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d43932c8
编写于
1月 23, 2018
作者:
W
Wang Hao
提交者:
GitHub
1月 23, 2018
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Merge pull request #7566 from wanghaox/iou_sim
add iou similarity operator
上级
9536c4e3
fa10f03f
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
262 addition
and
0 deletion
+262
-0
paddle/operators/iou_similarity_op.cc
paddle/operators/iou_similarity_op.cc
+96
-0
paddle/operators/iou_similarity_op.cu
paddle/operators/iou_similarity_op.cu
+21
-0
paddle/operators/iou_similarity_op.h
paddle/operators/iou_similarity_op.h
+90
-0
python/paddle/v2/fluid/tests/test_iou_similarity_op.py
python/paddle/v2/fluid/tests/test_iou_similarity_op.py
+55
-0
未找到文件。
paddle/operators/iou_similarity_op.cc
0 → 100755
浏览文件 @
d43932c8
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/iou_similarity_op.h"
namespace
paddle
{
namespace
operators
{
class
IOUSimilarityOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of IOUSimilarityOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Y"
),
"Input(Y) of IOUSimilarityOp should not be null."
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
y_dims
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_ENFORCE_EQ
(
x_dims
.
size
(),
2UL
,
"The rank of Input(X) must be 2."
);
PADDLE_ENFORCE_EQ
(
x_dims
[
1
],
4UL
,
"The shape of X is [N, 4]"
);
PADDLE_ENFORCE_EQ
(
y_dims
.
size
(),
2UL
,
"The rank of Input(Y) must be 2."
);
PADDLE_ENFORCE_EQ
(
y_dims
[
1
],
4UL
,
"The shape of Y is [M, 4]"
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
({
x_dims
[
0
],
y_dims
[
0
]}));
}
};
class
IOUSimilarityOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
IOUSimilarityOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"(LoDTensor, default LoDTensor<float>) "
"Box list X is a 2-D LoDTensor with shape [N, 4] holds N boxes, "
"each box is represented as [xmin, ymin, xmax, ymax], "
"the shape of X is [N, 4]. [xmin, ymin] is the left top "
"coordinate of the box if the input is image feature map, they "
"are close to the origin of the coordinate system. "
"[xmax, ymax] is the right bottom coordinate of the box. "
"This tensor can contain LoD information to represent a batch "
"of inputs. One instance of this batch can contain different "
"numbers of entities."
);
AddInput
(
"Y"
,
"(Tensor, default Tensor<float>) "
"Box list Y holds M boxes, each box is represented as "
"[xmin, ymin, xmax, ymax], the shape of X is [N, 4]. "
"[xmin, ymin] is the left top coordinate of the box if the "
"input is image feature map, and [xmax, ymax] is the right "
"bottom coordinate of the box."
);
AddOutput
(
"Out"
,
"(LoDTensor, the lod is same as input X) The output of "
"iou_similarity op, a tensor with shape [N, M] "
"representing pairwise iou scores."
);
AddComment
(
R"DOC(
IOU Similarity Operator.
Computes intersection-over-union (IOU) between two box lists.
Box list 'X' should be a LoDTensor and 'Y' is a common Tensor,
boxes in 'Y' are shared by all instance of the batched inputs of X.
Given two boxes A and B, the calculation of IOU is as follows:
$$
IOU(A, B) =
\frac{area(A\cap B)}{area(A)+area(B)-area(A\cap B)}
$$
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_WITHOUT_GRADIENT
(
iou_similarity
,
ops
::
IOUSimilarityOp
,
ops
::
IOUSimilarityOpMaker
);
REGISTER_OP_CPU_KERNEL
(
iou_similarity
,
ops
::
IOUSimilarityKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
IOUSimilarityKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/operators/iou_similarity_op.cu
0 → 100755
浏览文件 @
d43932c8
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/iou_similarity_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
iou_similarity
,
ops
::
IOUSimilarityKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
IOUSimilarityKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
paddle/operators/iou_similarity_op.h
0 → 100644
浏览文件 @
d43932c8
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "paddle/framework/op_registry.h"
#include "paddle/platform/for_range.h"
template
<
typename
T
>
inline
HOSTDEVICE
T
IOUSimilarity
(
T
xmin1
,
T
ymin1
,
T
xmax1
,
T
ymax1
,
T
xmin2
,
T
ymin2
,
T
xmax2
,
T
ymax2
)
{
constexpr
T
zero
=
static_cast
<
T
>
(
0
);
T
area1
=
(
ymax1
-
ymin1
)
*
(
xmax1
-
xmin1
);
T
area2
=
(
ymax2
-
ymin2
)
*
(
xmax2
-
xmin2
);
T
inter_xmax
=
xmax1
>
xmax2
?
xmax2
:
xmax1
;
T
inter_ymax
=
ymax1
>
ymax2
?
ymax2
:
ymax1
;
T
inter_xmin
=
xmin1
>
xmin2
?
xmin1
:
xmin2
;
T
inter_ymin
=
ymin1
>
ymin2
?
ymin1
:
ymin2
;
T
inter_height
=
inter_ymax
-
inter_ymin
;
T
inter_width
=
inter_xmax
-
inter_xmin
;
inter_height
=
inter_height
>
zero
?
inter_height
:
zero
;
inter_width
=
inter_width
>
zero
?
inter_width
:
zero
;
T
inter_area
=
inter_width
*
inter_height
;
T
union_area
=
area1
+
area2
-
inter_area
;
T
sim_score
=
inter_area
/
union_area
;
return
sim_score
;
}
template
<
typename
T
>
struct
IOUSimilarityFunctor
{
IOUSimilarityFunctor
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
cols
)
:
x_
(
x
),
y_
(
y
),
z_
(
z
),
cols_
(
static_cast
<
size_t
>
(
cols
))
{}
inline
HOSTDEVICE
void
operator
()(
size_t
row_id
)
const
{
T
x_min1
=
x_
[
row_id
*
4
];
T
y_min1
=
x_
[
row_id
*
4
+
1
];
T
x_max1
=
x_
[
row_id
*
4
+
2
];
T
y_max1
=
x_
[
row_id
*
4
+
3
];
for
(
size_t
i
=
0
;
i
<
cols_
;
++
i
)
{
T
x_min2
=
y_
[
i
*
4
];
T
y_min2
=
y_
[
i
*
4
+
1
];
T
x_max2
=
y_
[
i
*
4
+
2
];
T
y_max2
=
y_
[
i
*
4
+
3
];
T
sim
=
IOUSimilarity
(
x_min1
,
y_min1
,
x_max1
,
y_max1
,
x_min2
,
y_min2
,
x_max2
,
y_max2
);
z_
[
row_id
*
cols_
+
i
]
=
sim
;
}
}
const
T
*
x_
;
const
T
*
y_
;
T
*
z_
;
const
size_t
cols_
;
};
namespace
paddle
{
namespace
operators
{
template
<
typename
DeviceContext
,
typename
T
>
class
IOUSimilarityKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
const
framework
::
LoDTensor
*
in_x
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
const
framework
::
Tensor
*
in_y
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Y"
);
framework
::
LoDTensor
*
out
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
int
x_n
=
in_x
->
dims
()[
0
];
int
y_n
=
in_y
->
dims
()[
0
];
IOUSimilarityFunctor
<
T
>
functor
(
in_x
->
data
<
T
>
(),
in_y
->
data
<
T
>
(),
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
()),
y_n
);
platform
::
ForRange
<
DeviceContext
>
for_range
(
static_cast
<
const
DeviceContext
&>
(
ctx
.
device_context
()),
x_n
);
for_range
(
functor
);
}
};
// namespace operators
}
// namespace operators
}
// namespace paddle
python/paddle/v2/fluid/tests/test_iou_similarity_op.py
0 → 100755
浏览文件 @
d43932c8
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
import
sys
import
math
from
op_test
import
OpTest
class
TestIOUSimilarityOp
(
OpTest
):
def
test_check_output
(
self
):
self
.
check_output
()
def
setUp
(
self
):
self
.
op_type
=
"iou_similarity"
self
.
boxes1
=
np
.
array
(
[[
4.0
,
3.0
,
7.0
,
5.0
],
[
5.0
,
6.0
,
10.0
,
7.0
]]).
astype
(
'float32'
)
self
.
boxes2
=
np
.
array
([[
3.0
,
4.0
,
6.0
,
8.0
],
[
14.0
,
14.0
,
15.0
,
15.0
],
[
0.0
,
0.0
,
20.0
,
20.0
]]).
astype
(
'float32'
)
self
.
output
=
np
.
array
(
[[
2.0
/
16.0
,
0
,
6.0
/
400.0
],
[
1.0
/
16.0
,
0.0
,
5.0
/
400.0
]]).
astype
(
'float32'
)
self
.
inputs
=
{
'X'
:
self
.
boxes1
,
'Y'
:
self
.
boxes2
}
self
.
outputs
=
{
'Out'
:
self
.
output
}
class
TestIOUSimilarityOpWithLoD
(
TestIOUSimilarityOp
):
def
test_check_output
(
self
):
self
.
check_output
()
def
setUp
(
self
):
super
(
TestIOUSimilarityOpWithLoD
,
self
).
setUp
()
self
.
boxes1_lod
=
[[
0
,
1
,
2
]]
self
.
output_lod
=
[[
0
,
1
,
2
]]
self
.
inputs
=
{
'X'
:
(
self
.
boxes1
,
self
.
boxes1_lod
),
'Y'
:
self
.
boxes2
}
self
.
outputs
=
{
'Out'
:
(
self
.
output
,
self
.
output_lod
)}
if
__name__
==
'__main__'
:
unittest
.
main
()
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