text: from .bases import BaseImageDataset
  import os.path as osp
  import glob
  import re
  import os
  
  class DukeMTMC(BaseImageDataset):
      """
      DukeMTMC-reID
      Reference:
      1. Ristani et al. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. ECCVW 2016.
      2. Zheng et al. Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro. ICCV 2017.
      URL: https://github.com/layumi/DukeMTMC-reID_evaluation
  
      Dataset statistics:
      # identities: 1404 (train + query)
      # images:16522 (train) + 2228 (query) + 17661 (gallery)
      # cameras: 8
      """
      dataset_dir = '.'
  
      def __init__(self, data_dir, verbose=True, **kwargs):
          super(DukeMTMC, self).__init__()
          self.dataset_dir = data_dir # osp.join(root, self.dataset_dir)
          self.dataset_url = 'http://vision.cs.duke.edu/DukeMTMC/data/misc/DukeMTMC-reID.zip'
          self.train_dir = osp.join(self.dataset_dir, 'DukeMTMC-reID/bounding_box_train')
          self.query_dir = osp.join(self.dataset_dir, 'DukeMTMC-reID/query')
          self.gallery_dir = osp.join(self.dataset_dir, 'DukeMTMC-reID/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("=> DukeMTMC-reID 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())
              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())
              assert 1 <= camid <= 8
              camid -= 1  # index starts from 0
              if relabel: pid = pid2label[pid]
              dataset.append((img_path, pid, camid))
          return dataset
  