add config & fix spvcnn name

mmdet3d/configs/_base_/models/spvcnn.py

@@ -0,0 +1,41 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from mmdet3d.models.backbones.spvcnn_backbone import SPVCNNBackbone
+from mmdet3d.models.data_preprocessors.data_preprocessor import \
+    Det3DDataPreprocessor
+from mmdet3d.models.decode_heads.minkunet_head import MinkUNetHead
+from mmdet3d.models.segmentors.minkunet import MinkUNet
+
+model = dict(
+    type=MinkUNet,
+    data_preprocessor=dict(
+        type=Det3DDataPreprocessor,
+        voxel=True,
+        voxel_type='minkunet',
+        batch_first=False,
+        max_voxels=80000,
+        voxel_layer=dict(
+            max_num_points=-1,
+            point_cloud_range=[-100, -100, -20, 100, 100, 20],
+            voxel_size=[0.05, 0.05, 0.05],
+            max_voxels=(-1, -1))),
+    backbone=dict(
+        type=SPVCNNBackbone,
+        in_channels=4,
+        num_stages=4,
+        base_channels=32,
+        encoder_channels=[32, 64, 128, 256],
+        encoder_blocks=[2, 2, 2, 2],
+        decoder_channels=[256, 128, 96, 96],
+        decoder_blocks=[2, 2, 2, 2],
+        block_type='basic',
+        sparseconv_backend='torchsparse',
+        drop_ratio=0.3),
+    decode_head=dict(
+        type=MinkUNetHead,
+        channels=96,
+        num_classes=19,
+        dropout_ratio=0,
+        loss_decode=dict(type='mmdet.CrossEntropyLoss', avg_non_ignore=True),
+        ignore_index=19),
+    train_cfg=dict(),
+    test_cfg=dict())