code: def draw_mask(image, im_id, segms, threshold, alpha=0.7):
      """
      Draw mask on image
      """
      mask_color_id = 0
      w_ratio = 0.4
      color_list = colormap(rgb=True)
      img_array = np.array(image).astype("float32")
      for dt in np.array(segms):
          if im_id != dt["image_id"]:
              continue
          segm, score = dt["segmentation"], dt["score"]
          if score < threshold:
              continue
          import pycocotools.mask as mask_util
  
          mask = mask_util.decode(segm) * 255
          color_mask = color_list[mask_color_id % len(color_list), 0:3]
          mask_color_id += 1
          for c in range(3):
              color_mask[c] = (
                  color_mask[c] * (1 - w_ratio) + w_ratio * 255
              )
          idx = np.nonzero(mask)
          img_array[idx[0], idx[1], :] *= 1.0 - alpha
          img_array[idx[0], idx[1], :] += alpha * color_mask
      return Image.fromarray(img_array.astype("uint8"))
  
file_path: PaddleDetection/ppdet/utils/visualizer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import os
  import numpy
  from PIL import Image, ImageDraw, ImageFont
  import cv2
  import math
  from .colormap import colormap
  from ppdet.utils.logger import setup_logger
  from ppdet.utils.compact import imagedraw_textsize_c
  from ppdet.utils.download import get_path
label_desc: Use image node_id 2 for calling a global function with example usage: draw_mask(image, im_id, segms, threshold, alpha) and returns: Image