def main():
parser = argparse.ArgumentParser()
parser.add_argument('--in_root', default=os.path.join(fs_root(), 'data/learnlarge/merged_parametrized'))
parser.add_argument('--folds', default=['train', 'val', 'test', 'full'])
parser.add_argument('--query_dates', type=list, default=[
'2015-08-14-14-54-57', # roadworks, overcast
'2014-11-18-13-20-12', # sun, clouds
'2014-12-17-18-18-43', # night, rain
'2015-02-03-08-45-10', # snow
'2014-06-26-09-24-58' # overcast, alternate-route (validation area)
]
)
args = parser.parse_args()
print(flags_to_args(args))
folds = args.folds
in_root = args.in_root
query_dates = args.query_dates
set_aside_queries(in_root, folds, query_dates)
default=os.path.join(fs_root(),
'data/learnlarge/shuffled'))
parser.add_argument('--out_root',
default=os.path.join(fs_root(),
'data/learnlarge/clusters'))
parser.add_argument('--num_clusters',
type=dict,
default={
'train': 7000,
'test': 2000,
'val': 1000
})
parser.add_argument('--r', type=int, default=5)
args = parser.parse_args()
flags_to_args(args)
in_root = args.in_root
num_clusters = args.num_clusters
out_root = args.out_root
r = args.r
test_ref_date = args.test_ref_date
train_ref_date = args.train_ref_date
val_ref_date = args.val_ref_date
if not os.path.exists(out_root):
os.makedirs(out_root)
for mode in ['ref']:
for s in ['train', 'val', 'test']:
cluster(in_root, out_root, s, mode, r)