from __future__ import absolute_import
  import copy
  from random import randint
  import mxnet
  from ..None import bbox
  from ..None import image
  from ..None import mask
label_desc: Use image node_id 2 for calling the FasterRCNNDefaultTrainTransform obj's underlying member method code with example usage: obj._target_generator() and returns: self, self, None