max sweeps should be 9 to match nuscenes limit

Author: traveller59

README.md

@@ -132,8 +132,8 @@ Since the dataset is really large, you can download parts of the dataset.
 
 Then run
 ```bash
-python create_data.py nuscenes_data_prep --data_path=NUSCENES_TRAINVAL_DATASET_ROOT --version="v1.0-trainval" --max_sweeps=10
-python create_data.py nuscenes_data_prep --data_path=NUSCENES_TEST_DATASET_ROOT --version="v1.0-test" --max_sweeps=10
+python create_data.py nuscenes_data_prep --data_path=NUSCENES_TRAINVAL_DATASET_ROOT --version="v1.0-trainval" --max_sweeps=9
+python create_data.py nuscenes_data_prep --data_path=NUSCENES_TEST_DATASET_ROOT --version="v1.0-test" --max_sweeps=9
 ```
 
 * Modify config file

second/create_data.py

@@ -13,7 +13,7 @@ def kitti_data_prep(root_path):
     kitti_ds.create_reduced_point_cloud(root_path)
     create_groundtruth_database("KittiDataset", root_path, Path(root_path) / "kitti_infos_train.pkl")
 
-def nuscenes_data_prep(root_path, version, max_sweeps=10):
+def nuscenes_data_prep(root_path, version, max_sweeps=9):
     nu_ds.create_nuscenes_infos(root_path, version=version, max_sweeps=max_sweeps)
     create_groundtruth_database("NuScenesDataset", root_path, Path(root_path) / "infos_train.pkl")
 

second/data/nuscenes_dataset.py

@@ -434,7 +434,7 @@ def _fill_trainval_infos(nusc,
                          train_scenes,
                          val_scenes,
                          test=False,
-                         max_sweeps=10):
+                         max_sweeps=9):
     train_nusc_infos = []
     val_nusc_infos = []
     from pyquaternion import Quaternion
@@ -523,7 +523,7 @@ def _fill_trainval_infos(nusc,
     return train_nusc_infos, val_nusc_infos
 
 
-def create_nuscenes_infos(root_path, version="v1.0-trainval", max_sweeps=10):
+def create_nuscenes_infos(root_path, version="v1.0-trainval", max_sweeps=9):
     from nuscenes.nuscenes import NuScenes
     nusc = NuScenes(version=version, dataroot=root_path, verbose=True)
     from nuscenes.utils import splits