data_manager.py:自动处理数据集,返回数据集的一些常用属性
from __future__ import print_function, absolute_import
import os
import os.path as osp
import re
import numpy as np
import glob
from IPython import embed
class Market1501(object):
"""
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)
"""
dataset_dir = 'market1501'
def __init__(self, root='data', **kwargs):
self.dataset_dir = osp.join(root, self.dataset_dir)
self.train_dir = osp.join(self.dataset_dir, 'bounding_box_train')
self.query_dir = osp.join(self.dataset_dir, 'query')
self.gallery_dir = osp.join(self.dataset_dir, 'bounding_box_test')
self._check_before_run()
'''
想要拿出的东西:文件路径,标注信息(id,camid),图片数量
'''
train, num_train_pids,num_train_imgs = self._process_dir(self.train_dir,relabel=True)
query, num_query_pids, num_query_imgs = self._process_dir(self.query_dir, relabel=False)
gallery, num_gallery_pids, num_gallery_imgs = self._process_dir(self.gallery_dir, relabel=False)
num_total_pids = num_train_pids + num_query_pids
num_total_imgs = num_train_imgs + num_query_imgs + num_gallery_imgs
print("=> Market1501 loaded")
print("Dataset statistics:")
print(" ------------------------------")
print(" subset | # ids | # images")
print(" ------------------------------")
print(" train | {:5d} | {:8d}".format(num_train_pids, num_train_imgs))
print(" query | {:5d} | {:8d}".format(num_query_pids, num_query_imgs))
print(" gallery | {:5d} | {:8d}".format(num_gallery_pids, num_gallery_imgs))
print(" ------------------------------")
print(" total | {:5d} | {:8d}".format(num_total_pids, num_total_imgs))
print(" ------------------------------")
self.train = train
self.query = query
self.gallery = gallery
self.num_train_pids = num_train_pids
self.num_query_pids = num_query_pids
self.num_gallery_pids = num_gallery_pids
def _check_before_run(self):
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())
if pid == -1: continue
pid_container.add(pid)
pid2label = {pid: lable for lable, pid in enumerate(pid_container)}
dataset = []
for img_path in img_paths:
pid, camid = map(int, pattern.search(img_path).groups())
if pid == -1: continue
assert 0 <= pid <= 1501
assert 1 <= camid <= 6
camid -= 1
if relabel:
pid = pid2label[pid]
dataset.append((img_path,pid,camid))
num_pids = len(pid_container)
num_imgs = len(img_paths)
return dataset, num_pids, num_imgs
if __name__ == '__main__':
data = Market1501(root='../../data')