def __init__(self, root='', split_id=0, **kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.download_dataset(self.dataset_dir, self.dataset_url)
self.zip_path = osp.join(self.dataset_dir, 'CUHK01.zip')
self.campus_dir = osp.join(self.dataset_dir, 'campus')
self.split_path = osp.join(self.dataset_dir, 'splits.json')
self.extract_file()
required_files = [self.dataset_dir, self.campus_dir]
self.check_before_run(required_files)
self.prepare_split()
splits = read_json(self.split_path)
if split_id >= len(splits):
raise ValueError(
'split_id exceeds range, received {}, but expected between 0 and {}'
.format(split_id,
len(splits) - 1))
split = splits[split_id]
train = split['train']
query = split['query']
gallery = split['gallery']
train = [tuple(item) for item in train]
query = [tuple(item) for item in query]
gallery = [tuple(item) for item in gallery]
super(CUHK01, self).__init__(train, query, gallery, **kwargs)
def __init__(self, root='', split_id=0, **kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.download_dataset(self.dataset_dir, self.dataset_url)
self.cam_a_dir = osp.join(
self.dataset_dir, 'prid_2011', 'single_shot', 'cam_a'
)
self.cam_b_dir = osp.join(
self.dataset_dir, 'prid_2011', 'single_shot', 'cam_b'
)
self.split_path = osp.join(self.dataset_dir, 'splits_single_shot.json')
required_files = [self.dataset_dir, self.cam_a_dir, self.cam_b_dir]
self.check_before_run(required_files)
self.prepare_split()
splits = read_json(self.split_path)
if split_id >= len(splits):
raise ValueError(
'split_id exceeds range, received {}, but expected between 0 and {}'
.format(split_id,
len(splits) - 1)
)
split = splits[split_id]
train, query, gallery = self.process_split(split)
super(PRID, self).__init__(train, query, gallery, **kwargs)
def __init__(self, root='', split_id=0, **kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.download_dataset(self.dataset_dir, self.dataset_url)
self.split_path = osp.join(self.dataset_dir, 'splits_prid2011.json')
self.cam_a_dir = osp.join(self.dataset_dir, 'prid_2011', 'multi_shot',
'cam_a')
self.cam_b_dir = osp.join(self.dataset_dir, 'prid_2011', 'multi_shot',
'cam_b')
required_files = [self.dataset_dir, self.cam_a_dir, self.cam_b_dir]
self.check_before_run(required_files)
splits = read_json(self.split_path)
if split_id >= len(splits):
raise ValueError(
'split_id exceeds range, received {}, but expected between 0 and {}'
.format(split_id,
len(splits) - 1))
split = splits[split_id]
train_dirs, test_dirs = split['train'], split['test']
train = self.process_dir(train_dirs, cam1=True, cam2=True)
query = self.process_dir(test_dirs, cam1=True, cam2=False)
gallery = self.process_dir(test_dirs, cam1=False, cam2=True)
super(PRID2011, self).__init__(train, query, gallery, **kwargs)
def __init__(self, root='', split_id=0, **kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.download_dataset(self.dataset_dir, self.dataset_url)
self.data_dir = osp.join(self.dataset_dir, 'i-LIDS-VID')
self.split_dir = osp.join(self.dataset_dir, 'train-test people splits')
self.split_mat_path = osp.join(self.split_dir,
'train_test_splits_ilidsvid.mat')
self.split_path = osp.join(self.dataset_dir, 'splits.json')
self.cam_1_path = osp.join(self.dataset_dir,
'i-LIDS-VID/sequences/cam1')
self.cam_2_path = osp.join(self.dataset_dir,
'i-LIDS-VID/sequences/cam2')
required_files = [self.dataset_dir, self.data_dir, self.split_dir]
self.check_before_run(required_files)
self.prepare_split()
splits = read_json(self.split_path)
if split_id >= len(splits):
raise ValueError(
'split_id exceeds range, received {}, but expected between 0 and {}'
.format(split_id,
len(splits) - 1))
split = splits[split_id]
train_dirs, test_dirs = split['train'], split['test']
train = self.process_data(train_dirs, cam1=True, cam2=True)
query = self.process_data(test_dirs, cam1=True, cam2=False)
gallery = self.process_data(test_dirs, cam1=False, cam2=True)
super(iLIDSVID, self).__init__(train, query, gallery, **kwargs)
def __init__(self,
root='',
split_id=0,
cuhk03_labeled=False,
cuhk03_classic_split=False,
**kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
# self.download_dataset(self.dataset_dir, self.dataset_url)
self.data_dir = osp.join(self.dataset_dir, 'cuhk03_release')
self.raw_mat_path = osp.join(self.data_dir, 'cuhk-03.mat')
self.imgs_detected_dir = osp.join(self.dataset_dir, 'images_detected')
self.imgs_labeled_dir = osp.join(self.dataset_dir, 'images_labeled')
self.split_classic_det_json_path = osp.join(
self.dataset_dir, 'splits_classic_detected.json')
self.split_classic_lab_json_path = osp.join(
self.dataset_dir, 'splits_classic_labeled.json')
self.split_new_det_json_path = osp.join(self.dataset_dir,
'splits_new_detected.json')
self.split_new_lab_json_path = osp.join(self.dataset_dir,
'splits_new_labeled.json')
self.split_new_det_mat_path = osp.join(
self.dataset_dir, 'cuhk03_new_protocol_config_detected.mat')
self.split_new_lab_mat_path = osp.join(
self.dataset_dir, 'cuhk03_new_protocol_config_labeled.mat')
required_files = [
self.dataset_dir, self.data_dir, self.raw_mat_path,
self.split_new_det_mat_path, self.split_new_lab_mat_path
]
self.check_before_run(required_files)
self.preprocess_split()
if cuhk03_labeled:
split_path = self.split_classic_lab_json_path if cuhk03_classic_split else self.split_new_lab_json_path
else:
split_path = self.split_classic_det_json_path if cuhk03_classic_split else self.split_new_det_json_path
splits = read_json(split_path)
assert split_id < len(
splits
), 'Condition split_id ({}) < len(splits) ({}) is false'.format(
split_id, len(splits))
split = splits[split_id]
train = split['train']
query = split['query']
gallery = split['gallery']
print('Init complete')
super(CUHK03, self).__init__(train, query, gallery, **kwargs)
def process_dir(self, dir_path, json_path, relabel):
if osp.exists(json_path):
split = read_json(json_path)
return split['tracklets']
print('=> Generating split json file (** this might take a while **)')
pdirs = glob.glob(osp.join(dir_path, '*')) # avoid .DS_Store
print('Processing "{}" with {} person identities'.format(
dir_path, len(pdirs)))
pid_container = set()
for pdir in pdirs:
pid = int(osp.basename(pdir))
pid_container.add(pid)
pid2label = {pid: label for label, pid in enumerate(pid_container)}
tracklets = []
for pdir in pdirs:
pid = int(osp.basename(pdir))
if relabel:
pid = pid2label[pid]
tdirs = glob.glob(osp.join(pdir, '*'))
for tdir in tdirs:
raw_img_paths = glob.glob(osp.join(tdir, '*.jpg'))
num_imgs = len(raw_img_paths)
if num_imgs < self.min_seq_len:
continue
img_paths = []
for img_idx in range(num_imgs):
# some tracklet starts from 0002 instead of 0001
img_idx_name = 'F' + str(img_idx + 1).zfill(4)
res = glob.glob(
osp.join(tdir, '*' + img_idx_name + '*.jpg'))
if len(res) == 0:
warnings.warn(
'Index name {} in {} is missing, skip'.format(
img_idx_name, tdir))
continue
img_paths.append(res[0])
img_name = osp.basename(img_paths[0])
if img_name.find('_') == -1:
# old naming format: 0001C6F0099X30823.jpg
camid = int(img_name[5]) - 1
else:
# new naming format: 0001_C6_F0099_X30823.jpg
camid = int(img_name[6]) - 1
img_paths = tuple(img_paths)
tracklets.append((img_paths, pid, camid))
print('Saving split to {}'.format(json_path))
split_dict = {'tracklets': tracklets}
write_json(split_dict, json_path)
return tracklets
def __init__(self, root='', split_id=0, **kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.download_dataset(self.dataset_dir, self.dataset_url)
self.probe_path = osp.join(
self.dataset_dir, 'underground_reid', 'probe'
)
self.gallery_path = osp.join(
self.dataset_dir, 'underground_reid', 'gallery'
)
self.split_mat_path = osp.join(
self.dataset_dir, 'underground_reid', 'features_and_partitions.mat'
)
self.split_path = osp.join(self.dataset_dir, 'splits.json')
required_files = [
self.dataset_dir, self.probe_path, self.gallery_path,
self.split_mat_path
]
self.check_before_run(required_files)
self.prepare_split()
splits = read_json(self.split_path)
if split_id >= len(splits):
raise ValueError(
'split_id exceeds range, received {}, '
'but expected between 0 and {}'.format(
split_id,
len(splits) - 1
)
)
split = splits[split_id]
train = split['train']
query = split['query']
gallery = split['gallery']
train = [tuple(item) for item in train]
query = [tuple(item) for item in query]
gallery = [tuple(item) for item in gallery]
super(GRID, self).__init__(train, query, gallery, **kwargs)
def __init__(self, root='', split_id=0, **kwargs):
self.root = osp.abspath(osp.expanduser(root))
self.dataset_dir = osp.join(self.root, self.dataset_dir)
self.download_dataset(self.dataset_dir, self.dataset_url)
self.data_dir = osp.join(self.dataset_dir, 'i-LIDS_Pedestrian/Persons')
self.split_path = osp.join(self.dataset_dir, 'splits.json')
required_files = [self.dataset_dir, self.data_dir]
self.check_before_run(required_files)
self.prepare_split()
splits = read_json(self.split_path)
if split_id >= len(splits):
raise ValueError('split_id exceeds range, received {}, but '
'expected between 0 and {}'.format(
split_id,
len(splits) - 1))
split = splits[split_id]
train, query, gallery = self.process_split(split)
super(iLIDS, self).__init__(train, query, gallery, **kwargs)
