code: def remove_pipeline_elements(
      results: Dict, remove_inds: Union[List[int], np.ndarray]
  ) -> Dict:
      """Remove elements in the pipeline given target indexes.
  
      Args:
          results (dict): Result dict from loading pipeline.
          remove_inds (list(int) or np.ndarray): The element indexes to be
              removed.
  
      Required Keys:
  
      - gt_polygons (optional)
      - gt_bboxes (optional)
      - gt_bboxes_labels (optional)
      - gt_ignored (optional)
      - gt_texts (optional)
  
      Modified Keys:
  
      - gt_polygons (optional)
      - gt_bboxes (optional)
      - gt_bboxes_labels (optional)
      - gt_ignored (optional)
      - gt_texts (optional)
  
      Returns:
          dict: The results with element removed.
      """
      keys = [
          "gt_polygons",
          "gt_bboxes",
          "gt_bboxes_labels",
          "gt_ignored",
          "gt_texts",
      ]
      num_elements = -1
      for key in keys:
          if key in results:
              num_elements = len(results[key])
              break
      if num_elements == -1:
          return results
      kept_inds = np.array(
          [i for i in range(num_elements) if i not in remove_inds]
      )
      for key in keys:
          if key in results:
              if isinstance(results[key], np.ndarray):
                  results[key] = results[key][kept_inds]
              elif isinstance(results[key], list):
                  results[key] = [results[key][i] for i in kept_inds]
              else:
                  raise TypeError(
                      f"Unsupported type {type(results[key])} for key {key}"
                  )
      return results
  
label_desc: Use image node_id 1 for calling a global function with example usage: remove_pipeline_elements(results, remove_inds) and returns: results, results