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Fix for BEVFusion HungarianAssigner3D #2911

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Fix for BEVFusion HungarianAssigner3D #2911

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962f093
[Fix] Replace np.long with np.int64 (#2872)
chbehrens Jan 17, 2024
cd551e4
returning a tensor instead of 'None' for max_overlaps which provides…
Feb 26, 2024
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2 changes: 1 addition & 1 deletion mmdet3d/datasets/transforms/dbsampler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -280,7 +280,7 @@ def sample_all(self,
s_points_list.append(s_points)

gt_labels = np.array([self.cat2label[s['name']] for s in sampled],
dtype=np.long)
dtype=np.int64)

if ground_plane is not None:
xyz = sampled_gt_bboxes[:, :3]
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9 changes: 8 additions & 1 deletion projects/BEVFusion/bevfusion/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -271,8 +271,15 @@ def assign(self, bboxes, gt_bboxes, gt_labels, cls_pred, train_cfg):
if num_gts == 0:
# No ground truth, assign all to background
assigned_gt_inds[:] = 0
max_overlaps = torch.zeros(
max(num_gts, num_bboxes),
device=bboxes.device,
dtype=torch.float32)
return AssignResult(
num_gts, assigned_gt_inds, None, labels=assigned_labels)
num_gts,
assigned_gt_inds,
max_overlaps,
labels=assigned_labels)

# 2. compute the weighted costs
# Hard code here to be compatible with the interface of
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