class_docstr: Load the subdataset for tracking.
  get annotation data,and get positive pair every frame range.
  
  Parameters
  ----------
  name : str
      dataset name.
  root : str
      Path to the folder stored the dataset.
  anno : str
      Path to the Json stored detaset annotation
  frame_range : int
      dataset frame range that get positive pair.
  num_use : int
      if num_use = -1 show all dataset,show fisrt num_use dataset
  start_idx : int
      dataset start idx
class_docstr_tok: ["Load","the","subdataset","for","tracking",".","get","annotation","data",",","and","get","positive","pair","every","frame","range",".","Parameters","--","--","--","--","--","name",":","str","dataset","name",".","root",":","str","Path","to","the","folder","stored","the","dataset",".","anno",":","str","Path","to","the","Json","stored","detaset","annotation","frame_range",":","int","dataset","frame","range","that","get","positive","pair",".","num_use",":","int","if","num_use","=","-1","show","all","dataset",",","show","fisrt","num_use","dataset","start_idx",":","int","dataset","start","idx"]
docstr: Collate annotation and filter data
  
  Parameters
  ----------
      path
          meta_data
  
  Returns
      data after collate annotation and filter
docstr_tok: ["Collate","annotation","and","filter","data","Parameters","--","--","--","--","--","path","meta_data","Returns","data","after","collate","annotation","and","filter"]
code: def _filter_zero(self, meta_data):
      """
      Collate annotation and filter data
  
      Parameters
      ----------
          path
              meta_data
  
      Returns
          data after collate annotation and filter
      """
      meta_data_new = {}
      for video, tracks in meta_data.items():
          new_tracks = {}
          for trk, frames in tracks.items():
              new_frames = {}
              for frm, bbox in frames.items():
                  if not isinstance(bbox, dict):
                      if len(bbox) == 4:
                          x1, y1, x2, y2 = bbox
                          w, h = x2 - x1, y2 - y1
                      else:
                          w, h = bbox
                      if w <= 0 or h <= 0:
                          continue
                  new_frames[frm] = bbox
              if len(new_frames) > 0:
                  new_tracks[trk] = new_frames
          if len(new_tracks) > 0:
              meta_data_new[video] = new_tracks
      return meta_data_new
  
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 2 for calling the SubDataset obj's underlying member method code with example usage: obj._filter_zero(meta_data) and returns: meta_data_new