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6f64faea
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PaddleOCR
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体验新版 GitCode,发现更多精彩内容 >>
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6f64faea
编写于
6月 28, 2021
作者:
D
Double_V
提交者:
GitHub
6月 28, 2021
浏览文件
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浏览文件
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差异文件
Merge pull request #3069 from LDOUBLEV/bm_dyg
fix save_log_path as null
上级
bc999986
465ef3bf
变更
4
显示空白变更内容
内联
并排
Showing
4 changed file
with
12 addition
and
37 deletion
+12
-37
ppocr/modeling/transforms/tps.py
ppocr/modeling/transforms/tps.py
+2
-9
tools/infer/predict_det.py
tools/infer/predict_det.py
+1
-0
tools/infer/predict_rec.py
tools/infer/predict_rec.py
+2
-1
tools/infer/utility.py
tools/infer/utility.py
+7
-27
未找到文件。
ppocr/modeling/transforms/tps.py
浏览文件 @
6f64faea
...
@@ -230,15 +230,8 @@ class GridGenerator(nn.Layer):
...
@@ -230,15 +230,8 @@ class GridGenerator(nn.Layer):
def
build_inv_delta_C_paddle
(
self
,
C
):
def
build_inv_delta_C_paddle
(
self
,
C
):
""" Return inv_delta_C which is needed to calculate T """
""" Return inv_delta_C which is needed to calculate T """
F
=
self
.
F
F
=
self
.
F
hat_C
=
paddle
.
zeros
((
F
,
F
),
dtype
=
'float64'
)
# F x F
hat_eye
=
paddle
.
eye
(
F
,
dtype
=
'float64'
)
# F x F
for
i
in
range
(
0
,
F
):
hat_C
=
paddle
.
norm
(
C
.
reshape
([
1
,
F
,
2
])
-
C
.
reshape
([
F
,
1
,
2
]),
axis
=
2
)
+
hat_eye
for
j
in
range
(
i
,
F
):
if
i
==
j
:
hat_C
[
i
,
j
]
=
1
else
:
r
=
paddle
.
norm
(
C
[
i
]
-
C
[
j
])
hat_C
[
i
,
j
]
=
r
hat_C
[
j
,
i
]
=
r
hat_C
=
(
hat_C
**
2
)
*
paddle
.
log
(
hat_C
)
hat_C
=
(
hat_C
**
2
)
*
paddle
.
log
(
hat_C
)
delta_C
=
paddle
.
concat
(
# F+3 x F+3
delta_C
=
paddle
.
concat
(
# F+3 x F+3
[
[
...
...
tools/infer/predict_det.py
浏览文件 @
6f64faea
...
@@ -237,3 +237,4 @@ if __name__ == "__main__":
...
@@ -237,3 +237,4 @@ if __name__ == "__main__":
"det_res_{}"
.
format
(
img_name_pure
))
"det_res_{}"
.
format
(
img_name_pure
))
cv2
.
imwrite
(
img_path
,
src_im
)
cv2
.
imwrite
(
img_path
,
src_im
)
logger
.
info
(
"The visualized image saved in {}"
.
format
(
img_path
))
logger
.
info
(
"The visualized image saved in {}"
.
format
(
img_path
))
tools/infer/predict_rec.py
浏览文件 @
6f64faea
...
@@ -322,7 +322,8 @@ def main(args):
...
@@ -322,7 +322,8 @@ def main(args):
'total_time_s'
:
rec_time_dict
[
'total_time'
]
'total_time_s'
:
rec_time_dict
[
'total_time'
]
}
}
benchmark_log
=
benchmark_utils
.
PaddleInferBenchmark
(
benchmark_log
=
benchmark_utils
.
PaddleInferBenchmark
(
text_recognizer
.
config
,
model_info
,
data_info
,
perf_info
,
mems
)
text_recognizer
.
config
,
model_info
,
data_info
,
perf_info
,
mems
,
args
.
save_log_path
)
benchmark_log
(
"Rec"
)
benchmark_log
(
"Rec"
)
...
...
tools/infer/utility.py
浏览文件 @
6f64faea
...
@@ -37,6 +37,7 @@ def init_args():
...
@@ -37,6 +37,7 @@ def init_args():
parser
.
add_argument
(
"--use_gpu"
,
type
=
str2bool
,
default
=
True
)
parser
.
add_argument
(
"--use_gpu"
,
type
=
str2bool
,
default
=
True
)
parser
.
add_argument
(
"--ir_optim"
,
type
=
str2bool
,
default
=
True
)
parser
.
add_argument
(
"--ir_optim"
,
type
=
str2bool
,
default
=
True
)
parser
.
add_argument
(
"--use_tensorrt"
,
type
=
str2bool
,
default
=
False
)
parser
.
add_argument
(
"--use_tensorrt"
,
type
=
str2bool
,
default
=
False
)
parser
.
add_argument
(
"--min_subgraph_size"
,
type
=
int
,
default
=
3
)
parser
.
add_argument
(
"--precision"
,
type
=
str
,
default
=
"fp32"
)
parser
.
add_argument
(
"--precision"
,
type
=
str
,
default
=
"fp32"
)
parser
.
add_argument
(
"--gpu_mem"
,
type
=
int
,
default
=
500
)
parser
.
add_argument
(
"--gpu_mem"
,
type
=
int
,
default
=
500
)
...
@@ -236,12 +237,14 @@ def create_predictor(args, mode, logger):
...
@@ -236,12 +237,14 @@ def create_predictor(args, mode, logger):
config
.
enable_tensorrt_engine
(
config
.
enable_tensorrt_engine
(
precision_mode
=
inference
.
PrecisionType
.
Float32
,
precision_mode
=
inference
.
PrecisionType
.
Float32
,
max_batch_size
=
args
.
max_batch_size
,
max_batch_size
=
args
.
max_batch_size
,
min_subgraph_size
=
3
)
# skip the minmum trt subgraph
min_subgraph_size
=
args
.
min_subgraph_size
)
if
mode
==
"det"
and
"mobile"
in
model_file_path
:
# skip the minmum trt subgraph
if
mode
==
"det"
:
min_input_shape
=
{
min_input_shape
=
{
"x"
:
[
1
,
3
,
50
,
50
],
"x"
:
[
1
,
3
,
50
,
50
],
"conv2d_92.tmp_0"
:
[
1
,
96
,
20
,
20
],
"conv2d_92.tmp_0"
:
[
1
,
96
,
20
,
20
],
"conv2d_91.tmp_0"
:
[
1
,
96
,
10
,
10
],
"conv2d_91.tmp_0"
:
[
1
,
96
,
10
,
10
],
"conv2d_59.tmp_0"
:
[
1
,
96
,
20
,
20
],
"nearest_interp_v2_1.tmp_0"
:
[
1
,
96
,
10
,
10
],
"nearest_interp_v2_1.tmp_0"
:
[
1
,
96
,
10
,
10
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
20
,
20
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
20
,
20
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
20
,
20
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
20
,
20
],
...
@@ -254,6 +257,7 @@ def create_predictor(args, mode, logger):
...
@@ -254,6 +257,7 @@ def create_predictor(args, mode, logger):
"x"
:
[
1
,
3
,
2000
,
2000
],
"x"
:
[
1
,
3
,
2000
,
2000
],
"conv2d_92.tmp_0"
:
[
1
,
96
,
400
,
400
],
"conv2d_92.tmp_0"
:
[
1
,
96
,
400
,
400
],
"conv2d_91.tmp_0"
:
[
1
,
96
,
200
,
200
],
"conv2d_91.tmp_0"
:
[
1
,
96
,
200
,
200
],
"conv2d_59.tmp_0"
:
[
1
,
96
,
400
,
400
],
"nearest_interp_v2_1.tmp_0"
:
[
1
,
96
,
200
,
200
],
"nearest_interp_v2_1.tmp_0"
:
[
1
,
96
,
200
,
200
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
400
,
400
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
400
,
400
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
400
,
400
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
400
,
400
],
...
@@ -266,6 +270,7 @@ def create_predictor(args, mode, logger):
...
@@ -266,6 +270,7 @@ def create_predictor(args, mode, logger):
"x"
:
[
1
,
3
,
640
,
640
],
"x"
:
[
1
,
3
,
640
,
640
],
"conv2d_92.tmp_0"
:
[
1
,
96
,
160
,
160
],
"conv2d_92.tmp_0"
:
[
1
,
96
,
160
,
160
],
"conv2d_91.tmp_0"
:
[
1
,
96
,
80
,
80
],
"conv2d_91.tmp_0"
:
[
1
,
96
,
80
,
80
],
"conv2d_59.tmp_0"
:
[
1
,
96
,
160
,
160
],
"nearest_interp_v2_1.tmp_0"
:
[
1
,
96
,
80
,
80
],
"nearest_interp_v2_1.tmp_0"
:
[
1
,
96
,
80
,
80
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
160
,
160
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
160
,
160
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
160
,
160
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
160
,
160
],
...
@@ -274,31 +279,6 @@ def create_predictor(args, mode, logger):
...
@@ -274,31 +279,6 @@ def create_predictor(args, mode, logger):
"elementwise_add_7"
:
[
1
,
56
,
40
,
40
],
"elementwise_add_7"
:
[
1
,
56
,
40
,
40
],
"nearest_interp_v2_0.tmp_0"
:
[
1
,
96
,
40
,
40
]
"nearest_interp_v2_0.tmp_0"
:
[
1
,
96
,
40
,
40
]
}
}
if
mode
==
"det"
and
"server"
in
model_file_path
:
min_input_shape
=
{
"x"
:
[
1
,
3
,
50
,
50
],
"conv2d_59.tmp_0"
:
[
1
,
96
,
20
,
20
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
20
,
20
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
20
,
20
],
"nearest_interp_v2_4.tmp_0"
:
[
1
,
24
,
20
,
20
],
"nearest_interp_v2_5.tmp_0"
:
[
1
,
24
,
20
,
20
]
}
max_input_shape
=
{
"x"
:
[
1
,
3
,
2000
,
2000
],
"conv2d_59.tmp_0"
:
[
1
,
96
,
400
,
400
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
400
,
400
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
400
,
400
],
"nearest_interp_v2_4.tmp_0"
:
[
1
,
24
,
400
,
400
],
"nearest_interp_v2_5.tmp_0"
:
[
1
,
24
,
400
,
400
]
}
opt_input_shape
=
{
"x"
:
[
1
,
3
,
640
,
640
],
"conv2d_59.tmp_0"
:
[
1
,
96
,
160
,
160
],
"nearest_interp_v2_2.tmp_0"
:
[
1
,
96
,
160
,
160
],
"nearest_interp_v2_3.tmp_0"
:
[
1
,
24
,
160
,
160
],
"nearest_interp_v2_4.tmp_0"
:
[
1
,
24
,
160
,
160
],
"nearest_interp_v2_5.tmp_0"
:
[
1
,
24
,
160
,
160
]
}
elif
mode
==
"rec"
:
elif
mode
==
"rec"
:
min_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
32
,
10
]}
min_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
32
,
10
]}
max_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
32
,
2000
]}
max_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
32
,
2000
]}
...
...
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