class_docstr: Extracts bounding boxes from instances
class_docstr_tok: ["Extracts","bounding","boxes","from","instances"]
code: def __call__(self, instances: Instances, select=None):
      scores = extract_scores_from_instances(instances)
      boxes_xywh = extract_boxes_xywh_from_instances(instances)
      if (scores is None) or (boxes_xywh is None):
          return (boxes_xywh, scores)
      if select is not None:
          scores = scores[select]
          boxes_xywh = boxes_xywh[select]
      return (boxes_xywh, scores)
  
imports: import logging
  from typing import List, Optional, Sequence, Tuple
  import torch
  from detectron2.layers.nms import batched_nms
  from detectron2.structures.instances import Instances
  from densepose.converters import ToChartResultConverterWithConfidences
  from densepose.structures import DensePoseChartResultWithConfidences, DensePoseEmbeddingPredictorOutput
  from densepose.vis.bounding_box import BoundingBoxVisualizer, ScoredBoundingBoxVisualizer
  from densepose.vis.densepose_outputs_vertex import DensePoseOutputsVertexVisualizer
  from densepose.vis.densepose_results import DensePoseResultsVisualizer
  from .base import CompoundVisualizer
label_desc: Use image node_id 1 for calling the ScoredBoundingBoxExtractor obj's underlying member method code with example usage: obj.__call__(instances, select) and returns: boxes_xywh,  scores, boxes_xywh,  scores