fast-reid/fastreid/data/datasets/market1501.py

91 lines
3.1 KiB
Python

# encoding: utf-8
"""
@author: sherlock
@contact: sherlockliao01@gmail.com
"""
import glob
import os.path as osp
import re
import warnings
from .bases import ImageDataset
from ..datasets import DATASET_REGISTRY
@DATASET_REGISTRY.register()
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 = ''
dataset_url = 'http://188.138.127.15:81/Datasets/Market-1501-v15.09.15.zip'
dataset_name = "market1501"
def __init__(self, root='datasets', market1501_500k=False, **kwargs):
# self.root = osp.abspath(osp.expanduser(root))
self.root = root
self.dataset_dir = osp.join(self.root, self.dataset_dir)
# 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)
query = self.process_dir(self.query_dir, is_train=False)
gallery = self.process_dir(self.gallery_dir, is_train=False)
if self.market1501_500k:
gallery += self.process_dir(self.extra_gallery_dir, is_train=False)
super(Market1501, self).__init__(train, query, gallery, **kwargs)
def process_dir(self, dir_path, is_train=True):
img_paths = glob.glob(osp.join(dir_path, '*.jpg'))
pattern = re.compile(r'([-\d]+)_c(\d)')
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 is_train:
pid = self.dataset_name + "_" + str(pid)
camid = self.dataset_name + "_" + str(camid)
data.append((img_path, pid, camid))
return data