[Fix]Fix Centerpoints point clouds range (#1998)

* fix comments

* fix config

* fix

* fix

configs/_base_/datasets/nus-3d.py

 # If point cloud range is changed, the models should also change their point
 # cloud range accordingly
 point_cloud_range = [-50, -50, -5, 50, 50, 3]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-50, -50.8, -5, 50, 49.2, 3]
 # For nuScenes we usually do 10-class detection
 class_names = [
     'car', 'truck', 'trailer', 'bus', 'construction_vehicle', 'bicycle',

configs/centerpoint/centerpoint_pillar02_second_secfpn_8xb4-cyclic-20e_nus-3d.py

@@ -7,6 +7,9 @@ _base_ = [
 # If point cloud range is changed, the models should also change their point
 # cloud range accordingly
 point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-51.2, -52, -5.0, 51.2, 50.4, 3.0]
 # For nuScenes we usually do 10-class detection
 class_names = [
     'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',

configs/centerpoint/centerpoint_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d.py

@@ -4,6 +4,9 @@ _base_ = ['./centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 # cloud range accordingly
 voxel_size = [0.075, 0.075, 0.2]
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-54, -54.8, -5.0, 54, 53.2, 3.0]
 # For nuScenes we usually do 10-class detection
 class_names = [
     'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',

configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn-circlenms_8xb4-flip-tta-cyclic-20e_nus-3d.py

@@ -2,6 +2,9 @@ _base_ = './centerpoint_voxel0075_second_secfpn_' \
          'head-dcn-circlenms_8xb4_cyclic-20e_nus-3d.py'
 
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-54, -54.8, -5.0, 54, 53.2, 3.0]
 file_client_args = dict(backend='disk')
 class_names = [
     'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',

configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-flip-tta-cyclic-20e_nus-3d.py

@@ -2,6 +2,9 @@ _base_ = './centerpoint_voxel0075_second_secfpn' \
          '_head-dcn_8xb4-cyclic-20e_nus-3d.py'
 
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-54, -54.8, -5.0, 54, 53.2, 3.0]
 file_client_args = dict(backend='disk')
 class_names = [
     'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',

configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-tta-cyclic-20e_nus-3d.py

@@ -4,6 +4,9 @@ _base_ = './centerpoint_voxel0075_second_secfpn' \
 model = dict(test_cfg=dict(pts=dict(use_rotate_nms=True, max_num=500)))
 
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-54, -54.8, -5.0, 54, 53.2, 3.0]
 file_client_args = dict(backend='disk')
 class_names = [
     'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',

configs/centerpoint/centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py

@@ -7,6 +7,9 @@ _base_ = [
 # If point cloud range is changed, the models should also change their point
 # cloud range accordingly
 point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
+# Using calibration info convert the Lidar-coordinate point cloud range to the
+# ego-coordinate point cloud range could bring a little promotion in nuScenes.
+# point_cloud_range = [-51.2, -52, -5.0, 51.2, 50.4, 3.0]
 # For nuScenes we usually do 10-class detection
 class_names = [
     'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',