def createwaymo_info(root_path,
info_prefix,
out_dir,
workers,
max_sweeps=5):
"""Prepare the info file for waymo dataset.
Args:
root_path (str): Path of dataset root.
info_prefix (str): The prefix of info filenames.
out_dir (str): Output directory of the generated info file.
workers (int): Number of threads to be used.
max_sweeps (int): Number of input consecutive frames. Default: 5 \
Here we store pose information of these frames for later use.
"""
# Generate waymo infos
out_dir = osp.join(out_dir, 'kitti_format')
# Create ImageSets, train test split
create_trainvaltestsplitfile(out_dir)
kitti.create_waymo_info_file(out_dir, info_prefix, max_sweeps=max_sweeps)
create_groundtruth_database(
'WaymoDataset',
out_dir,
info_prefix,
f'{out_dir}/{info_prefix}_infos_train.pkl',
relative_path=False,
with_mask=False)
def waymo_data_prep(root_path,
info_prefix,
version,
out_dir,
workers,
max_sweeps=5):
"""Prepare the info file for waymo dataset.
Args:
root_path (str): Path of dataset root.
info_prefix (str): The prefix of info filenames.
out_dir (str): Output directory of the generated info file.
workers (int): Number of threads to be used.
max_sweeps (int): Number of input consecutive frames. Default: 5 \
Here we store pose information of these frames for later use.
"""
from tools.data_converter import waymo_converter as waymo
#splits = ['training', 'validation', 'testing']
splits = ['training', 'validation', 'test']
for i, split in enumerate(splits):
#load_dir = osp.join(root_path, 'waymo_format', split)
load_dir = osp.join(root_path, split)
if split == 'validation':
save_dir = osp.join(out_dir, 'kitti_format', 'training')
else:
save_dir = osp.join(out_dir, 'kitti_format', split)
converter = waymo.Waymo2KITTI(
load_dir,
save_dir,
prefix=str(i),
workers=workers,
test_mode=(split == 'test'))
converter.convert()
# Generate waymo infos
out_dir = osp.join(out_dir, 'kitti_format')
kitti.create_waymo_info_file(out_dir, info_prefix, max_sweeps=max_sweeps)
create_groundtruth_database(
'WaymoDataset',
out_dir,
info_prefix,
f'{out_dir}/{info_prefix}_infos_train.pkl',
relative_path=False,
with_mask=False)