Source code for torchreid.data.datasets.image.market1501

from __future__ import division, print_function, absolute_import
import re
import glob
import os.path as osp
import warnings

from ..dataset import ImageDataset


[docs]class Market1501(ImageDataset): """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). """ _junk_pids = [0, -1] dataset_dir = 'market1501' dataset_url = 'http://188.138.127.15:81/Datasets/Market-1501-v15.09.15.zip' def __init__(self, root='', market1501_500k=False, **kwargs): self.root = osp.abspath(osp.expanduser(root)) self.dataset_dir = osp.join(self.root, self.dataset_dir) self.download_dataset(self.dataset_dir, self.dataset_url) # allow alternative directory structure self.data_dir = self.dataset_dir data_dir = osp.join(self.data_dir, 'Market-1501-v15.09.15') if osp.isdir(data_dir): self.data_dir = data_dir else: warnings.warn( 'The current data structure is deprecated. Please ' 'put data folders such as "bounding_box_train" under ' '"Market-1501-v15.09.15".' ) self.train_dir = osp.join(self.data_dir, 'bounding_box_train') self.query_dir = osp.join(self.data_dir, 'query') self.gallery_dir = osp.join(self.data_dir, 'bounding_box_test') self.extra_gallery_dir = osp.join(self.data_dir, 'images') self.market1501_500k = market1501_500k required_files = [ self.data_dir, self.train_dir, self.query_dir, self.gallery_dir ] if self.market1501_500k: required_files.append(self.extra_gallery_dir) self.check_before_run(required_files) 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 self.market1501_500k: gallery += self.process_dir(self.extra_gallery_dir, relabel=False) super(Market1501, self).__init__(train, query, gallery, **kwargs) 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)} data = [] 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] data.append((img_path, pid, camid)) return data