code: def get_config(init_mode="canonical_checkpoint"):
      """Returns the configuration for text-query-based detection using OWL-ViT."""
      config = ml_collections.ConfigDict()
      config.experiment_name = "owl_vit_detection"
  
      # Dataset.
      config.dataset_name = "owl_vit"
      config.dataset_configs = ml_collections.ConfigDict()
      config.dataset_configs.input_size = 960
      config.dataset_configs.input_range = None
      config.dataset_configs.max_query_length = 16
  
      # Model.
      config.model_name = "text_zero_shot_detection"
  
      config.model = ml_collections.ConfigDict()
      config.model.normalize = True
  
      config.model.body = ml_collections.ConfigDict()
      config.model.body.type = "clip"
      config.model.body.variant = "vit_b16"
      config.model.body.merge_class_token = "mul-ln"
      config.model.box_bias = "both"
  
      # Objectness head.
      config.model.objectness_head = ml_collections.ConfigDict()
      config.model.objectness_head.stop_gradient = True
  
      # Init.
      config.init_from = ml_collections.ConfigDict()
      checkpoint_path = CHECKPOINTS.get(init_mode, None)
      if checkpoint_path is None:
          raise ValueError("Unknown init_mode: {}".format(init_mode))
      config.init_from.checkpoint_path = checkpoint_path
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(init_mode) and returns: config