from __future__ import division, print_function, absolute_import
import re
import glob
import os.path as osp
from ..dataset import ImageDataset
[docs]class DukeMTMCreID(ImageDataset):
"""DukeMTMC-reID.
Reference:
- Ristani et al. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. ECCVW 2016.
- 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 = 'dukemtmc-reid'
dataset_url = 'http://vision.cs.duke.edu/DukeMTMC/data/misc/DukeMTMC-reID.zip'
def __init__(self, root='', **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)
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'
)
required_files = [
self.dataset_dir, self.train_dir, self.query_dir, self.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)
super(DukeMTMCreID, 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())
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())
assert 1 <= camid <= 8
camid -= 1 # index starts from 0
if relabel:
pid = pid2label[pid]
data.append((img_path, pid, camid))
return data