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[Feature] Add the support of BoxIouRotated op for ascend device (#2854)

pull/2876/head
MrShadowY 2023-07-19 11:32:45 +08:00 committed by GitHub
parent ca60ccb664
commit 8fbacc446d
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5 changed files with 65 additions and 5 deletions
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2
docs/en/understand_mmcv/ops.md
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@ -9,7 +9,7 @@ We implement common ops used in detection, segmentation, etc.
| BallQuery | | √ | √ | | |
| BBoxOverlaps | | √ | √ | √ | √ |
| BorderAlign | | √ | | | |
| BoxIouRotated | √ | √ | √ | | |
| BoxIouRotated | √ | √ | √ | | √ |
| BoxIouQuadri | √ | √ | | | |
| CARAFE | | √ | √ | | |
| ChamferDistance | | √ | | | |

2
docs/zh_cn/understand_mmcv/ops.md
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@ -9,7 +9,7 @@ MMCV 提供了检测、分割等任务中常用的算子
| BallQuery | | √ | √ | | |
| BBoxOverlaps | | √ | √ | √ | √ |
| BorderAlign | | √ | | | |
| BoxIouRotated | √ | √ | √ | | |
| BoxIouRotated | √ | √ | √ | | √ |
| BoxIouQuadri | √ | √ | | | |
| CARAFE | | √ | √ | | |
| ChamferDistance | | √ | | | |

5
mmcv/ops/box_iou_rotated.py
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@ -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(

47
mmcv/ops/csrc/pytorch/npu/box_iou_rotated_npu.cpp 100644
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@ -0,0 +1,47 @@
#include "pytorch_npu_helper.hpp"
using namespace NPU_NAME_SPACE;
using namespace std;
void box_iou_rotated_impl(const Tensor boxes1, const Tensor boxes2, Tensor ious,
const int mode_flag, const bool aligned);
void box_iou_rotated_npu(const Tensor boxes1, const Tensor boxes2, Tensor ious,
const int mode_flag, const bool aligned) {
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);
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);

14
tests/test_ops/test_box_iou_rotated.py
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@ -4,7 +4,7 @@ import pytest
import torch
from mmcv.ops import box_iou_rotated
from mmcv.utils import IS_CUDA_AVAILABLE, IS_MLU_AVAILABLE
from mmcv.utils import IS_CUDA_AVAILABLE, IS_MLU_AVAILABLE, IS_NPU_AVAILABLE
class TestBoxIoURotated:
@ -54,7 +54,11 @@ class TestBoxIoURotated:
pytest.param(
'mlu',
marks=pytest.mark.skipif(
not IS_MLU_AVAILABLE, reason='requires MLU support'))
not IS_MLU_AVAILABLE, reason='requires MLU support')),
pytest.param(
'npu',
marks=pytest.mark.skipif(
not IS_NPU_AVAILABLE, reason='requires NPU support'))
])
def test_box_iou_rotated(self, device):
np_boxes1 = np.asarray(
@ -137,7 +141,11 @@ class TestBoxIoURotated:
pytest.param(
'mlu',
marks=pytest.mark.skipif(
not IS_MLU_AVAILABLE, reason='requires MLU support'))
not IS_MLU_AVAILABLE, reason='requires MLU support')),
pytest.param(
'npu',
marks=pytest.mark.skipif(
not IS_NPU_AVAILABLE, reason='requires NPU support'))
])
def test_box_iou_rotated_iof(self, device):
np_boxes1 = np.asarray(