code: def test_BWmode_nomask(self):
      img, boxes, _, _, masks = self._random_data()
      num_inst = len(boxes)
      inst = Instances((img.shape[0], img.shape[1]))
      inst.pred_classes = torch.randint(0, 80, size=(num_inst,))
      inst.scores = torch.rand(num_inst)
      inst.pred_boxes = torch.from_numpy(boxes)
  
      v = Visualizer(
          img, self.metadata, instance_mode=ColorMode.IMAGE_BW
      )
      v.draw_instance_predictions(inst)
  
      # check that output is grayscale
      inst = inst[:0]
      v = Visualizer(
          img, self.metadata, instance_mode=ColorMode.IMAGE_BW
      )
      output = v.draw_instance_predictions(inst).get_image()
      self.assertTrue(np.allclose(output[:, :, 0], output[:, :, 1]))
      self.assertTrue(np.allclose(output[:, :, 0], output[:, :, 2]))
  
imports: import numpy
  import os
  import tempfile
  import unittest
  import cv2
  import torch
  from detectron2.data import MetadataCatalog
  from detectron2.structures import BoxMode, Instances, RotatedBoxes
  from detectron2.utils.visualizer import ColorMode, Visualizer
label_desc: Use image node_id 8 for calling the TestVisualizer obj's underlying member method code with example usage: obj.test_BWmode_nomask() without return types