[Fix]Fix a bug in StackQueryAndGroup (#2043)

* fix a bug

* fix a batch inference bug

* fix docs

mmdet3d/models/layers/pointnet_modules/stack_point_sa_module.py

@@ -57,10 +57,11 @@ def forward(self,
  'new_xyz: str(new_xyz.shape), new_xyz_batch_cnt: ' \
  'str(new_xyz_batch_cnt)'
 
- # idx: (M1 + M2 ..., nsample), empty_ball_mask: (M1 + M2 ...)
- idx, empty_ball_mask = ball_query(0, self.radius, self.sample_nums,
- xyz, new_xyz, xyz_batch_cnt,
- new_xyz_batch_cnt)
+ # idx: (M1 + M2 ..., nsample)
+ idx = ball_query(0, self.radius, self.sample_nums, xyz, new_xyz,
+ xyz_batch_cnt, new_xyz_batch_cnt)
+ empty_ball_mask = (idx[:, 0] == -1)
+ idx[empty_ball_mask] = 0
  grouped_xyz = grouping_operation(
  xyz, idx, xyz_batch_cnt,
  new_xyz_batch_cnt) # (M1 + M2, 3, nsample)

mmdet3d/models/roi_heads/bbox_heads/pv_rcnn_bbox_head.py

@@ -4,6 +4,8 @@
 import numpy as np
 import torch
 from mmcv.cnn import ConvModule
+from mmdet.models.task_modules.samplers import SamplingResult
+from mmdet.models.utils import multi_apply
 from mmengine.model import BaseModule
 from mmengine.structures import InstanceData
 from torch import nn as nn
@@ -14,8 +16,6 @@
 from mmdet3d.structures.bbox_3d import (LiDARInstance3DBoxes,
  rotation_3d_in_axis, xywhr2xyxyr)
 from mmdet3d.utils import InstanceList
-from mmdet.models.task_modules.samplers import SamplingResult
-from mmdet.models.utils import multi_apply
 
 
 @MODELS.register_module()
@@ -440,21 +440,21 @@ def get_results(self,
  # post processing
  result_list = []
  for batch_id in range(batch_size):
- cls_preds = cls_preds[roi_batch_id == batch_id]
+ cur_cls_preds = cls_preds[roi_batch_id == batch_id]
  box_preds = batch_box_preds[roi_batch_id == batch_id]
  label_preds = class_labels[batch_id]
 
- cls_preds = cls_preds.sigmoid()
- cls_preds, _ = torch.max(cls_preds, dim=-1)
+ cur_cls_preds = cur_cls_preds.sigmoid()
+ cur_cls_preds, _ = torch.max(cur_cls_preds, dim=-1)
  selected = self.class_agnostic_nms(
- scores=cls_preds,
+ scores=cur_cls_preds,
  bbox_preds=box_preds,
  input_meta=input_metas[batch_id],
  nms_cfg=test_cfg)
 
  selected_bboxes = box_preds[selected]
  selected_label_preds = label_preds[selected]
- selected_scores = cls_preds[selected]
+ selected_scores = cur_cls_preds[selected]
 
  results = InstanceData()
  results.bboxes_3d = input_metas[batch_id]['box_type_3d'](