class_docstr: OTB Visual Tracker Benchmark.
  
  Parameters
  ----------
  name : str
      name to data, and name to dataset json Default is 'OTB2015'
  dataset_root: str
      path to dataset root
class_docstr_tok: ["OTB","Visual","Tracker","Benchmark",".","Parameters","--","--","--","--","--","name",":","str","name","to","data",",","and","name","to","dataset","json","Default","is","'OTB2015'","dataset_root",":","str","path","to","dataset","root"]
code: def __init__(self, name, dataset_root, load_img=False):
      super(OTBTracking, self).__init__()
      self.name = name
      self.dataset_root = dataset_root
      with open(
          os.path.join(self.dataset_root, self.name + ".json"), "r"
      ) as f:
          meta_data = json.load(f)
      # load videos
      pbar = tqdm(
          meta_data.keys(), desc="loading " + self.name, ncols=100
      )
      self.videos = {}
      for video in pbar:
          pbar.set_postfix_str(video)
          self.videos[video] = OTBVideo(
              video,
              self.dataset_root,
              meta_data[video]["video_dir"],
              meta_data[video]["init_rect"],
              meta_data[video]["img_names"],
              meta_data[video]["gt_rect"],
              meta_data[video]["attr"],
              load_img,
          )
      # set attr
      attr = []
      for x in self.videos.values():
          attr += x.attr
      attr = set(attr)
      self.attr = {}
      self.attr["ALL"] = list(self.videos.keys())
      for x in attr:
          self.attr[x] = []
      for k, v in self.videos.items():
          for attr_ in v.attr:
              self.attr[attr_].append(k)
  
imports: import json
  import os
  from glob import glob
  from tqdm import tqdm
  from mxnet.gluon.data import dataset
  from gluoncv.utils.filesystem import try_import_cv2
label_desc: Use image node_id 1 to create a new OTBTracking object from inherited base classes: dataset with example: obj = OTBTracking(name, dataset_root, load_img)