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体验新版 GitCode,发现更多精彩内容 >>
提交
db8ff57a
编写于
12月 17, 2018
作者:
D
dengkaipeng
浏览文件
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浏览文件
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电子邮件补丁
差异文件
remove useless code and update doc. test=develop
上级
577a92d9
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
45 addition
and
69 deletion
+45
-69
paddle/fluid/operators/yolov3_loss_op.cc
paddle/fluid/operators/yolov3_loss_op.cc
+17
-15
paddle/fluid/operators/yolov3_loss_op.h
paddle/fluid/operators/yolov3_loss_op.h
+28
-36
python/paddle/fluid/layers/detection.py
python/paddle/fluid/layers/detection.py
+0
-13
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
+0
-5
未找到文件。
paddle/fluid/operators/yolov3_loss_op.cc
浏览文件 @
db8ff57a
...
...
@@ -138,17 +138,23 @@ class Yolov3LossOpMaker : public framework::OpProtoAndCheckerMaker {
thresh, the confidence score loss of this anchor box will be ignored.
Therefore, the yolov3 loss consist of three major parts, box location loss,
confidence score loss, and classification loss. The MSE loss is used for
box location, and binary cross entropy loss is used for confidence score
loss and classification loss.
confidence score loss, and classification loss. The L1 loss is used for
box coordinates (w, h), and sigmoid cross entropy loss is used for box
coordinates (x, y), confidence score loss and classification loss.
In order to trade off box coordinate losses between big boxes and small
boxes, box coordinate losses will be mutiplied by scale weight, which is
calculated as follow.
$$
weight_{box} = 2.0 - t_w * t_h
$$
Final loss will be represented as follow.
$$
loss = \loss_weight_{xy} * loss_{xy} + \loss_weight_{wh} * loss_{wh}
+ \loss_weight_{conf_target} * loss_{conf_target}
+ \loss_weight_{conf_notarget} * loss_{conf_notarget}
+ \loss_weight_{class} * loss_{class}
loss = (loss_{xy} + loss_{wh}) * weight_{box}
+ loss_{conf} + loss_{class}
$$
)DOC"
);
}
...
...
@@ -204,11 +210,7 @@ namespace ops = paddle::operators;
REGISTER_OPERATOR
(
yolov3_loss
,
ops
::
Yolov3LossOp
,
ops
::
Yolov3LossOpMaker
,
ops
::
Yolov3LossGradMaker
);
REGISTER_OPERATOR
(
yolov3_loss_grad
,
ops
::
Yolov3LossOpGrad
);
REGISTER_OP_CPU_KERNEL
(
yolov3_loss
,
ops
::
Yolov3LossKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
Yolov3LossKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
yolov3_loss_grad
,
ops
::
Yolov3LossGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
Yolov3LossGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
yolov3_loss
,
ops
::
Yolov3LossKernel
<
float
>
,
ops
::
Yolov3LossKernel
<
double
>
);
REGISTER_OP_CPU_KERNEL
(
yolov3_loss_grad
,
ops
::
Yolov3LossGradKernel
<
float
>
,
ops
::
Yolov3LossGradKernel
<
double
>
);
paddle/fluid/operators/yolov3_loss_op.h
浏览文件 @
db8ff57a
...
...
@@ -260,26 +260,18 @@ static void CalcYolov3Loss(T* loss_data, const Tensor& input, const Tensor& tx,
const
int
class_num
=
tclass
.
dims
()[
4
];
const
int
grid_num
=
h
*
w
;
// T l = 0.0;
CalcSCE
<
T
>
(
loss_data
,
input_data
,
tx_data
,
tweight_data
,
obj_mask_data
,
n
,
an_num
,
grid_num
,
class_num
,
1
);
CalcSCE
<
T
>
(
loss_data
,
input_data
+
grid_num
,
ty_data
,
tweight_data
,
obj_mask_data
,
n
,
an_num
,
grid_num
,
class_num
,
1
);
// LOG(ERROR) << "C++ xy: " << loss_data[0] - l;
// l = loss_data[0];
CalcL1Loss
<
T
>
(
loss_data
,
input_data
+
2
*
grid_num
,
tw_data
,
tweight_data
,
obj_mask_data
,
n
,
an_num
,
grid_num
,
class_num
);
CalcL1Loss
<
T
>
(
loss_data
,
input_data
+
3
*
grid_num
,
th_data
,
tweight_data
,
obj_mask_data
,
n
,
an_num
,
grid_num
,
class_num
);
// LOG(ERROR) << "C++ wh: " << loss_data[0] - l;
// l = loss_data[0];
CalcSCE
<
T
>
(
loss_data
,
input_data
+
4
*
grid_num
,
tconf_data
,
conf_mask_data
,
conf_mask_data
,
n
,
an_num
,
grid_num
,
class_num
,
1
);
// LOG(ERROR) << "C++ conf: " << loss_data[0] - l;
// l = loss_data[0];
CalcSCE
<
T
>
(
loss_data
,
input_data
+
5
*
grid_num
,
tclass_data
,
obj_mask_data
,
obj_mask_data
,
n
,
an_num
,
grid_num
,
class_num
,
class_num
);
// LOG(ERROR) << "C++ class: " << loss_data[0] - l;
}
template
<
typename
T
>
...
...
@@ -329,7 +321,7 @@ static void CalcYolov3LossGrad(T* input_grad_data, const Tensor& loss_grad,
obj_mask_data
,
n
,
an_num
,
grid_num
,
class_num
,
class_num
);
}
template
<
typename
DeviceContext
,
typename
T
>
template
<
typename
T
>
class
Yolov3LossKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
...
...
@@ -359,24 +351,24 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
tconf
.
mutable_data
<
T
>
({
n
,
an_num
,
h
,
w
},
ctx
.
GetPlace
());
tclass
.
mutable_data
<
T
>
({
n
,
an_num
,
h
,
w
,
class_num
},
ctx
.
GetPlace
());
math
::
SetConstant
<
DeviceContext
,
T
>
constant
;
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
conf_mask
,
static_cast
<
T
>
(
1.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
obj_mask
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tx
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
ty
,
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
constant
;
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
conf_mask
,
static_cast
<
T
>
(
1.0
));
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
obj_mask
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tx
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tw
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
ty
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
th
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tw
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tweight
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
th
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tconf
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tweight
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tconf
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tclass
,
constant
(
ctx
.
template
device_context
<
platform
::
CPU
DeviceContext
>(),
&
tclass
,
static_cast
<
T
>
(
0.0
));
PreProcessGTBox
<
T
>
(
*
gt_box
,
*
gt_label
,
ignore_thresh
,
anchors
,
input_size
,
...
...
@@ -390,7 +382,7 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
}
};
template
<
typename
DeviceContext
,
typename
T
>
template
<
typename
T
>
class
Yolov3LossGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
...
...
@@ -422,24 +414,24 @@ class Yolov3LossGradKernel : public framework::OpKernel<T> {
tconf
.
mutable_data
<
T
>
({
n
,
an_num
,
h
,
w
},
ctx
.
GetPlace
());
tclass
.
mutable_data
<
T
>
({
n
,
an_num
,
h
,
w
,
class_num
},
ctx
.
GetPlace
());
math
::
SetConstant
<
DeviceContext
,
T
>
constant
;
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
conf_mask
,
static_cast
<
T
>
(
1.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
obj_mask
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tx
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
ty
,
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
constant
;
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
conf_mask
,
static_cast
<
T
>
(
1.0
));
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
obj_mask
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tx
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tw
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
ty
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
th
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tw
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tweight
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
th
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tconf
,
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tweight
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
tconf
,
static_cast
<
T
>
(
0.0
));
constant
(
ctx
.
template
device_context
<
DeviceContext
>(),
&
tclass
,
constant
(
ctx
.
template
device_context
<
platform
::
CPU
DeviceContext
>(),
&
tclass
,
static_cast
<
T
>
(
0.0
));
PreProcessGTBox
<
T
>
(
*
gt_box
,
*
gt_label
,
ignore_thresh
,
anchors
,
input_size
,
...
...
python/paddle/fluid/layers/detection.py
浏览文件 @
db8ff57a
...
...
@@ -485,19 +485,6 @@ def yolov3_loss(x,
"input_size"
:
input_size
,
}
# if loss_weight_xy is not None and isinstance(loss_weight_xy, float):
# self.attrs['loss_weight_xy'] = loss_weight_xy
# if loss_weight_wh is not None and isinstance(loss_weight_wh, float):
# self.attrs['loss_weight_wh'] = loss_weight_wh
# if loss_weight_conf_target is not None and isinstance(
# loss_weight_conf_target, float):
# self.attrs['loss_weight_conf_target'] = loss_weight_conf_target
# if loss_weight_conf_notarget is not None and isinstance(
# loss_weight_conf_notarget, float):
# self.attrs['loss_weight_conf_notarget'] = loss_weight_conf_notarget
# if loss_weight_class is not None and isinstance(loss_weight_class, float):
# self.attrs['loss_weight_class'] = loss_weight_class
helper
.
append_op
(
type
=
'yolov3_loss'
,
inputs
=
{
"X"
:
x
,
...
...
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
浏览文件 @
db8ff57a
...
...
@@ -157,11 +157,6 @@ def YoloV3Loss(x, gtbox, gtlabel, attrs):
loss_obj
=
sce
(
pred_conf
,
tconf
,
conf_mask
)
loss_class
=
sce
(
pred_cls
,
tcls
,
obj_mask_expand
)
# print("python loss_xy: ", loss_x + loss_y)
# print("python loss_wh: ", loss_w + loss_h)
# print("python loss_obj: ", loss_obj)
# print("python loss_class: ", loss_class)
return
loss_x
+
loss_y
+
loss_w
+
loss_h
+
loss_obj
+
loss_class
...
...
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