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体验新版 GitCode,发现更多精彩内容 >>
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d38b8694
编写于
2月 11, 2018
作者:
Q
qingqing01
提交者:
GitHub
2月 11, 2018
浏览文件
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电子邮件补丁
差异文件
Fix the input dimension for multiclass_nms_op. (#8232)
上级
e800597b
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
24 addition
and
15 deletion
+24
-15
paddle/fluid/operators/multiclass_nms_op.cc
paddle/fluid/operators/multiclass_nms_op.cc
+19
-10
python/paddle/v2/fluid/tests/test_multiclass_nms_op.py
python/paddle/v2/fluid/tests/test_multiclass_nms_op.py
+5
-5
未找到文件。
paddle/fluid/operators/multiclass_nms_op.cc
浏览文件 @
d38b8694
...
...
@@ -38,22 +38,22 @@ class MultiClassNMSOp : public framework::OperatorWithKernel {
auto
box_dims
=
ctx
->
GetInputDim
(
"BBoxes"
);
auto
score_dims
=
ctx
->
GetInputDim
(
"Scores"
);
PADDLE_ENFORCE_EQ
(
box_dims
.
size
(),
2
,
"The rank of Input(BBoxes) must be
2
."
);
PADDLE_ENFORCE_EQ
(
box_dims
.
size
(),
3
,
"The rank of Input(BBoxes) must be
3
."
);
PADDLE_ENFORCE_EQ
(
score_dims
.
size
(),
3
,
"The rank of Input(Scores) must be 3."
);
PADDLE_ENFORCE_EQ
(
box_dims
[
1
],
4
,
PADDLE_ENFORCE_EQ
(
box_dims
[
2
],
4
,
"The 2nd dimension of Input(BBoxes) must be 4, "
"represents the layout of coordinate "
"[xmin, ymin, xmax, ymax]"
);
PADDLE_ENFORCE_EQ
(
box_dims
[
0
],
score_dims
[
2
],
PADDLE_ENFORCE_EQ
(
box_dims
[
1
],
score_dims
[
2
],
"The 1st dimensiong of Input(BBoxes) must be equal to "
"3rd dimension of Input(Scores), which represents the "
"predicted bboxes."
);
// Here the box_dims[0] is not the real dimension of output.
// It will be rewritten in the computing kernel.
ctx
->
SetOutputDim
(
"Out"
,
{
box_dims
[
0
],
6
});
ctx
->
SetOutputDim
(
"Out"
,
{
box_dims
[
1
],
6
});
}
protected:
...
...
@@ -260,15 +260,20 @@ class MultiClassNMSKernel : public framework::OpKernel<T> {
int64_t
batch_size
=
score_dims
[
0
];
int64_t
class_num
=
score_dims
[
1
];
int64_t
predict_dim
=
score_dims
[
2
];
int64_t
box_dim
=
boxes
->
dims
()[
2
];
std
::
vector
<
std
::
map
<
int
,
std
::
vector
<
int
>>>
all_indices
;
std
::
vector
<
size_t
>
batch_starts
=
{
0
};
for
(
int64_t
i
=
0
;
i
<
batch_size
;
++
i
)
{
Tensor
ins_score
=
scores
->
Slice
(
i
,
i
+
1
);
ins_score
.
Resize
({
class_num
,
predict_dim
});
Tensor
ins_boxes
=
boxes
->
Slice
(
i
,
i
+
1
);
ins_boxes
.
Resize
({
predict_dim
,
box_dim
});
std
::
map
<
int
,
std
::
vector
<
int
>>
indices
;
int
num_nmsed_out
=
0
;
MultiClassNMS
(
ctx
,
ins_score
,
*
boxes
,
indices
,
num_nmsed_out
);
MultiClassNMS
(
ctx
,
ins_score
,
ins_
boxes
,
indices
,
num_nmsed_out
);
all_indices
.
push_back
(
indices
);
batch_starts
.
push_back
(
batch_starts
.
back
()
+
num_nmsed_out
);
}
...
...
@@ -282,11 +287,15 @@ class MultiClassNMSKernel : public framework::OpKernel<T> {
for
(
int64_t
i
=
0
;
i
<
batch_size
;
++
i
)
{
Tensor
ins_score
=
scores
->
Slice
(
i
,
i
+
1
);
ins_score
.
Resize
({
class_num
,
predict_dim
});
Tensor
ins_boxes
=
boxes
->
Slice
(
i
,
i
+
1
);
ins_boxes
.
Resize
({
predict_dim
,
box_dim
});
int64_t
s
=
batch_starts
[
i
];
int64_t
e
=
batch_starts
[
i
+
1
];
if
(
e
>
s
)
{
Tensor
out
=
outs
->
Slice
(
s
,
e
);
MultiClassOutput
(
ins_score
,
*
boxes
,
all_indices
[
i
],
&
out
);
MultiClassOutput
(
ins_score
,
ins_
boxes
,
all_indices
[
i
],
&
out
);
}
}
}
...
...
@@ -303,9 +312,9 @@ class MultiClassNMSOpMaker : public framework::OpProtoAndCheckerMaker {
MultiClassNMSOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"BBoxes"
,
"(Tensor) A
2-D Tensor with shape [
M, 4] represents the "
"predicted locations of M bounding bboxes
. Each bounding box
"
"has four coordinate values and the layout is "
"(Tensor) A
3-D Tensor with shape [N,
M, 4] represents the "
"predicted locations of M bounding bboxes
, N is the batch size.
"
"
Each bounding box
has four coordinate values and the layout is "
"[xmin, ymin, xmax, ymax]."
);
AddInput
(
"Scores"
,
"(Tensor) A 3-D Tensor with shape [N, C, M] represents the "
...
...
python/paddle/v2/fluid/tests/test_multiclass_nms_op.py
浏览文件 @
d38b8694
...
...
@@ -137,7 +137,7 @@ def batched_multiclass_nms(boxes, scores, background, score_threshold,
det_outs
=
[]
lod
=
[
0
]
for
n
in
range
(
batch_size
):
nmsed_outs
,
nmsed_num
=
multiclass_nms
(
boxes
,
scores
[
n
],
background
,
nmsed_outs
,
nmsed_num
=
multiclass_nms
(
boxes
[
n
]
,
scores
[
n
],
background
,
score_threshold
,
nms_threshold
,
nms_top_k
,
keep_top_k
)
lod
.
append
(
lod
[
-
1
]
+
nmsed_num
)
...
...
@@ -145,7 +145,7 @@ def batched_multiclass_nms(boxes, scores, background, score_threshold,
for
c
,
indices
in
nmsed_outs
.
iteritems
():
for
idx
in
indices
:
xmin
,
ymin
,
xmax
,
ymax
=
boxes
[
idx
][:]
xmin
,
ymin
,
xmax
,
ymax
=
boxes
[
n
][
idx
][:]
det_outs
.
append
([
c
,
scores
[
n
][
c
][
idx
],
xmin
,
ymin
,
xmax
,
ymax
])
return
det_outs
,
lod
...
...
@@ -179,9 +179,9 @@ class TestMulticlassNMSOp(OpTest):
scores
=
np
.
reshape
(
scores
,
(
N
,
M
,
C
))
scores
=
np
.
transpose
(
scores
,
(
0
,
2
,
1
))
boxes
=
np
.
random
.
random
((
M
,
BOX_SIZE
)).
astype
(
'float32'
)
boxes
[:,
0
:
2
]
=
boxes
[
:,
0
:
2
]
*
0.5
boxes
[:,
2
:
4
]
=
boxes
[
:,
2
:
4
]
*
0.5
+
0.5
boxes
=
np
.
random
.
random
((
N
,
M
,
BOX_SIZE
)).
astype
(
'float32'
)
boxes
[:,
:,
0
:
2
]
=
boxes
[:,
:,
0
:
2
]
*
0.5
boxes
[:,
:,
2
:
4
]
=
boxes
[:,
:,
2
:
4
]
*
0.5
+
0.5
nmsed_outs
,
lod
=
batched_multiclass_nms
(
boxes
,
scores
,
background
,
score_threshold
,
nms_threshold
,
...
...
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