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体验新版 GitCode,发现更多精彩内容 >>
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e45ff483
编写于
6月 06, 2021
作者:
littletomatodonkey
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
remove fpn name
上级
48d85379
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
13 addition
and
32 deletion
+13
-32
ppocr/modeling/heads/det_db_head.py
ppocr/modeling/heads/det_db_head.py
+5
-16
ppocr/modeling/necks/db_fpn.py
ppocr/modeling/necks/db_fpn.py
+8
-16
未找到文件。
ppocr/modeling/heads/det_db_head.py
浏览文件 @
e45ff483
...
...
@@ -23,10 +23,10 @@ import paddle.nn.functional as F
from
paddle
import
ParamAttr
def
get_bias_attr
(
k
,
name
):
def
get_bias_attr
(
k
):
stdv
=
1.0
/
math
.
sqrt
(
k
*
1.0
)
initializer
=
paddle
.
nn
.
initializer
.
Uniform
(
-
stdv
,
stdv
)
bias_attr
=
ParamAttr
(
initializer
=
initializer
,
name
=
name
+
"_b_attr"
)
bias_attr
=
ParamAttr
(
initializer
=
initializer
)
return
bias_attr
...
...
@@ -38,18 +38,14 @@ class Head(nn.Layer):
out_channels
=
in_channels
//
4
,
kernel_size
=
3
,
padding
=
1
,
weight_attr
=
ParamAttr
(
name
=
name_list
[
0
]
+
'.w_0'
),
weight_attr
=
ParamAttr
(),
bias_attr
=
False
)
self
.
conv_bn1
=
nn
.
BatchNorm
(
num_channels
=
in_channels
//
4
,
param_attr
=
ParamAttr
(
name
=
name_list
[
1
]
+
'.w_0'
,
initializer
=
paddle
.
nn
.
initializer
.
Constant
(
value
=
1.0
)),
bias_attr
=
ParamAttr
(
name
=
name_list
[
1
]
+
'.b_0'
,
initializer
=
paddle
.
nn
.
initializer
.
Constant
(
value
=
1e-4
)),
moving_mean_name
=
name_list
[
1
]
+
'.w_1'
,
moving_variance_name
=
name_list
[
1
]
+
'.w_2'
,
act
=
'relu'
)
self
.
conv2
=
nn
.
Conv2DTranspose
(
in_channels
=
in_channels
//
4
,
...
...
@@ -57,19 +53,14 @@ class Head(nn.Layer):
kernel_size
=
2
,
stride
=
2
,
weight_attr
=
ParamAttr
(
name
=
name_list
[
2
]
+
'.w_0'
,
initializer
=
paddle
.
nn
.
initializer
.
KaimingUniform
()),
bias_attr
=
get_bias_attr
(
in_channels
//
4
,
name_list
[
-
1
]
+
"conv2"
))
bias_attr
=
get_bias_attr
(
in_channels
//
4
))
self
.
conv_bn2
=
nn
.
BatchNorm
(
num_channels
=
in_channels
//
4
,
param_attr
=
ParamAttr
(
name
=
name_list
[
3
]
+
'.w_0'
,
initializer
=
paddle
.
nn
.
initializer
.
Constant
(
value
=
1.0
)),
bias_attr
=
ParamAttr
(
name
=
name_list
[
3
]
+
'.b_0'
,
initializer
=
paddle
.
nn
.
initializer
.
Constant
(
value
=
1e-4
)),
moving_mean_name
=
name_list
[
3
]
+
'.w_1'
,
moving_variance_name
=
name_list
[
3
]
+
'.w_2'
,
act
=
"relu"
)
self
.
conv3
=
nn
.
Conv2DTranspose
(
in_channels
=
in_channels
//
4
,
...
...
@@ -77,10 +68,8 @@ class Head(nn.Layer):
kernel_size
=
2
,
stride
=
2
,
weight_attr
=
ParamAttr
(
name
=
name_list
[
4
]
+
'.w_0'
,
initializer
=
paddle
.
nn
.
initializer
.
KaimingUniform
()),
bias_attr
=
get_bias_attr
(
in_channels
//
4
,
name_list
[
-
1
]
+
"conv3"
),
)
bias_attr
=
get_bias_attr
(
in_channels
//
4
),
)
def
forward
(
self
,
x
):
x
=
self
.
conv1
(
x
)
...
...
ppocr/modeling/necks/db_fpn.py
浏览文件 @
e45ff483
...
...
@@ -32,61 +32,53 @@ class DBFPN(nn.Layer):
in_channels
=
in_channels
[
0
],
out_channels
=
self
.
out_channels
,
kernel_size
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_51.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
in3_conv
=
nn
.
Conv2D
(
in_channels
=
in_channels
[
1
],
out_channels
=
self
.
out_channels
,
kernel_size
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_50.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
in4_conv
=
nn
.
Conv2D
(
in_channels
=
in_channels
[
2
],
out_channels
=
self
.
out_channels
,
kernel_size
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_49.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
in5_conv
=
nn
.
Conv2D
(
in_channels
=
in_channels
[
3
],
out_channels
=
self
.
out_channels
,
kernel_size
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_48.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
p5_conv
=
nn
.
Conv2D
(
in_channels
=
self
.
out_channels
,
out_channels
=
self
.
out_channels
//
4
,
kernel_size
=
3
,
padding
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_52.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
p4_conv
=
nn
.
Conv2D
(
in_channels
=
self
.
out_channels
,
out_channels
=
self
.
out_channels
//
4
,
kernel_size
=
3
,
padding
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_53.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
p3_conv
=
nn
.
Conv2D
(
in_channels
=
self
.
out_channels
,
out_channels
=
self
.
out_channels
//
4
,
kernel_size
=
3
,
padding
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_54.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
self
.
p2_conv
=
nn
.
Conv2D
(
in_channels
=
self
.
out_channels
,
out_channels
=
self
.
out_channels
//
4
,
kernel_size
=
3
,
padding
=
1
,
weight_attr
=
ParamAttr
(
name
=
'conv2d_55.w_0'
,
initializer
=
weight_attr
),
weight_attr
=
ParamAttr
(
initializer
=
weight_attr
),
bias_attr
=
False
)
def
forward
(
self
,
x
):
...
...
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