text: from __future__ import print_function, absolute_import
  import os.path as osp
  import glob
  import re
  import urllib
  import zipfile
  
  from ..utils.data import BaseImageDataset
  from ..utils.osutils import mkdir_if_missing
  from ..utils.serialization import write_json
  
  class Market1501(BaseImageDataset):
      """
      Market1501
      Reference:
      Zheng et al. Scalable Person Re-identification: A Benchmark. ICCV 2015.
      URL: http://www.liangzheng.org/Project/project_reid.html
  
      Dataset statistics:
      # identities: 1501 (+1 for background)
      # images: 12936 (train) + 3368 (query) + 15913 (gallery)
      """
      dataset_dir = 'Market-1501'
  
      def __init__(self, root, verbose=True, **kwargs):
          super(Market1501, self).__init__()
          self.dataset_dir = osp.join(root, self.dataset_dir)
          self.train_dir = osp.join(self.dataset_dir, 'bounding_box_train')
          self.query_dir = osp.join(self.dataset_dir, 'query')
          self.gallery_dir = osp.join(self.dataset_dir, 'bounding_box_test')
  
          self._check_before_run()
  
          train = self._process_dir(self.train_dir, relabel=True)
          query = self._process_dir(self.query_dir, relabel=False)
          gallery = self._process_dir(self.gallery_dir, relabel=False)
  
          if verbose:
              print("=> Market1501 loaded")
              self.print_dataset_statistics(train, query, gallery)
  
          self.train = train
          self.query = query
          self.gallery = gallery
  
          self.num_train_pids, self.num_train_imgs, self.num_train_cams = self.get_imagedata_info(self.train)
          self.num_query_pids, self.num_query_imgs, self.num_query_cams = self.get_imagedata_info(self.query)
          self.num_gallery_pids, self.num_gallery_imgs, self.num_gallery_cams = self.get_imagedata_info(self.gallery)
  
      def _check_before_run(self):
          """Check if all files are available before going deeper"""
          if not osp.exists(self.dataset_dir):
              raise RuntimeError("'{}' is not available".format(self.dataset_dir))
          if not osp.exists(self.train_dir):
              raise RuntimeError("'{}' is not available".format(self.train_dir))
          if not osp.exists(self.query_dir):
              raise RuntimeError("'{}' is not available".format(self.query_dir))
          if not osp.exists(self.gallery_dir):
              raise RuntimeError("'{}' is not available".format(self.gallery_dir))
  
      def _process_dir(self, dir_path, relabel=False):
          img_paths = glob.glob(osp.join(dir_path, '*.jpg'))
          pattern = re.compile(r'([-\d]+)_c(\d)')
  
          pid_container = set()
          for img_path in img_paths:
              pid, _ = map(int, pattern.search(img_path).groups())
              if pid == -1: continue  # junk images are just ignored
              pid_container.add(pid)
          pid2label = {pid: label for label, pid in enumerate(pid_container)}
  
          dataset = []
          for img_path in img_paths:
              pid, camid = map(int, pattern.search(img_path).groups())
              if pid == -1: continue  # junk images are just ignored
              assert 0 <= pid <= 1501  # pid == 0 means background
              assert 1 <= camid <= 6
              camid -= 1  # index starts from 0
              if relabel: pid = pid2label[pid]
              dataset.append((img_path, pid, camid))
  
          return dataset
  