refactor new config of cylinder3d

mmdet3d/configs/_base_/models/cylinder3d.py

@@ -7,6 +7,7 @@
 from mmdet3d.models.voxel_encoders import SegVFE
 
 grid_shape = [480, 360, 32]
+point_cloud_range = [0, -3.14159265359, -4, 50, 3.14159265359, 2]
 model = dict(
     type=Cylinder3D,
     data_preprocessor=dict(
@@ -15,18 +16,17 @@
         voxel_type='cylindrical',
         voxel_layer=dict(
             grid_shape=grid_shape,
-            point_cloud_range=[0, -3.14159265359, -4, 50, 3.14159265359, 2],
+            point_cloud_range=point_cloud_range,
             max_num_points=-1,
-            max_voxels=-1,
-        ),
-    ),
+            max_voxels=-1)),
     voxel_encoder=dict(
         type=SegVFE,
-        feat_channels=[64, 128, 256, 256],
         in_channels=6,
+        feat_channels=[64, 128, 256, 256],
         with_voxel_center=True,
-        feat_compression=16,
-        return_point_feats=False),
+        grid_shape=grid_shape,
+        point_cloud_range=point_cloud_range,
+        feat_compression=16),
     backbone=dict(
         type=Asymm3DSpconv,
         grid_size=grid_shape,
@@ -37,13 +37,14 @@
         type=Cylinder3DHead,
         channels=128,
         num_classes=20,
+        dropout_ratio=0,
         loss_ce=dict(
             type='mmdet.CrossEntropyLoss',
             use_sigmoid=False,
             class_weight=None,
             loss_weight=1.0),
         loss_lovasz=dict(type=LovaszLoss, loss_weight=1.0, reduction='none'),
-    ),
+        conv_seg_kernel_size=3,
+        ignore_index=19),
     train_cfg=None,
-    test_cfg=dict(mode='whole'),
-)
+    test_cfg=dict(mode='whole'))

mmdet3d/configs/cylinder3d/cylinder3d_4xb4-3x_semantickitti.py

@@ -32,7 +32,7 @@
         gamma=0.1)
 ]
 
-train_dataloader.update(dict(batch_size=4, ))
+train_dataloader.update(dict(batch_size=4))
 
 # Default setting for scaling LR automatically
 #   - `enable` means enable scaling LR automatically