code: def draw_bounding_boxes(images, annotations, confidence_threshold=0):
      
      _numeric_param_check_range('confidence_threshold', confidence_threshold, 0.0, 1.0)
      from PIL import Image
      def draw_single_image(row):
          image = row['image']
          anns = row['annotations']
          if anns == None:
              anns = []
          elif type(anns) == dict:
              anns = [anns]
          pil_img = Image.fromarray(image.pixel_data)
          _annotate_image(pil_img, anns, confidence_threshold=confidence_threshold)
          image = _np.array(pil_img)
          FORMAT_RAW = 2
          annotated_image = _tc.Image(_image_data=image.tobytes(),
                                      _width=image.shape[1],
                                      _height=image.shape[0],
                                      _channels=image.shape[2],
                                      _format_enum=FORMAT_RAW,
                                      _image_data_size=image.size)
          return annotated_image
  
      if isinstance(images, _tc.Image) and isinstance(annotations, list):
          return draw_single_image({'image': images, 'annotations': annotations})
      else:
          return (_tc.SFrame({'image': images, 'annotations': annotations})
                  .apply(draw_single_image))
docs: Visualizes bounding boxes (ground truth or predictions) by
      returning annotated copies of the images.
  
      Parameters
      ----------
      images: SArray or Image
          An `SArray` of type `Image`. A single `Image` instance may also be
          given.
  
      annotations: SArray or list
          An `SArray` of annotations (either output from the
          `ObjectDetector.predict` function or ground truth). A single list of
          annotations may also be given, provided that it is coupled with a
          single image.
  
      confidence_threshold: float
          Confidence threshold can limit the number of boxes to draw. By
          default, this is set to 0, since the prediction may have already pruned
          with an appropriate confidence threshold.
  
      Returns
      -------
      annotated_images: SArray or Image
          Similar to the input `images`, except the images are decorated with
          boxes to visualize the object instances.
  
      See also
      --------
      unstack_annotations