code: def save_fddb_bboxes(
      bboxes_scores, output_dir, output_fname="pred_fddb_res.txt"
  ):
      if not os.path.exists(output_dir):
          os.makedirs(output_dir)
      predict_file = os.path.join(output_dir, output_fname)
      f = open(predict_file, "w")
      for image_path, dets in bboxes_scores.iteritems():
          f.write("{:s}\n".format(image_path))
          f.write("{:d}\n".format(dets.shape[0]))
          for box_score in dets:
              xmin, ymin, xmax, ymax, score = box_score
              width, height = xmax - xmin, ymax - ymin
              f.write(
                  "{:.1f} {:.1f} {:.1f} {:.1f} {:.3f}\n".format(
                      xmin, ymin, width, height, score
                  )
              )
      logger.info(
          "The predicted result is saved as {}".format(predict_file)
      )
      return predict_file
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import cv2
  import numpy
  from collections import OrderedDict
  import paddle
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 11 for calling a global function with example usage: save_fddb_bboxes(bboxes_scores, output_dir, output_fname) and returns: predict_file