def main():
gt_root_folder = '/dataset/kitti_format/waymo/training/'
cam_idx = 0
thresh = 5
lidar_dtype = float
gt_label_folder = os.path.join(gt_root_folder, 'label_{}/'.format(cam_idx))
gt_lidar_folder = os.path.join(gt_root_folder, 'velodyne/')
gt_calib_folder = os.path.join(gt_root_folder, 'calib/')
new_label_folder = os.path.join(gt_root_folder,
'label_filtered_{}/'.format(cam_idx))
os.makedirs(new_label_folder, exist_ok=True)
label_names = [
f.name.split('.')[0] for f in os.scandir(gt_label_folder)
if f.is_file() and f.name.endswith('.txt')
]
for sample_name in tqdm.tqdm(label_names):
calib_filename = os.path.join(gt_calib_folder, sample_name + '.txt')
gt_filename = os.path.join(gt_label_folder, sample_name + '.txt')
lidar_filename = os.path.join(gt_lidar_folder, sample_name + '.bin')
lidar_scan = utils.load_velo_scan(lidar_filename, dtype=lidar_dtype)
calib = utils.Calibration(calib_filename, cam_idx=cam_idx)
objects_gt = utils.read_label(gt_filename)
filtered_objects = filter_boxes_kitti(objects_gt,
lidar_scan,
calib,
thresh=thresh)
writepath = os.path.join(new_label_folder, sample_name + '.txt')
# print(f"Before filtering: {len(objects_gt)}, after filtering {len(filtered_objects)}")
with open(writepath, 'w') as f:
for obj in filtered_objects:
f.write(obj.get_string_ann() + '\n')
def get_lidar(self, idx):
assert (idx < self.num_samples)
lidar_filename = os.path.join(self.lidar_dir, '%06d.bin' % (idx))
return utils.load_velo_scan(lidar_filename)
def get_lidar(self, idx):
assert (idx < self.num_samples)
lidar_filename = self.lidar_filenames[idx]
return utils.load_velo_scan(lidar_filename)