mirror of https://github.com/JDAI-CV/fast-reid.git
91 lines
3.1 KiB
Python
91 lines
3.1 KiB
Python
# encoding: utf-8
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"""
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@author: sherlock
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@contact: sherlockliao01@gmail.com
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"""
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import glob
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import os.path as osp
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import re
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import warnings
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from .bases import ImageDataset
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from ..datasets import DATASET_REGISTRY
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@DATASET_REGISTRY.register()
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class Market1501(ImageDataset):
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"""Market1501.
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Reference:
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Zheng et al. Scalable Person Re-identification: A Benchmark. ICCV 2015.
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URL: `<http://www.liangzheng.org/Project/project_reid.html>`_
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Dataset statistics:
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- identities: 1501 (+1 for background).
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- images: 12936 (train) + 3368 (query) + 15913 (gallery).
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"""
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_junk_pids = [0, -1]
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dataset_dir = ''
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dataset_url = 'http://188.138.127.15:81/Datasets/Market-1501-v15.09.15.zip'
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dataset_name = "market1501"
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def __init__(self, root='datasets', market1501_500k=False, **kwargs):
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# self.root = osp.abspath(osp.expanduser(root))
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self.root = root
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self.dataset_dir = osp.join(self.root, self.dataset_dir)
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# allow alternative directory structure
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self.data_dir = self.dataset_dir
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data_dir = osp.join(self.data_dir, 'Market-1501-v15.09.15')
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if osp.isdir(data_dir):
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self.data_dir = data_dir
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else:
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warnings.warn('The current data structure is deprecated. Please '
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'put data folders such as "bounding_box_train" under '
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'"Market-1501-v15.09.15".')
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self.train_dir = osp.join(self.data_dir, 'bounding_box_train')
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self.query_dir = osp.join(self.data_dir, 'query')
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self.gallery_dir = osp.join(self.data_dir, 'bounding_box_test')
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self.extra_gallery_dir = osp.join(self.data_dir, 'images')
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self.market1501_500k = market1501_500k
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required_files = [
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self.data_dir,
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self.train_dir,
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self.query_dir,
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self.gallery_dir,
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]
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if self.market1501_500k:
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required_files.append(self.extra_gallery_dir)
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self.check_before_run(required_files)
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train = self.process_dir(self.train_dir)
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query = self.process_dir(self.query_dir, is_train=False)
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gallery = self.process_dir(self.gallery_dir, is_train=False)
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if self.market1501_500k:
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gallery += self.process_dir(self.extra_gallery_dir, is_train=False)
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super(Market1501, self).__init__(train, query, gallery, **kwargs)
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def process_dir(self, dir_path, is_train=True):
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img_paths = glob.glob(osp.join(dir_path, '*.jpg'))
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pattern = re.compile(r'([-\d]+)_c(\d)')
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data = []
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for img_path in img_paths:
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pid, camid = map(int, pattern.search(img_path).groups())
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if pid == -1:
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continue # junk images are just ignored
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assert 0 <= pid <= 1501 # pid == 0 means background
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assert 1 <= camid <= 6
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camid -= 1 # index starts from 0
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if is_train:
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pid = self.dataset_name + "_" + str(pid)
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camid = self.dataset_name + "_" + str(camid)
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data.append((img_path, pid, camid))
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return data
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