code: def predict(
      self,
      x,
      metric,
      asc,
      model_id=None,
      saved=False,
      custom_objects=None,
  ):
      """Makes a probability prediction from input x. If model_id
      is not given, then best_model will be used.
  
      x | array | data to be used for the predictions
      model_id | int | the id of the model from the Scan() object
      metric | str | the metric to be used for picking best model
      asc | bool | True if `metric` is something to be minimized
      saved | bool | if a model saved on local machine should be used
      custom_objects | dict | if the model has a custom object,
                              pass it here
  
      """
  
      if model_id is None:
          from ..utils.best_model import best_model
  
          model_id = best_model(self.scan_object, metric, asc)
  
      from ..utils.best_model import activate_model
  
      model = activate_model(
          self.scan_object, model_id, saved, custom_objects
      )
  
      return model.predict(x)
  
label_desc: Use image node_id 2 for calling the Predict obj's underlying member method code with example usage: obj.predict(x, metric, asc, model_id, saved, custom_objects) and returns: model