code: def _random_data(self):
      H, W = 100, 100
      N = 10
      img = np.random.rand(H, W, 3) * 255
      boxxy = np.random.rand(N, 2) * (H // 2)
      boxes = np.concatenate((boxxy, boxxy + H // 2), axis=1)
  
      def _rand_poly():
          return np.random.rand(3, 2).flatten() * H
  
      polygons = [
          [_rand_poly() for _ in range(np.random.randint(1, 5))]
          for _ in range(N)
      ]
  
      mask = np.zeros_like(img[:, :, 0], dtype=bool)
      mask[:40, 10:20] = 1
  
      labels = [str(i) for i in range(N)]
      return img, boxes, labels, polygons, [mask] * N
  
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 1 for calling the TestVisualizer obj's underlying member method code with example usage: obj._random_data() and returns: img,  boxes,  labels,  polygons,  unknown, unknown