code: def visualize_box_mask(im, results, labels, threshold=0.5):
      """
      Args:
          im (str/np.ndarray): path of image/np.ndarray read by cv2
          results (dict): include 'boxes': np.ndarray: shape:[N,6], N: number of box,
                          matix element:[class, score, x_min, y_min, x_max, y_max]
                          MaskRCNN's results include 'masks': np.ndarray:
                          shape:[N, im_h, im_w]
          labels (list): labels:['class1', ..., 'classn']
          threshold (float): Threshold of score.
      Returns:
          im (PIL.Image.Image): visualized image
      """
      if isinstance(im, str):
          im = Image.open(im).convert("RGB")
      elif isinstance(im, np.ndarray):
          im = Image.fromarray(im)
      if (
          "masks" in results
          and "boxes" in results
          and len(results["boxes"]) > 0
      ):
          im = draw_mask(
              im,
              results["boxes"],
              results["masks"],
              labels,
              threshold=threshold,
          )
      if "boxes" in results and len(results["boxes"]) > 0:
          im = draw_box(
              im, results["boxes"], labels, threshold=threshold
          )
      if "segm" in results:
          im = draw_segm(
              im,
              results["segm"],
              results["label"],
              results["score"],
              labels,
              threshold=threshold,
          )
      return im
  
imports: from __future__ import division
  import os
  import cv2
  import math
  import numpy
  import PIL
  from PIL import Image, ImageDraw, ImageFile
label_desc: Use image node_id 2 for calling a global function with example usage: visualize_box_mask(im, results, labels, threshold) and returns: im