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f056e713
编写于
1月 18, 2018
作者:
A
Alexander Alekhin
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差异文件
Merge pull request #10512 from sturkmen72:update_documentation
上级
aa55cdb7
dcd4f8f5
变更
8
展开全部
隐藏空白更改
内联
并排
Showing
8 changed file
with
452 addition
and
401 deletion
+452
-401
modules/core/include/opencv2/core.hpp
modules/core/include/opencv2/core.hpp
+50
-73
modules/core/include/opencv2/core/types.hpp
modules/core/include/opencv2/core/types.hpp
+36
-44
modules/imgcodecs/include/opencv2/imgcodecs.hpp
modules/imgcodecs/include/opencv2/imgcodecs.hpp
+1
-42
modules/imgproc/include/opencv2/imgproc.hpp
modules/imgproc/include/opencv2/imgproc.hpp
+252
-227
samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
+6
-6
samples/cpp/tutorial_code/snippets/core_reduce.cpp
samples/cpp/tutorial_code/snippets/core_reduce.cpp
+9
-9
samples/cpp/tutorial_code/snippets/core_various.cpp
samples/cpp/tutorial_code/snippets/core_various.cpp
+53
-0
samples/cpp/tutorial_code/snippets/imgcodecs_imwrite.cpp
samples/cpp/tutorial_code/snippets/imgcodecs_imwrite.cpp
+45
-0
未找到文件。
modules/core/include/opencv2/core.hpp
浏览文件 @
f056e713
此差异已折叠。
点击以展开。
modules/core/include/opencv2/core/types.hpp
浏览文件 @
f056e713
...
...
@@ -75,7 +75,7 @@ template<typename _Tp> class Complex
{
public:
//!
constructors
//!
default constructor
Complex
();
Complex
(
_Tp
_re
,
_Tp
_im
=
0
);
...
...
@@ -159,7 +159,7 @@ template<typename _Tp> class Point_
public:
typedef
_Tp
value_type
;
//
various constructors
//
! default constructor
Point_
();
Point_
(
_Tp
_x
,
_Tp
_y
);
Point_
(
const
Point_
&
pt
);
...
...
@@ -181,8 +181,8 @@ public:
double
cross
(
const
Point_
&
pt
)
const
;
//! checks whether the point is inside the specified rectangle
bool
inside
(
const
Rect_
<
_Tp
>&
r
)
const
;
_Tp
x
,
y
;
//< the point coordinates
_Tp
x
;
//!< x coordinate of the point
_Tp
y
;
//!< y coordinate of the point
};
typedef
Point_
<
int
>
Point2i
;
...
...
@@ -239,7 +239,7 @@ template<typename _Tp> class Point3_
public:
typedef
_Tp
value_type
;
//
various constructors
//
! default constructor
Point3_
();
Point3_
(
_Tp
_x
,
_Tp
_y
,
_Tp
_z
);
Point3_
(
const
Point3_
&
pt
);
...
...
@@ -262,8 +262,9 @@ public:
double
ddot
(
const
Point3_
&
pt
)
const
;
//! cross product of the 2 3D points
Point3_
cross
(
const
Point3_
&
pt
)
const
;
_Tp
x
,
y
,
z
;
//< the point coordinates
_Tp
x
;
//!< x coordinate of the 3D point
_Tp
y
;
//!< y coordinate of the 3D point
_Tp
z
;
//!< z coordinate of the 3D point
};
typedef
Point3_
<
int
>
Point3i
;
...
...
@@ -316,7 +317,7 @@ template<typename _Tp> class Size_
public:
typedef
_Tp
value_type
;
//!
various constructors
//!
default constructor
Size_
();
Size_
(
_Tp
_width
,
_Tp
_height
);
Size_
(
const
Size_
&
sz
);
...
...
@@ -331,7 +332,8 @@ public:
//! conversion of another data type.
template
<
typename
_Tp2
>
operator
Size_
<
_Tp2
>
()
const
;
_Tp
width
,
height
;
// the width and the height
_Tp
width
;
//!< the width
_Tp
height
;
//!< the height
};
typedef
Size_
<
int
>
Size2i
;
...
...
@@ -416,7 +418,7 @@ template<typename _Tp> class Rect_
public:
typedef
_Tp
value_type
;
//!
various constructors
//!
default constructor
Rect_
();
Rect_
(
_Tp
_x
,
_Tp
_y
,
_Tp
_width
,
_Tp
_height
);
Rect_
(
const
Rect_
&
r
);
...
...
@@ -442,7 +444,10 @@ public:
//! checks whether the rectangle contains the point
bool
contains
(
const
Point_
<
_Tp
>&
pt
)
const
;
_Tp
x
,
y
,
width
,
height
;
//< the top-left corner, as well as width and height of the rectangle
_Tp
x
;
//!< x coordinate of the top-left corner
_Tp
y
;
//!< y coordinate of the top-left corner
_Tp
width
;
//!< width of the rectangle
_Tp
height
;
//!< height of the rectangle
};
typedef
Rect_
<
int
>
Rect2i
;
...
...
@@ -481,24 +486,10 @@ struct Type< Rect_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 4) };
/** @brief The class represents rotated (i.e. not up-right) rectangles on a plane.
Each rectangle is specified by the center point (mass center), length of each side (represented by
cv::
Size2f structure) and the rotation angle in degrees.
#
Size2f structure) and the rotation angle in degrees.
The sample below demonstrates how to use RotatedRect:
@code
Mat image(200, 200, CV_8UC3, Scalar(0));
RotatedRect rRect = RotatedRect(Point2f(100,100), Size2f(100,50), 30);
Point2f vertices[4];
rRect.points(vertices);
for (int i = 0; i < 4; i++)
line(image, vertices[i], vertices[(i+1)%4], Scalar(0,255,0));
Rect brect = rRect.boundingRect();
rectangle(image, brect, Scalar(255,0,0));
imshow("rectangles", image);
waitKey(0);
@endcode
@snippet snippets/core_various.cpp RotatedRect_demo
![image](pics/rotatedrect.png)
@sa CamShift, fitEllipse, minAreaRect, CvBox2D
...
...
@@ -506,9 +497,9 @@ The sample below demonstrates how to use RotatedRect:
class
CV_EXPORTS
RotatedRect
{
public:
//!
various constructors
//!
default constructor
RotatedRect
();
/**
/**
full constructor
@param center The rectangle mass center.
@param size Width and height of the rectangle.
@param angle The rotation angle in a clockwise direction. When the angle is 0, 90, 180, 270 etc.,
...
...
@@ -529,10 +520,12 @@ public:
Rect
boundingRect
()
const
;
//! returns the minimal (exact) floating point rectangle containing the rotated rectangle, not intended for use with images
Rect_
<
float
>
boundingRect2f
()
const
;
Point2f
center
;
//< the rectangle mass center
Size2f
size
;
//< width and height of the rectangle
float
angle
;
//< the rotation angle. When the angle is 0, 90, 180, 270 etc., the rectangle becomes an up-right rectangle.
//! returns the rectangle mass center
Point2f
center
;
//! returns width and height of the rectangle
Size2f
size
;
//! returns the rotation angle. When the angle is 0, 90, 180, 270 etc., the rectangle becomes an up-right rectangle.
float
angle
;
};
template
<
>
class
DataType
<
RotatedRect
>
...
...
@@ -637,7 +630,7 @@ OpenCV to pass pixel values.
template
<
typename
_Tp
>
class
Scalar_
:
public
Vec
<
_Tp
,
4
>
{
public:
//!
various constructors
//!
default constructor
Scalar_
();
Scalar_
(
_Tp
v0
,
_Tp
v1
,
_Tp
v2
=
0
,
_Tp
v3
=
0
);
Scalar_
(
_Tp
v0
);
...
...
@@ -654,10 +647,10 @@ public:
//! per-element product
Scalar_
<
_Tp
>
mul
(
const
Scalar_
<
_Tp
>&
a
,
double
scale
=
1
)
const
;
// returns (v0, -v1, -v2, -v3)
//
!
returns (v0, -v1, -v2, -v3)
Scalar_
<
_Tp
>
conj
()
const
;
// returns true iff v1 == v2 == v3 == 0
//
!
returns true iff v1 == v2 == v3 == 0
bool
isReal
()
const
;
};
...
...
@@ -695,14 +688,13 @@ struct Type< Scalar_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 4) }
/** @brief Data structure for salient point detectors.
The class instance stores a keypoint, i.e. a point feature found by one of many available keypoint
detectors, such as Harris corner detector, cv::FAST, cv::StarDetector, cv::SURF, cv::SIFT,
cv::LDetector etc.
detectors, such as Harris corner detector, #FAST, %StarDetector, %SURF, %SIFT etc.
The keypoint is characterized by the 2D position, scale (proportional to the diameter of the
neighborhood that needs to be taken into account), orientation and some other parameters. The
keypoint neighborhood is then analyzed by another algorithm that builds a descriptor (usually
represented as a feature vector). The keypoints representing the same object in different images
can then be matched using
cv::
KDTree or another method.
can then be matched using
%
KDTree or another method.
*/
class
CV_EXPORTS_W_SIMPLE
KeyPoint
{
...
...
@@ -808,9 +800,9 @@ public:
CV_WRAP
DMatch
(
int
_queryIdx
,
int
_trainIdx
,
float
_distance
);
CV_WRAP
DMatch
(
int
_queryIdx
,
int
_trainIdx
,
int
_imgIdx
,
float
_distance
);
CV_PROP_RW
int
queryIdx
;
// query descriptor index
CV_PROP_RW
int
trainIdx
;
// train descriptor index
CV_PROP_RW
int
imgIdx
;
// train image index
CV_PROP_RW
int
queryIdx
;
//
!<
query descriptor index
CV_PROP_RW
int
trainIdx
;
//
!<
train descriptor index
CV_PROP_RW
int
imgIdx
;
//
!<
train image index
CV_PROP_RW
float
distance
;
...
...
@@ -868,8 +860,8 @@ public:
TermCriteria
(
int
type
,
int
maxCount
,
double
epsilon
);
int
type
;
//!< the type of termination criteria: COUNT, EPS or COUNT + EPS
int
maxCount
;
// the maximum number of iterations/elements
double
epsilon
;
// the desired accuracy
int
maxCount
;
//
!<
the maximum number of iterations/elements
double
epsilon
;
//
!<
the desired accuracy
};
...
...
modules/imgcodecs/include/opencv2/imgcodecs.hpp
浏览文件 @
f056e713
...
...
@@ -197,48 +197,7 @@ should have alpha set to 0, fully opaque pixels should have alpha set to 255/655
The sample below shows how to create such a BGRA image and store to PNG file. It also demonstrates how to set custom
compression parameters :
@code
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;
void createAlphaMat(Mat &mat)
{
CV_Assert(mat.channels() == 4);
for (int i = 0; i < mat.rows; ++i) {
for (int j = 0; j < mat.cols; ++j) {
Vec4b& bgra = mat.at<Vec4b>(i, j);
bgra[0] = UCHAR_MAX; // Blue
bgra[1] = saturate_cast<uchar>((float (mat.cols - j)) / ((float)mat.cols) * UCHAR_MAX); // Green
bgra[2] = saturate_cast<uchar>((float (mat.rows - i)) / ((float)mat.rows) * UCHAR_MAX); // Red
bgra[3] = saturate_cast<uchar>(0.5 * (bgra[1] + bgra[2])); // Alpha
}
}
}
int main(int argv, char **argc)
{
// Create mat with alpha channel
Mat mat(480, 640, CV_8UC4);
createAlphaMat(mat);
vector<int> compression_params;
compression_params.push_back(IMWRITE_PNG_COMPRESSION);
compression_params.push_back(9);
try {
imwrite("alpha.png", mat, compression_params);
}
catch (cv::Exception& ex) {
fprintf(stderr, "Exception converting image to PNG format: %s\n", ex.what());
return 1;
}
fprintf(stdout, "Saved PNG file with alpha data.\n");
return 0;
}
@endcode
@include snippets/imgcodecs_imwrite.cpp
@param filename Name of the file.
@param img Image to be saved.
@param params Format-specific parameters encoded as pairs (paramId_1, paramValue_1, paramId_2, paramValue_2, ... .) see cv::ImwriteFlags
...
...
modules/imgproc/include/opencv2/imgproc.hpp
浏览文件 @
f056e713
此差异已折叠。
点击以展开。
samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
浏览文件 @
f056e713
...
...
@@ -73,15 +73,15 @@ int main()
//! [bin]
// Create binary image from source image
Mat
bw
;
cvtColor
(
src
,
bw
,
C
V
_BGR2GRAY
);
threshold
(
bw
,
bw
,
40
,
255
,
CV_THRESH_BINARY
|
CV_
THRESH_OTSU
);
cvtColor
(
src
,
bw
,
C
OLOR
_BGR2GRAY
);
threshold
(
bw
,
bw
,
40
,
255
,
THRESH_BINARY
|
THRESH_OTSU
);
imshow
(
"Binary Image"
,
bw
);
//! [bin]
//! [dist]
// Perform the distance transform algorithm
Mat
dist
;
distanceTransform
(
bw
,
dist
,
CV_
DIST_L2
,
3
);
distanceTransform
(
bw
,
dist
,
DIST_L2
,
3
);
// Normalize the distance image for range = {0.0, 1.0}
// so we can visualize and threshold it
...
...
@@ -92,7 +92,7 @@ int main()
//! [peaks]
// Threshold to obtain the peaks
// This will be the markers for the foreground objects
threshold
(
dist
,
dist
,
.4
,
1.
,
CV_
THRESH_BINARY
);
threshold
(
dist
,
dist
,
.4
,
1.
,
THRESH_BINARY
);
// Dilate a bit the dist image
Mat
kernel1
=
Mat
::
ones
(
3
,
3
,
CV_8UC1
);
...
...
@@ -108,7 +108,7 @@ int main()
// Find total markers
vector
<
vector
<
Point
>
>
contours
;
findContours
(
dist_8u
,
contours
,
CV_RETR_EXTERNAL
,
CV_
CHAIN_APPROX_SIMPLE
);
findContours
(
dist_8u
,
contours
,
RETR_EXTERNAL
,
CHAIN_APPROX_SIMPLE
);
// Create the marker image for the watershed algorithm
Mat
markers
=
Mat
::
zeros
(
dist
.
size
(),
CV_32SC1
);
...
...
@@ -165,4 +165,4 @@ int main()
waitKey
(
0
);
return
0
;
}
\ No newline at end of file
}
samples/cpp/tutorial_code/snippets/core_reduce.cpp
浏览文件 @
f056e713
...
...
@@ -23,8 +23,8 @@ int main()
Mat
m
=
(
Mat_
<
uchar
>
(
3
,
2
)
<<
1
,
2
,
3
,
4
,
5
,
6
);
Mat
col_sum
,
row_sum
;
reduce
(
m
,
col_sum
,
0
,
CV_
REDUCE_SUM
,
CV_32F
);
reduce
(
m
,
row_sum
,
1
,
CV_
REDUCE_SUM
,
CV_32F
);
reduce
(
m
,
col_sum
,
0
,
REDUCE_SUM
,
CV_32F
);
reduce
(
m
,
row_sum
,
1
,
REDUCE_SUM
,
CV_32F
);
/*
m =
[ 1, 2;
...
...
@@ -40,22 +40,22 @@ int main()
//! [example]
Mat
col_average
,
row_average
,
col_min
,
col_max
,
row_min
,
row_max
;
reduce
(
m
,
col_average
,
0
,
CV_
REDUCE_AVG
,
CV_32F
);
reduce
(
m
,
col_average
,
0
,
REDUCE_AVG
,
CV_32F
);
cout
<<
"col_average =
\n
"
<<
col_average
<<
endl
;
reduce
(
m
,
row_average
,
1
,
CV_
REDUCE_AVG
,
CV_32F
);
reduce
(
m
,
row_average
,
1
,
REDUCE_AVG
,
CV_32F
);
cout
<<
"row_average =
\n
"
<<
row_average
<<
endl
;
reduce
(
m
,
col_min
,
0
,
CV_
REDUCE_MIN
,
CV_8U
);
reduce
(
m
,
col_min
,
0
,
REDUCE_MIN
,
CV_8U
);
cout
<<
"col_min =
\n
"
<<
col_min
<<
endl
;
reduce
(
m
,
row_min
,
1
,
CV_
REDUCE_MIN
,
CV_8U
);
reduce
(
m
,
row_min
,
1
,
REDUCE_MIN
,
CV_8U
);
cout
<<
"row_min =
\n
"
<<
row_min
<<
endl
;
reduce
(
m
,
col_max
,
0
,
CV_
REDUCE_MAX
,
CV_8U
);
reduce
(
m
,
col_max
,
0
,
REDUCE_MAX
,
CV_8U
);
cout
<<
"col_max =
\n
"
<<
col_max
<<
endl
;
reduce
(
m
,
row_max
,
1
,
CV_
REDUCE_MAX
,
CV_8U
);
reduce
(
m
,
row_max
,
1
,
REDUCE_MAX
,
CV_8U
);
cout
<<
"row_max =
\n
"
<<
row_max
<<
endl
;
/*
...
...
@@ -86,7 +86,7 @@ int main()
char
d
[]
=
{
1
,
2
,
3
,
4
,
5
,
6
};
Mat
m
(
3
,
1
,
CV_8UC2
,
d
);
Mat
col_sum_per_channel
;
reduce
(
m
,
col_sum_per_channel
,
0
,
CV_
REDUCE_SUM
,
CV_32F
);
reduce
(
m
,
col_sum_per_channel
,
0
,
REDUCE_SUM
,
CV_32F
);
/*
col_sum_per_channel =
[9, 12]
...
...
samples/cpp/tutorial_code/snippets/core_various.cpp
0 → 100644
浏览文件 @
f056e713
#include <opencv2/opencv.hpp>
using
namespace
std
;
using
namespace
cv
;
int
main
()
{
//! [Algorithm]
Ptr
<
Feature2D
>
sbd
=
SimpleBlobDetector
::
create
();
FileStorage
fs_read
(
"SimpleBlobDetector_params.xml"
,
FileStorage
::
READ
);
if
(
fs_read
.
isOpened
())
// if we have file with parameters, read them
{
sbd
->
read
(
fs_read
.
root
());
fs_read
.
release
();
}
else
// else modify the parameters and store them; user can later edit the file to use different parameters
{
fs_read
.
release
();
FileStorage
fs_write
(
"SimpleBlobDetector_params.xml"
,
FileStorage
::
WRITE
);
sbd
->
write
(
fs_write
);
fs_write
.
release
();
}
Mat
result
,
image
=
imread
(
"../data/detect_blob.png"
,
IMREAD_COLOR
);
vector
<
KeyPoint
>
keypoints
;
sbd
->
detect
(
image
,
keypoints
,
Mat
());
drawKeypoints
(
image
,
keypoints
,
result
);
for
(
vector
<
KeyPoint
>::
iterator
k
=
keypoints
.
begin
();
k
!=
keypoints
.
end
();
++
k
)
circle
(
result
,
k
->
pt
,
(
int
)
k
->
size
,
Scalar
(
0
,
0
,
255
),
2
);
imshow
(
"result"
,
result
);
waitKey
(
0
);
//! [Algorithm]
//! [RotatedRect_demo]
Mat
test_image
(
200
,
200
,
CV_8UC3
,
Scalar
(
0
));
RotatedRect
rRect
=
RotatedRect
(
Point2f
(
100
,
100
),
Size2f
(
100
,
50
),
30
);
Point2f
vertices
[
4
];
rRect
.
points
(
vertices
);
for
(
int
i
=
0
;
i
<
4
;
i
++
)
line
(
test_image
,
vertices
[
i
],
vertices
[(
i
+
1
)
%
4
],
Scalar
(
0
,
255
,
0
),
2
);
Rect
brect
=
rRect
.
boundingRect
();
rectangle
(
test_image
,
brect
,
Scalar
(
255
,
0
,
0
),
2
);
imshow
(
"rectangles"
,
test_image
);
waitKey
(
0
);
//! [RotatedRect_demo]
return
0
;
}
samples/cpp/tutorial_code/snippets/imgcodecs_imwrite.cpp
0 → 100644
浏览文件 @
f056e713
#include <opencv2/opencv.hpp>
using
namespace
cv
;
using
namespace
std
;
static
void
createAlphaMat
(
Mat
&
mat
)
{
CV_Assert
(
mat
.
channels
()
==
4
);
for
(
int
i
=
0
;
i
<
mat
.
rows
;
++
i
)
{
for
(
int
j
=
0
;
j
<
mat
.
cols
;
++
j
)
{
Vec4b
&
bgra
=
mat
.
at
<
Vec4b
>
(
i
,
j
);
bgra
[
0
]
=
UCHAR_MAX
;
// Blue
bgra
[
1
]
=
saturate_cast
<
uchar
>
((
float
(
mat
.
cols
-
j
))
/
((
float
)
mat
.
cols
)
*
UCHAR_MAX
);
// Green
bgra
[
2
]
=
saturate_cast
<
uchar
>
((
float
(
mat
.
rows
-
i
))
/
((
float
)
mat
.
rows
)
*
UCHAR_MAX
);
// Red
bgra
[
3
]
=
saturate_cast
<
uchar
>
(
0.5
*
(
bgra
[
1
]
+
bgra
[
2
]));
// Alpha
}
}
}
int
main
()
{
// Create mat with alpha channel
Mat
mat
(
480
,
640
,
CV_8UC4
);
createAlphaMat
(
mat
);
vector
<
int
>
compression_params
;
compression_params
.
push_back
(
IMWRITE_PNG_COMPRESSION
);
compression_params
.
push_back
(
9
);
bool
result
=
false
;
try
{
result
=
imwrite
(
"alpha.png"
,
mat
,
compression_params
);
}
catch
(
const
cv
::
Exception
&
ex
)
{
fprintf
(
stderr
,
"Exception converting image to PNG format: %s
\n
"
,
ex
.
what
());
}
if
(
result
)
printf
(
"Saved PNG file with alpha data.
\n
"
);
else
printf
(
"ERROR: Can't save PNG file.
\n
"
);
return
result
?
0
:
1
;
}
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