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submodule
opencv
Commits
838842cc
Commit
838842cc
authored
Oct 03, 2012
by
marina.kolpakova
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Add performance detection test in ROI; refactored soft cascade performance tests
parent
dd595376
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185 additions
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2 deletions
+185
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perf_objdetect.cpp
modules/gpu/perf/perf_objdetect.cpp
+185
-2
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modules/gpu/perf/perf_objdetect.cpp
View file @
838842cc
...
@@ -89,11 +89,90 @@ PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gp
...
@@ -89,11 +89,90 @@ PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gp
SANITY_CHECK
(
found_locations
);
SANITY_CHECK
(
found_locations
);
}
}
//================================================= ICF SoftCascade =================================================//
typedef
pair
<
string
,
string
>
pair_string
;
typedef
pair
<
string
,
string
>
pair_string
;
DEF_PARAM_TEST_1
(
SoftCascade
,
pair_string
);
DEF_PARAM_TEST_1
(
SoftCascade
,
pair_string
);
PERF_TEST_P
(
SoftCascade
,
detect
,
Values
<
pair_string
>
(
make_pair
(
"cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml"
,
"cv/cascadeandhog/bahnhof/image_00000000_0.png"
)))
// struct SoftCascadeTest : public perf::TestBaseWithParam<roi_fixture_t>
// {
// typedef cv::gpu::SoftCascade::Detection detection_t;
// static cv::Rect getFromTable(int idx)
// {
// static const cv::Rect rois[] =
// {
// cv::Rect( 65, 20, 35, 80),
// cv::Rect( 95, 35, 45, 40),
// cv::Rect( 45, 35, 45, 40),
// cv::Rect( 25, 27, 50, 45),
// cv::Rect(100, 50, 45, 40),
// cv::Rect( 60, 30, 45, 40),
// cv::Rect( 40, 55, 50, 40),
// cv::Rect( 48, 37, 72, 80),
// cv::Rect( 48, 32, 85, 58),
// cv::Rect( 48, 0, 32, 27)
// };
// return rois[idx];
// }
// static std::string itoa(long i)
// {
// static char s[65];
// sprintf(s, "%ld", i);
// return std::string(s);
// }
// static std::string getImageName(int level)
// {
// time_t rawtime;
// struct tm * timeinfo;
// char buffer [80];
// time ( &rawtime );
// timeinfo = localtime ( &rawtime );
// strftime (buffer,80,"%Y-%m-%d--%H-%M-%S",timeinfo);
// return "gpu_rec_level_" + itoa(level)+ "_" + std::string(buffer) + ".png";
// }
// static void print(std::ostream &out, const detection_t& d)
// {
// out << "\x1b[32m[ detection]\x1b[0m ("
// << std::setw(4) << d.x
// << " "
// << std::setw(4) << d.y
// << ") ("
// << std::setw(4) << d.w
// << " "
// << std::setw(4) << d.h
// << ") "
// << std::setw(12) << d.confidence
// << std::endl;
// }
// static void printTotal(std::ostream &out, int detbytes)
// {
// out << "\x1b[32m[ ]\x1b[0m Total detections " << (detbytes / sizeof(detection_t)) << std::endl;
// }
// static void writeResult(const cv::Mat& result, const int level)
// {
// std::string path = cv::tempfile(getImageName(level).c_str());
// cv::imwrite(path, result);
// std::cout << "\x1b[32m" << "[ ]" << std::endl << "[ stored in]"<< "\x1b[0m" << path << std::endl;
// }
// };
typedef
std
::
tr1
::
tuple
<
std
::
string
,
std
::
string
>
fixture_t
;
typedef
perf
::
TestBaseWithParam
<
fixture_t
>
SoftCascadeTest
;
PERF_TEST_P
(
SoftCascadeTest
,
detect
,
testing
::
Combine
(
testing
::
Values
(
std
::
string
(
"cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml"
)),
testing
::
Values
(
std
::
string
(
"cv/cascadeandhog/bahnhof/image_00000000_0.png"
))))
{
{
if
(
runOnGpu
)
if
(
runOnGpu
)
{
{
...
@@ -133,6 +212,110 @@ PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog
...
@@ -133,6 +212,110 @@ PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog
}
}
}
}
static
cv
::
Rect
getFromTable
(
int
idx
)
{
static
const
cv
::
Rect
rois
[]
=
{
cv
::
Rect
(
65
,
20
,
35
,
80
),
cv
::
Rect
(
95
,
35
,
45
,
40
),
cv
::
Rect
(
45
,
35
,
45
,
40
),
cv
::
Rect
(
25
,
27
,
50
,
45
),
cv
::
Rect
(
100
,
50
,
45
,
40
),
cv
::
Rect
(
60
,
30
,
45
,
40
),
cv
::
Rect
(
40
,
55
,
50
,
40
),
cv
::
Rect
(
48
,
37
,
72
,
80
),
cv
::
Rect
(
48
,
32
,
85
,
58
),
cv
::
Rect
(
48
,
0
,
32
,
27
)
};
return
rois
[
idx
];
}
typedef
std
::
tr1
::
tuple
<
std
::
string
,
std
::
string
,
int
>
roi_fixture_t
;
typedef
perf
::
TestBaseWithParam
<
roi_fixture_t
>
SoftCascadeTestRoi
;
PERF_TEST_P
(
SoftCascadeTestRoi
,
detectInRoi
,
testing
::
Combine
(
testing
::
Values
(
std
::
string
(
"cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml"
)),
testing
::
Values
(
std
::
string
(
"cv/cascadeandhog/bahnhof/image_00000000_0.png"
)),
testing
::
Range
(
0
,
5
)))
{
if
(
runOnGpu
)
{
cv
::
Mat
cpu
=
readImage
(
GET_PARAM
(
1
));
ASSERT_FALSE
(
cpu
.
empty
());
cv
::
gpu
::
GpuMat
colored
(
cpu
);
cv
::
gpu
::
SoftCascade
cascade
;
ASSERT_TRUE
(
cascade
.
load
(
perf
::
TestBase
::
getDataPath
(
GET_PARAM
(
0
))));
cv
::
gpu
::
GpuMat
objectBoxes
(
1
,
16384
*
20
,
CV_8UC1
),
rois
(
cascade
.
getRoiSize
(),
CV_8UC1
);
rois
.
setTo
(
0
);
int
nroi
=
GET_PARAM
(
2
);
cv
::
RNG
rng
;
for
(
int
i
=
0
;
i
<
nroi
;
++
i
)
{
cv
::
Rect
r
=
getFromTable
(
rng
(
10
));
cv
::
gpu
::
GpuMat
sub
(
rois
,
r
);
sub
.
setTo
(
1
);
}
cv
::
gpu
::
GpuMat
curr
=
objectBoxes
;
cascade
.
detectMultiScale
(
colored
,
rois
,
curr
);
TEST_CYCLE
()
{
curr
=
objectBoxes
;
cascade
.
detectMultiScale
(
colored
,
rois
,
curr
);
}
}
else
{
FAIL
();
}
}
PERF_TEST_P
(
SoftCascadeTestRoi
,
detectEachRoi
,
testing
::
Combine
(
testing
::
Values
(
std
::
string
(
"cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml"
)),
testing
::
Values
(
std
::
string
(
"cv/cascadeandhog/bahnhof/image_00000000_0.png"
)),
testing
::
Range
(
0
,
10
)))
{
if
(
runOnGpu
)
{
cv
::
Mat
cpu
=
readImage
(
GET_PARAM
(
1
));
ASSERT_FALSE
(
cpu
.
empty
());
cv
::
gpu
::
GpuMat
colored
(
cpu
);
cv
::
gpu
::
SoftCascade
cascade
;
ASSERT_TRUE
(
cascade
.
load
(
perf
::
TestBase
::
getDataPath
(
GET_PARAM
(
0
))));
cv
::
gpu
::
GpuMat
objectBoxes
(
1
,
16384
*
20
,
CV_8UC1
),
rois
(
cascade
.
getRoiSize
(),
CV_8UC1
);
rois
.
setTo
(
0
);
int
idx
=
GET_PARAM
(
2
);
cv
::
Rect
r
=
getFromTable
(
idx
);
cv
::
gpu
::
GpuMat
sub
(
rois
,
r
);
sub
.
setTo
(
1
);
cv
::
gpu
::
GpuMat
curr
=
objectBoxes
;
cascade
.
detectMultiScale
(
colored
,
rois
,
curr
);
TEST_CYCLE
()
{
curr
=
objectBoxes
;
cascade
.
detectMultiScale
(
colored
,
rois
,
curr
);
}
}
else
{
FAIL
();
}
}
///////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////
// HaarClassifier
// HaarClassifier
...
...
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