code: def main(args):
      logger = logging.getLogger(__name__)
      merge_cfg_from_file(args.cfg)
      cfg.NUM_GPUS = 1
      args.weights = cache_url(args.weights, cfg.DOWNLOAD_CACHE)
      assert_and_infer_cfg(cache_urls=False)
      model = infer_engine.initialize_model_from_cfg(args.weights)
      dummy_coco_dataset = dummy_datasets.get_coco_dataset()
  
      if os.path.isdir(args.im_or_folder):
          im_list = glob.iglob(
              args.im_or_folder + "/*." + args.image_ext
          )
      else:
          im_list = [args.im_or_folder]
  
      for i, im_name in enumerate(im_list):
          out_name = os.path.join(
              args.output_dir,
              "{}".format(os.path.basename(im_name) + ".pdf"),
          )
          logger.info("Processing {} -> {}".format(im_name, out_name))
          im = cv2.imread(im_name)
          timers = defaultdict(Timer)
          t = time.time()
          with c2_utils.NamedCudaScope(0):
              (
                  cls_boxes,
                  cls_segms,
                  cls_keyps,
                  cls_bodys,
              ) = infer_engine.im_detect_all(
                  model, im, None, timers=timers
              )
          logger.info("Inference time: {:.3f}s".format(time.time() - t))
          for k, v in timers.items():
              logger.info(" | {}: {:.3f}s".format(k, v.average_time))
          if i == 0:
              logger.info(
                  " \ Note: inference on the first image will be slower than the "
                  "rest (caches and auto-tuning need to warm up)"
              )
  
          vis_utils.vis_one_image(
              im[:, :, ::-1],  # BGR -> RGB for visualization
              im_name,
              args.output_dir,
              cls_boxes,
              cls_segms,
              cls_keyps,
              cls_bodys,
              dataset=dummy_coco_dataset,
              box_alpha=0.3,
              show_class=True,
              thresh=0.7,
              kp_thresh=2,
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from collections import defaultdict
  import argparse
  import cv2
  import glob
  import logging
  import os
  import sys
  import time
  from caffe2.python import workspace
  from detectron.core.config import assert_and_infer_cfg
  from detectron.core.config import cfg
  from detectron.core.config import merge_cfg_from_file
  from detectron.utils.io import cache_url
  from detectron.utils.logging import setup_logging
  from detectron.utils.timer import Timer
  import detectron.core.test_engine
  import detectron.datasets.dummy_datasets
  import detectron.utils.c2
  import detectron.utils.vis
label_desc: Use image node_id 2 for calling a global function with example usage: main(args) without return types