text: from pytracking.utils import TrackerParams
  from pytracking.features.net_wrappers import NetWithBackbone
  
  def parameters():
      params = TrackerParams()
  
      params.debug = 0
      params.visualization = False
  
      params.use_gpu = True
  
      params.train_feature_size = 18
      params.feature_stride = 16
      params.image_sample_size = params.train_feature_size*params.feature_stride
      params.search_area_scale = 5
      params.border_mode = 'inside_major'
      params.patch_max_scale_change = 1.5
  
      # Learning parameters
      params.sample_memory_size = 2
      params.learning_rate = 0.01
      params.init_samples_minimum_weight = 0.25
      params.train_skipping = 20
  
      # Net optimization params
      params.update_classifier = True
      params.net_opt_iter = 10
      params.net_opt_update_iter = 2
      params.net_opt_hn_iter = 1
  
      # Detection parameters
      params.window_output = False
  
      # Init augmentation parameters
      params.use_augmentation = False
      params.augmentation = {}
  
      params.augmentation_expansion_factor = 2
      params.random_shift_factor = 1/3
  
      # Advanced localization parameters
      params.advanced_localization = True
      params.target_not_found_threshold = 0.25
      params.distractor_threshold = 0.8
      params.hard_negative_threshold = 0.5
      params.target_neighborhood_scale = 2.2
      params.dispalcement_scale = 0.8
      params.hard_negative_learning_rate = 0.02
      params.update_scale_when_uncertain = True
      params.conf_ths = 0.9
      params.search_area_rescaling_at_occlusion = True
  
      params.net = NetWithBackbone(net_path='tomp50.pth.tar', use_gpu=params.use_gpu)
  
      params.vot_anno_conversion_type = 'preserve_area'
  
      params.use_gt_box = True
      params.plot_iou = True
  
      return params
  