code: def _coco_2017_detection(download=True):
      root = os.environ.get("MXNET_HOME", os.path.join("~", ".mxnet"))
      root = os.path.expanduser(os.path.join(root, "datasets", "coco"))
      if not os.path.isdir(root):
          if not download:
              raise OSError(
                  "No `coco` dataset found on disk and `download=False`"
              )
          # download automatically
          makedirs(root)
          _DOWNLOAD_URLS = [
              (
                  "http://images.cocodataset.org/zips/train2017.zip",
                  "10ad623668ab00c62c096f0ed636d6aff41faca5",
              ),
              (
                  "http://images.cocodataset.org/annotations/annotations_trainval2017.zip",
                  "8551ee4bb5860311e79dace7e79cb91e432e78b3",
              ),
              (
                  "http://images.cocodataset.org/zips/val2017.zip",
                  "4950dc9d00dbe1c933ee0170f5797584351d2a41",
              ),
          ]
          for url, checksum in _DOWNLOAD_URLS:
              filename = _download(
                  url, path=root, overwrite=True, sha1_hash=checksum
              )
              # extract
              with zipfile.ZipFile(filename) as zf:
                  zf.extractall(path=root)
      return COCODetection(
          root=root, splits="instances_train2017"
      ), COCODetection(
          root=root, splits="instances_val2017", skip_empty=False
      )
  
file_path: gluon-cv/gluoncv/auto/data/data_zoo.py
imports: import os
  import shutil
  import tarfile
  import zipfile
  from ...data import VOCDetection, COCODetection
  from ...utils import download, makedirs
label_desc: Use image node_id 5 for calling a global function with example usage: _coco_2017_detection(download) and returns: COCODetection,  COCODetection