Evaluated with "feat_" features and "cosine" metric:
Mean AP: 0.4%
CMC Scores
top-1 0.1%
top-5 0.4%
top-10 0.5%
Evaluated with "feat" features and "cosine" metric:
Mean AP: 0.3%
CMC Scores
top-1 0.1%
top-5 0.2%
top-10 0.5%
market.py as fellow
from future import absolute_import
from future import division
from future import print_function
import os
import glob
import re
import sys
import urllib
import tarfile
import zipfile
import os.path as osp
from scipy.io import loadmat
import numpy as np
import h5py
from scipy.misc import imsave
from ..utils.osutils import mkdir_if_missing
from ..utils.serialization import write_json, read_json
class Market(object):
"""
Args:
split_id (int): split index (default: 0)
cuhk03_labeled (bool): whether to load labeled images; if false, detected images are loaded (default: False)
"""
dataset_dir = 'cuhk03'
Evaluated with "feat_" features and "cosine" metric: Mean AP: 0.4% CMC Scores top-1 0.1% top-5 0.4% top-10 0.5% Evaluated with "feat" features and "cosine" metric: Mean AP: 0.3% CMC Scores top-1 0.1% top-5 0.2% top-10 0.5%
market.py as fellow from future import absolute_import from future import division from future import print_function
import os import glob import re import sys import urllib import tarfile import zipfile import os.path as osp from scipy.io import loadmat import numpy as np import h5py from scipy.misc import imsave
from ..utils.osutils import mkdir_if_missing from ..utils.serialization import write_json, read_json
class Market(object): """ Args: split_id (int): split index (default: 0) cuhk03_labeled (bool): whether to load labeled images; if false, detected images are loaded (default: False) """ dataset_dir = 'cuhk03'
dataset_dir = 'CUHK03_New'