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Revert "adapt boxes_overlap_bev & box_iou_rotated (#3162)" #3232

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Revert "adapt boxes_overlap_bev & box_iou_rotated (#3162)" #3232

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5 changes: 5 additions & 0 deletions mmcv/ops/box_iou_rotated.py
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Original file line number Diff line number Diff line change
Expand Up @@ -142,6 +142,11 @@ def box_iou_rotated(bboxes1: torch.Tensor,
flip_mat[-1] = -1
bboxes1 = bboxes1 * flip_mat
bboxes2 = bboxes2 * flip_mat
if bboxes1.device.type == 'npu':
scale_mat = bboxes1.new_ones(bboxes1.shape[-1])
scale_mat[-1] = 1.0 / 0.01745329252
bboxes1 = bboxes1 * scale_mat
bboxes2 = bboxes2 * scale_mat
bboxes1 = bboxes1.contiguous()
bboxes2 = bboxes2.contiguous()
ext_module.box_iou_rotated(
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37 changes: 33 additions & 4 deletions mmcv/ops/csrc/pytorch/npu/box_iou_rotated_npu.cpp
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Expand Up @@ -8,11 +8,40 @@ void box_iou_rotated_impl(const Tensor boxes1, const Tensor boxes2, Tensor ious,

void box_iou_rotated_npu(const Tensor boxes1, const Tensor boxes2, Tensor ious,
const int mode_flag, const bool aligned) {
TORCH_CHECK(boxes1.size(1) == 5, "boxes1 must be 2D tensor (N, 5)");
TORCH_CHECK(boxes1.size(1) == 5, "boxes1 must be 2D tensor (N, 5)");
at::Tensor boxes = at::ones_like(boxes1);
at::Tensor query_boxes = at::ones_like(boxes2);
boxes = boxes1.transpose(0, 1).unsqueeze(0);
query_boxes = boxes2.transpose(0, 1).unsqueeze(0);

EXEC_NPU_CMD(aclnnBoxIou, boxes1, boxes2, mode_flag, aligned, ious);
return;
bool is_trans = false;
string modeStr = "iou";
if (mode_flag == 1) {
modeStr = "iof";
}
bool is_cross = true;
if (aligned) {
is_cross = false;
}
float v_threshold = 0;
float e_threshold = 0;

OpCommand cmd;
cmd.Name("RotatedIou")
.Input(boxes)
.Input(query_boxes)
.Output(ious)
.Attr("trans", is_trans)
.Attr("mode", modeStr)
.Attr("is_cross", is_cross)
.Attr("v_threshold", v_threshold)
.Attr("e_threshold", e_threshold)
.Run();

if (is_cross) {
ious = ious.view({boxes1.size(0), boxes2.size(0)});
} else {
ious = ious.view({boxes1.size(0), 1});
}
}

REGISTER_NPU_IMPL(box_iou_rotated_impl, box_iou_rotated_npu);
6 changes: 1 addition & 5 deletions tests/test_ops/test_iou3d.py
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Expand Up @@ -11,11 +11,7 @@
pytest.param(
'cuda',
marks=pytest.mark.skipif(
not IS_CUDA_AVAILABLE, reason='requires CUDA support')),
pytest.param(
'npu',
marks=pytest.mark.skipif(
not IS_NPU_AVAILABLE, reason='requires NPU support'))
not IS_CUDA_AVAILABLE, reason='requires CUDA support'))
])
def test_boxes_overlap_bev(device):
np_boxes1 = np.asarray([[1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 0.0],
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