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3e11efa7
编写于
7月 27, 2021
作者:
L
LDOUBLEV
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix mem leak
上级
6887f457
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
13 addition
and
22 deletion
+13
-22
ppocr/data/simple_dataset.py
ppocr/data/simple_dataset.py
+12
-21
ppocr/modeling/architectures/distillation_model.py
ppocr/modeling/architectures/distillation_model.py
+1
-1
未找到文件。
ppocr/data/simple_dataset.py
浏览文件 @
3e11efa7
...
@@ -14,7 +14,6 @@
...
@@ -14,7 +14,6 @@
import
numpy
as
np
import
numpy
as
np
import
os
import
os
import
random
import
random
import
traceback
from
paddle.io
import
Dataset
from
paddle.io
import
Dataset
from
.imaug
import
transform
,
create_operators
from
.imaug
import
transform
,
create_operators
...
@@ -46,7 +45,6 @@ class SimpleDataSet(Dataset):
...
@@ -46,7 +45,6 @@ class SimpleDataSet(Dataset):
self
.
seed
=
seed
self
.
seed
=
seed
logger
.
info
(
"Initialize indexs of datasets:%s"
%
label_file_list
)
logger
.
info
(
"Initialize indexs of datasets:%s"
%
label_file_list
)
self
.
data_lines
=
self
.
get_image_info_list
(
label_file_list
,
ratio_list
)
self
.
data_lines
=
self
.
get_image_info_list
(
label_file_list
,
ratio_list
)
self
.
check_data
()
self
.
data_idx_order_list
=
list
(
range
(
len
(
self
.
data_lines
)))
self
.
data_idx_order_list
=
list
(
range
(
len
(
self
.
data_lines
)))
if
self
.
mode
==
"train"
and
self
.
do_shuffle
:
if
self
.
mode
==
"train"
and
self
.
do_shuffle
:
self
.
shuffle_data_random
()
self
.
shuffle_data_random
()
...
@@ -103,18 +101,25 @@ class SimpleDataSet(Dataset):
...
@@ -103,18 +101,25 @@ class SimpleDataSet(Dataset):
def
__getitem__
(
self
,
idx
):
def
__getitem__
(
self
,
idx
):
file_idx
=
self
.
data_idx_order_list
[
idx
]
file_idx
=
self
.
data_idx_order_list
[
idx
]
data
=
self
.
data_lines
[
file_idx
]
data
_line
=
self
.
data_lines
[
file_idx
]
try
:
try
:
data_line
=
data_line
.
decode
(
'utf-8'
)
substr
=
data_line
.
strip
(
"
\n
"
).
split
(
self
.
delimiter
)
file_name
=
substr
[
0
]
label
=
substr
[
1
]
img_path
=
os
.
path
.
join
(
self
.
data_dir
,
file_name
)
data
=
{
'img_path'
:
img_path
,
'label'
:
label
}
if
not
os
.
path
.
exists
(
img_path
):
raise
Exception
(
"{} does not exist!"
.
format
(
img_path
))
with
open
(
data
[
'img_path'
],
'rb'
)
as
f
:
with
open
(
data
[
'img_path'
],
'rb'
)
as
f
:
img
=
f
.
read
()
img
=
f
.
read
()
data
[
'image'
]
=
img
data
[
'image'
]
=
img
data
[
'ext_data'
]
=
self
.
get_ext_data
()
data
[
'ext_data'
]
=
self
.
get_ext_data
()
outs
=
transform
(
data
,
self
.
ops
)
outs
=
transform
(
data
,
self
.
ops
)
except
:
except
Exception
as
e
:
error_meg
=
traceback
.
format_exc
()
self
.
logger
.
error
(
self
.
logger
.
error
(
"When parsing
file {} and label
{}, error happened with msg: {}"
.
format
(
"When parsing
line
{}, error happened with msg: {}"
.
format
(
data
[
'img_path'
],
data
[
'label'
],
error_meg
))
data
_line
,
e
))
outs
=
None
outs
=
None
if
outs
is
None
:
if
outs
is
None
:
# during evaluation, we should fix the idx to get same results for many times of evaluation.
# during evaluation, we should fix the idx to get same results for many times of evaluation.
...
@@ -125,17 +130,3 @@ class SimpleDataSet(Dataset):
...
@@ -125,17 +130,3 @@ class SimpleDataSet(Dataset):
def
__len__
(
self
):
def
__len__
(
self
):
return
len
(
self
.
data_idx_order_list
)
return
len
(
self
.
data_idx_order_list
)
def
check_data
(
self
):
new_data_lines
=
[]
for
data_line
in
self
.
data_lines
:
data_line
=
data_line
.
decode
(
'utf-8'
)
substr
=
data_line
.
strip
(
"
\n
"
).
strip
(
"
\r
"
).
split
(
self
.
delimiter
)
file_name
=
substr
[
0
]
label
=
substr
[
1
]
img_path
=
os
.
path
.
join
(
self
.
data_dir
,
file_name
)
if
os
.
path
.
exists
(
img_path
):
new_data_lines
.
append
({
'img_path'
:
img_path
,
'label'
:
label
})
else
:
self
.
logger
.
info
(
"{} does not exist!"
.
format
(
img_path
))
self
.
data_lines
=
new_data_lines
\ No newline at end of file
ppocr/modeling/architectures/distillation_model.py
浏览文件 @
3e11efa7
...
@@ -46,7 +46,7 @@ class DistillationModel(nn.Layer):
...
@@ -46,7 +46,7 @@ class DistillationModel(nn.Layer):
pretrained
=
model_config
.
pop
(
"pretrained"
)
pretrained
=
model_config
.
pop
(
"pretrained"
)
model
=
BaseModel
(
model_config
)
model
=
BaseModel
(
model_config
)
if
pretrained
is
not
None
:
if
pretrained
is
not
None
:
model
=
load_pretrained_params
(
model
,
pretrained
)
load_pretrained_params
(
model
,
pretrained
)
if
freeze_params
:
if
freeze_params
:
for
param
in
model
.
parameters
():
for
param
in
model
.
parameters
():
param
.
trainable
=
False
param
.
trainable
=
False
...
...
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