83 lines
3.3 KiB
Python
83 lines
3.3 KiB
Python
#!/usr/bin/env python
|
|
# -*- coding: utf-8 -*-
|
|
# @Time : 2019/1/17 15:00
|
|
# @Author : Hao Luo
|
|
# @File : msmt17.py
|
|
|
|
import glob
|
|
import re
|
|
|
|
import os.path as osp
|
|
|
|
from .bases import BaseImageDataset
|
|
|
|
|
|
class MSMT17(BaseImageDataset):
|
|
"""
|
|
MSMT17
|
|
|
|
Reference:
|
|
Wei et al. Person Transfer GAN to Bridge Domain Gap for Person Re-Identification. CVPR 2018.
|
|
|
|
URL: http://www.pkuvmc.com/publications/msmt17.html
|
|
|
|
Dataset statistics:
|
|
# identities: 4101
|
|
# images: 32621 (train) + 11659 (query) + 82161 (gallery)
|
|
# cameras: 15
|
|
"""
|
|
dataset_dir = 'msmt17'
|
|
|
|
def __init__(self,root='/home/haoluo/data', verbose=True, **kwargs):
|
|
super(MSMT17, self).__init__()
|
|
self.dataset_dir = osp.join(root, self.dataset_dir)
|
|
self.train_dir = osp.join(self.dataset_dir, 'MSMT17_V2/mask_train_v2')
|
|
self.test_dir = osp.join(self.dataset_dir, 'MSMT17_V2/mask_test_v2')
|
|
self.list_train_path = osp.join(self.dataset_dir, 'MSMT17_V2/list_train.txt')
|
|
self.list_val_path = osp.join(self.dataset_dir, 'MSMT17_V2/list_val.txt')
|
|
self.list_query_path = osp.join(self.dataset_dir, 'MSMT17_V2/list_query.txt')
|
|
self.list_gallery_path = osp.join(self.dataset_dir, 'MSMT17_V2/list_gallery.txt')
|
|
|
|
self._check_before_run()
|
|
train = self._process_dir(self.train_dir, self.list_train_path)
|
|
#val, num_val_pids, num_val_imgs = self._process_dir(self.train_dir, self.list_val_path)
|
|
query = self._process_dir(self.test_dir, self.list_query_path)
|
|
gallery = self._process_dir(self.test_dir, self.list_gallery_path)
|
|
if verbose:
|
|
print("=> MSMT17 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.test_dir):
|
|
raise RuntimeError("'{}' is not available".format(self.test_dir))
|
|
|
|
def _process_dir(self, dir_path, list_path):
|
|
with open(list_path, 'r') as txt:
|
|
lines = txt.readlines()
|
|
dataset = []
|
|
pid_container = set()
|
|
for img_idx, img_info in enumerate(lines):
|
|
img_path, pid = img_info.split(' ')
|
|
pid = int(pid) # no need to relabel
|
|
camid = int(img_path.split('_')[2])
|
|
img_path = osp.join(dir_path, img_path)
|
|
dataset.append((img_path, pid, camid))
|
|
pid_container.add(pid)
|
|
|
|
# check if pid starts from 0 and increments with 1
|
|
for idx, pid in enumerate(pid_container):
|
|
assert idx == pid, "See code comment for explanation"
|
|
return dataset |