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体验新版 GitCode,发现更多精彩内容 >>
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25de5bec
编写于
8月 17, 2021
作者:
M
MissPenguin
浏览文件
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update
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36152456
变更
3
隐藏空白更改
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并排
Showing
3 changed file
with
4 addition
and
62 deletion
+4
-62
deploy/cpp_infer/include/ocr_rec.h
deploy/cpp_infer/include/ocr_rec.h
+0
-3
deploy/cpp_infer/src/ocr_det.cpp
deploy/cpp_infer/src/ocr_det.cpp
+2
-2
deploy/cpp_infer/src/ocr_rec.cpp
deploy/cpp_infer/src/ocr_rec.cpp
+2
-57
未找到文件。
deploy/cpp_infer/include/ocr_rec.h
浏览文件 @
25de5bec
...
...
@@ -90,9 +90,6 @@ private:
// post-process
PostProcessor
post_processor_
;
cv
::
Mat
GetRotateCropImage
(
const
cv
::
Mat
&
srcimage
,
std
::
vector
<
std
::
vector
<
int
>>
box
);
};
// class CrnnRecognizer
}
// namespace PaddleOCR
deploy/cpp_infer/src/ocr_det.cpp
浏览文件 @
25de5bec
...
...
@@ -118,10 +118,10 @@ void DBDetector::Run(cv::Mat &img,
auto
preprocess_end
=
std
::
chrono
::
steady_clock
::
now
();
// Inference.
auto
inference_start
=
std
::
chrono
::
steady_clock
::
now
();
auto
input_names
=
this
->
predictor_
->
GetInputNames
();
auto
input_t
=
this
->
predictor_
->
GetInputHandle
(
input_names
[
0
]);
input_t
->
Reshape
({
1
,
3
,
resize_img
.
rows
,
resize_img
.
cols
});
auto
inference_start
=
std
::
chrono
::
steady_clock
::
now
();
input_t
->
CopyFromCpu
(
input
.
data
());
this
->
predictor_
->
Run
();
...
...
@@ -165,8 +165,8 @@ void DBDetector::Run(cv::Mat &img,
this
->
det_db_unclip_ratio_
,
this
->
use_polygon_score_
);
boxes
=
post_processor_
.
FilterTagDetRes
(
boxes
,
ratio_h
,
ratio_w
,
srcimg
);
std
::
cout
<<
"Detected boxes num: "
<<
boxes
.
size
()
<<
endl
;
auto
postprocess_end
=
std
::
chrono
::
steady_clock
::
now
();
std
::
cout
<<
"Detected boxes num: "
<<
boxes
.
size
()
<<
endl
;
std
::
chrono
::
duration
<
float
>
preprocess_diff
=
preprocess_end
-
preprocess_start
;
times
->
push_back
(
double
(
preprocess_diff
.
count
()
*
1000
));
...
...
deploy/cpp_infer/src/ocr_rec.cpp
浏览文件 @
25de5bec
...
...
@@ -34,10 +34,10 @@ void CRNNRecognizer::Run(cv::Mat &img, std::vector<double> *times) {
auto
preprocess_end
=
std
::
chrono
::
steady_clock
::
now
();
// Inference.
auto
inference_start
=
std
::
chrono
::
steady_clock
::
now
();
auto
input_names
=
this
->
predictor_
->
GetInputNames
();
auto
input_t
=
this
->
predictor_
->
GetInputHandle
(
input_names
[
0
]);
input_t
->
Reshape
({
1
,
3
,
resize_img
.
rows
,
resize_img
.
cols
});
auto
inference_start
=
std
::
chrono
::
steady_clock
::
now
();
input_t
->
CopyFromCpu
(
input
.
data
());
this
->
predictor_
->
Run
();
...
...
@@ -77,12 +77,12 @@ void CRNNRecognizer::Run(cv::Mat &img, std::vector<double> *times) {
}
last_index
=
argmax_idx
;
}
auto
postprocess_end
=
std
::
chrono
::
steady_clock
::
now
();
score
/=
count
;
for
(
int
i
=
0
;
i
<
str_res
.
size
();
i
++
)
{
std
::
cout
<<
str_res
[
i
];
}
std
::
cout
<<
"
\t
score: "
<<
score
<<
std
::
endl
;
auto
postprocess_end
=
std
::
chrono
::
steady_clock
::
now
();
std
::
chrono
::
duration
<
float
>
preprocess_diff
=
preprocess_end
-
preprocess_start
;
times
->
push_back
(
double
(
preprocess_diff
.
count
()
*
1000
));
...
...
@@ -144,59 +144,4 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
this
->
predictor_
=
CreatePredictor
(
config
);
}
cv
::
Mat
CRNNRecognizer
::
GetRotateCropImage
(
const
cv
::
Mat
&
srcimage
,
std
::
vector
<
std
::
vector
<
int
>>
box
)
{
cv
::
Mat
image
;
srcimage
.
copyTo
(
image
);
std
::
vector
<
std
::
vector
<
int
>>
points
=
box
;
int
x_collect
[
4
]
=
{
box
[
0
][
0
],
box
[
1
][
0
],
box
[
2
][
0
],
box
[
3
][
0
]};
int
y_collect
[
4
]
=
{
box
[
0
][
1
],
box
[
1
][
1
],
box
[
2
][
1
],
box
[
3
][
1
]};
int
left
=
int
(
*
std
::
min_element
(
x_collect
,
x_collect
+
4
));
int
right
=
int
(
*
std
::
max_element
(
x_collect
,
x_collect
+
4
));
int
top
=
int
(
*
std
::
min_element
(
y_collect
,
y_collect
+
4
));
int
bottom
=
int
(
*
std
::
max_element
(
y_collect
,
y_collect
+
4
));
cv
::
Mat
img_crop
;
image
(
cv
::
Rect
(
left
,
top
,
right
-
left
,
bottom
-
top
)).
copyTo
(
img_crop
);
for
(
int
i
=
0
;
i
<
points
.
size
();
i
++
)
{
points
[
i
][
0
]
-=
left
;
points
[
i
][
1
]
-=
top
;
}
int
img_crop_width
=
int
(
sqrt
(
pow
(
points
[
0
][
0
]
-
points
[
1
][
0
],
2
)
+
pow
(
points
[
0
][
1
]
-
points
[
1
][
1
],
2
)));
int
img_crop_height
=
int
(
sqrt
(
pow
(
points
[
0
][
0
]
-
points
[
3
][
0
],
2
)
+
pow
(
points
[
0
][
1
]
-
points
[
3
][
1
],
2
)));
cv
::
Point2f
pts_std
[
4
];
pts_std
[
0
]
=
cv
::
Point2f
(
0.
,
0.
);
pts_std
[
1
]
=
cv
::
Point2f
(
img_crop_width
,
0.
);
pts_std
[
2
]
=
cv
::
Point2f
(
img_crop_width
,
img_crop_height
);
pts_std
[
3
]
=
cv
::
Point2f
(
0.
f
,
img_crop_height
);
cv
::
Point2f
pointsf
[
4
];
pointsf
[
0
]
=
cv
::
Point2f
(
points
[
0
][
0
],
points
[
0
][
1
]);
pointsf
[
1
]
=
cv
::
Point2f
(
points
[
1
][
0
],
points
[
1
][
1
]);
pointsf
[
2
]
=
cv
::
Point2f
(
points
[
2
][
0
],
points
[
2
][
1
]);
pointsf
[
3
]
=
cv
::
Point2f
(
points
[
3
][
0
],
points
[
3
][
1
]);
cv
::
Mat
M
=
cv
::
getPerspectiveTransform
(
pointsf
,
pts_std
);
cv
::
Mat
dst_img
;
cv
::
warpPerspective
(
img_crop
,
dst_img
,
M
,
cv
::
Size
(
img_crop_width
,
img_crop_height
),
cv
::
BORDER_REPLICATE
);
if
(
float
(
dst_img
.
rows
)
>=
float
(
dst_img
.
cols
)
*
1.5
)
{
cv
::
Mat
srcCopy
=
cv
::
Mat
(
dst_img
.
rows
,
dst_img
.
cols
,
dst_img
.
depth
());
cv
::
transpose
(
dst_img
,
srcCopy
);
cv
::
flip
(
srcCopy
,
srcCopy
,
0
);
return
srcCopy
;
}
else
{
return
dst_img
;
}
}
}
// namespace PaddleOCR
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