diff --git a/mmdet3d/__init__.py b/mmdet3d/__init__.py
index 643c39c9..a951e2cc 100644
--- a/mmdet3d/__init__.py
+++ b/mmdet3d/__init__.py
@@ -1,4 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
+# Copyright 2024 Huawei Technologies Co., Ltd
 import mmcv
 
 import mmdet
@@ -19,7 +20,7 @@ def digit_version(version_str):
 
 
 mmcv_minimum_version = '1.5.2'
-mmcv_maximum_version = '1.7.0'
+mmcv_maximum_version = '1.7.2'
 mmcv_version = digit_version(mmcv.__version__)
 
 
diff --git a/mmdet3d/datasets/nuscenes_dataset.py b/mmdet3d/datasets/nuscenes_dataset.py
index 47d6e15e..539205bf 100644
--- a/mmdet3d/datasets/nuscenes_dataset.py
+++ b/mmdet3d/datasets/nuscenes_dataset.py
@@ -1,4 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
+# Copyright 2024 Huawei Technologies Co., Ltd
 import tempfile
 from os import path as osp
 
@@ -316,7 +317,7 @@ class NuScenesDataset(Custom3DDataset):
         print('Start to convert detection format...')
         for sample_id, det in enumerate(mmcv.track_iter_progress(results)):
             annos = []
-            boxes = output_to_nusc_box(det, self.with_velocity)
+            boxes = output_to_nusc_box(det)
             sample_token = self.data_infos[sample_id]['token']
             boxes = lidar_nusc_box_to_global(self.data_infos[sample_id], boxes,
                                              mapped_class_names,
@@ -573,7 +574,7 @@ class NuScenesDataset(Custom3DDataset):
                         file_name, show)
 
 
-def output_to_nusc_box(detection, with_velocity=True):
+def output_to_nusc_box(detection):
     """Convert the output to the box class in the nuScenes.
 
     Args:
@@ -593,24 +594,21 @@ def output_to_nusc_box(detection, with_velocity=True):
     box_gravity_center = box3d.gravity_center.numpy()
     box_dims = box3d.dims.numpy()
     box_yaw = box3d.yaw.numpy()
-
-    # our LiDAR coordinate system -> nuScenes box coordinate system
-    nus_box_dims = box_dims[:, [1, 0, 2]]
+    # check whether this is necessary
+    # with dir_offset & dir_limit in the head
+    box_yaw = -box_yaw - np.pi / 2
 
     box_list = []
     for i in range(len(box3d)):
         quat = pyquaternion.Quaternion(axis=[0, 0, 1], radians=box_yaw[i])
-        if with_velocity:
-            velocity = (*box3d.tensor[i, 7:9], 0.0)
-        else:
-            velocity = (0, 0, 0)
+        velocity = (*box3d.tensor[i, 7:9], 0.0)
         # velo_val = np.linalg.norm(box3d[i, 7:9])
         # velo_ori = box3d[i, 6]
         # velocity = (
         # velo_val * np.cos(velo_ori), velo_val * np.sin(velo_ori), 0.0)
         box = NuScenesBox(
             box_gravity_center[i],
-            nus_box_dims[i],
+            box_dims[i],
             quat,
             label=labels[i],
             score=scores[i],
diff --git a/requirements/runtime.txt b/requirements/runtime.txt
index 643cb0cd..309f0042 100644
--- a/requirements/runtime.txt
+++ b/requirements/runtime.txt
@@ -1,10 +1,10 @@
 lyft_dataset_sdk
-networkx>=2.2,<2.3
-numba==0.53.0
+networkx==2.8
+numba==0.58.1
 numpy
 nuscenes-devkit
 plyfile
-scikit-image
+scikit-image==0.21.0
 # by default we also use tensorboard to log results
 tensorboard
-trimesh>=2.35.39,<2.35.40
+trimesh>=2.35.39,<2.35.40
\ No newline at end of file