Skip to content
Projects
Groups
Snippets
Help
Loading...
Sign in / Register
Toggle navigation
O
opencv
Project
Project
Details
Activity
Cycle Analytics
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Charts
Issues
0
Issues
0
List
Board
Labels
Milestones
Merge Requests
0
Merge Requests
0
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Charts
Packages
Packages
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Charts
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
submodule
opencv
Commits
bd98ed46
Commit
bd98ed46
authored
Sep 06, 2018
by
Alexander Alekhin
Browse files
Options
Browse Files
Download
Plain Diff
Merge pull request #12446 from alalek:imgproc_grabcut_numeric_issues
parents
8b48c2a1
24e72e15
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
with
29 additions
and
29 deletions
+29
-29
grabcut.cpp
modules/imgproc/src/grabcut.cpp
+29
-29
No files found.
modules/imgproc/src/grabcut.cpp
View file @
bd98ed46
...
@@ -69,7 +69,7 @@ public:
...
@@ -69,7 +69,7 @@ public:
void
endLearning
();
void
endLearning
();
private
:
private
:
void
calcInverseCovAndDeterm
(
int
ci
);
void
calcInverseCovAndDeterm
(
int
ci
,
double
singularFix
);
Mat
model
;
Mat
model
;
double
*
coefs
;
double
*
coefs
;
double
*
mean
;
double
*
mean
;
...
@@ -103,7 +103,7 @@ GMM::GMM( Mat& _model )
...
@@ -103,7 +103,7 @@ GMM::GMM( Mat& _model )
for
(
int
ci
=
0
;
ci
<
componentsCount
;
ci
++
)
for
(
int
ci
=
0
;
ci
<
componentsCount
;
ci
++
)
if
(
coefs
[
ci
]
>
0
)
if
(
coefs
[
ci
]
>
0
)
calcInverseCovAndDeterm
(
ci
);
calcInverseCovAndDeterm
(
ci
,
0.0
);
totalSampleCount
=
0
;
totalSampleCount
=
0
;
}
}
...
@@ -175,7 +175,6 @@ void GMM::addSample( int ci, const Vec3d color )
...
@@ -175,7 +175,6 @@ void GMM::addSample( int ci, const Vec3d color )
void
GMM
::
endLearning
()
void
GMM
::
endLearning
()
{
{
CV_Assert
(
totalSampleCount
>
0
);
CV_Assert
(
totalSampleCount
>
0
);
const
double
variance
=
0.01
;
for
(
int
ci
=
0
;
ci
<
componentsCount
;
ci
++
)
for
(
int
ci
=
0
;
ci
<
componentsCount
;
ci
++
)
{
{
int
n
=
sampleCounts
[
ci
];
int
n
=
sampleCounts
[
ci
];
...
@@ -183,48 +182,49 @@ void GMM::endLearning()
...
@@ -183,48 +182,49 @@ void GMM::endLearning()
coefs
[
ci
]
=
0
;
coefs
[
ci
]
=
0
;
else
else
{
{
double
inv_n
=
1.0
/
n
;
coefs
[
ci
]
=
(
double
)
n
/
totalSampleCount
;
coefs
[
ci
]
=
(
double
)
n
/
totalSampleCount
;
double
*
m
=
mean
+
3
*
ci
;
double
*
m
=
mean
+
3
*
ci
;
m
[
0
]
=
sums
[
ci
][
0
]
/
n
;
m
[
1
]
=
sums
[
ci
][
1
]
/
n
;
m
[
2
]
=
sums
[
ci
][
2
]
/
n
;
m
[
0
]
=
sums
[
ci
][
0
]
*
inv_n
;
m
[
1
]
=
sums
[
ci
][
1
]
*
inv_n
;
m
[
2
]
=
sums
[
ci
][
2
]
*
inv_
n
;
double
*
c
=
cov
+
9
*
ci
;
double
*
c
=
cov
+
9
*
ci
;
c
[
0
]
=
prods
[
ci
][
0
][
0
]
/
n
-
m
[
0
]
*
m
[
0
];
c
[
1
]
=
prods
[
ci
][
0
][
1
]
/
n
-
m
[
0
]
*
m
[
1
];
c
[
2
]
=
prods
[
ci
][
0
][
2
]
/
n
-
m
[
0
]
*
m
[
2
];
c
[
0
]
=
prods
[
ci
][
0
][
0
]
*
inv_n
-
m
[
0
]
*
m
[
0
];
c
[
1
]
=
prods
[
ci
][
0
][
1
]
*
inv_n
-
m
[
0
]
*
m
[
1
];
c
[
2
]
=
prods
[
ci
][
0
][
2
]
*
inv_
n
-
m
[
0
]
*
m
[
2
];
c
[
3
]
=
prods
[
ci
][
1
][
0
]
/
n
-
m
[
1
]
*
m
[
0
];
c
[
4
]
=
prods
[
ci
][
1
][
1
]
/
n
-
m
[
1
]
*
m
[
1
];
c
[
5
]
=
prods
[
ci
][
1
][
2
]
/
n
-
m
[
1
]
*
m
[
2
];
c
[
3
]
=
prods
[
ci
][
1
][
0
]
*
inv_n
-
m
[
1
]
*
m
[
0
];
c
[
4
]
=
prods
[
ci
][
1
][
1
]
*
inv_n
-
m
[
1
]
*
m
[
1
];
c
[
5
]
=
prods
[
ci
][
1
][
2
]
*
inv_
n
-
m
[
1
]
*
m
[
2
];
c
[
6
]
=
prods
[
ci
][
2
][
0
]
/
n
-
m
[
2
]
*
m
[
0
];
c
[
7
]
=
prods
[
ci
][
2
][
1
]
/
n
-
m
[
2
]
*
m
[
1
];
c
[
8
]
=
prods
[
ci
][
2
][
2
]
/
n
-
m
[
2
]
*
m
[
2
];
c
[
6
]
=
prods
[
ci
][
2
][
0
]
*
inv_n
-
m
[
2
]
*
m
[
0
];
c
[
7
]
=
prods
[
ci
][
2
][
1
]
*
inv_n
-
m
[
2
]
*
m
[
1
];
c
[
8
]
=
prods
[
ci
][
2
][
2
]
*
inv_
n
-
m
[
2
]
*
m
[
2
];
double
dtrm
=
c
[
0
]
*
(
c
[
4
]
*
c
[
8
]
-
c
[
5
]
*
c
[
7
])
-
c
[
1
]
*
(
c
[
3
]
*
c
[
8
]
-
c
[
5
]
*
c
[
6
])
+
c
[
2
]
*
(
c
[
3
]
*
c
[
7
]
-
c
[
4
]
*
c
[
6
]);
calcInverseCovAndDeterm
(
ci
,
0.01
);
if
(
dtrm
<=
std
::
numeric_limits
<
double
>::
epsilon
()
)
{
// Adds the white noise to avoid singular covariance matrix.
c
[
0
]
+=
variance
;
c
[
4
]
+=
variance
;
c
[
8
]
+=
variance
;
}
calcInverseCovAndDeterm
(
ci
);
}
}
}
}
}
}
void
GMM
::
calcInverseCovAndDeterm
(
int
ci
)
void
GMM
::
calcInverseCovAndDeterm
(
int
ci
,
const
double
singularFix
)
{
{
if
(
coefs
[
ci
]
>
0
)
if
(
coefs
[
ci
]
>
0
)
{
{
double
*
c
=
cov
+
9
*
ci
;
double
*
c
=
cov
+
9
*
ci
;
double
dtrm
=
double
dtrm
=
c
[
0
]
*
(
c
[
4
]
*
c
[
8
]
-
c
[
5
]
*
c
[
7
])
-
c
[
1
]
*
(
c
[
3
]
*
c
[
8
]
-
c
[
5
]
*
c
[
6
])
+
c
[
2
]
*
(
c
[
3
]
*
c
[
7
]
-
c
[
4
]
*
c
[
6
]);
covDeterms
[
ci
]
=
c
[
0
]
*
(
c
[
4
]
*
c
[
8
]
-
c
[
5
]
*
c
[
7
])
-
c
[
1
]
*
(
c
[
3
]
*
c
[
8
]
-
c
[
5
]
*
c
[
6
])
+
c
[
2
]
*
(
c
[
3
]
*
c
[
7
]
-
c
[
4
]
*
c
[
6
]);
if
(
dtrm
<=
1e-6
&&
singularFix
>
0
)
{
// Adds the white noise to avoid singular covariance matrix.
c
[
0
]
+=
singularFix
;
c
[
4
]
+=
singularFix
;
c
[
8
]
+=
singularFix
;
dtrm
=
c
[
0
]
*
(
c
[
4
]
*
c
[
8
]
-
c
[
5
]
*
c
[
7
])
-
c
[
1
]
*
(
c
[
3
]
*
c
[
8
]
-
c
[
5
]
*
c
[
6
])
+
c
[
2
]
*
(
c
[
3
]
*
c
[
7
]
-
c
[
4
]
*
c
[
6
]);
}
covDeterms
[
ci
]
=
dtrm
;
CV_Assert
(
dtrm
>
std
::
numeric_limits
<
double
>::
epsilon
()
);
CV_Assert
(
dtrm
>
std
::
numeric_limits
<
double
>::
epsilon
()
);
inverseCovs
[
ci
][
0
][
0
]
=
(
c
[
4
]
*
c
[
8
]
-
c
[
5
]
*
c
[
7
])
/
dtrm
;
double
inv_dtrm
=
1.0
/
dtrm
;
inverseCovs
[
ci
][
1
][
0
]
=
-
(
c
[
3
]
*
c
[
8
]
-
c
[
5
]
*
c
[
6
])
/
dtrm
;
inverseCovs
[
ci
][
0
][
0
]
=
(
c
[
4
]
*
c
[
8
]
-
c
[
5
]
*
c
[
7
])
*
inv_dtrm
;
inverseCovs
[
ci
][
2
][
0
]
=
(
c
[
3
]
*
c
[
7
]
-
c
[
4
]
*
c
[
6
])
/
dtrm
;
inverseCovs
[
ci
][
1
][
0
]
=
-
(
c
[
3
]
*
c
[
8
]
-
c
[
5
]
*
c
[
6
])
*
inv_dtrm
;
inverseCovs
[
ci
][
0
][
1
]
=
-
(
c
[
1
]
*
c
[
8
]
-
c
[
2
]
*
c
[
7
])
/
dtrm
;
inverseCovs
[
ci
][
2
][
0
]
=
(
c
[
3
]
*
c
[
7
]
-
c
[
4
]
*
c
[
6
])
*
inv_dtrm
;
inverseCovs
[
ci
][
1
][
1
]
=
(
c
[
0
]
*
c
[
8
]
-
c
[
2
]
*
c
[
6
])
/
dtrm
;
inverseCovs
[
ci
][
0
][
1
]
=
-
(
c
[
1
]
*
c
[
8
]
-
c
[
2
]
*
c
[
7
])
*
inv_dtrm
;
inverseCovs
[
ci
][
2
][
1
]
=
-
(
c
[
0
]
*
c
[
7
]
-
c
[
1
]
*
c
[
6
])
/
dtrm
;
inverseCovs
[
ci
][
1
][
1
]
=
(
c
[
0
]
*
c
[
8
]
-
c
[
2
]
*
c
[
6
])
*
inv_dtrm
;
inverseCovs
[
ci
][
0
][
2
]
=
(
c
[
1
]
*
c
[
5
]
-
c
[
2
]
*
c
[
4
])
/
dtrm
;
inverseCovs
[
ci
][
2
][
1
]
=
-
(
c
[
0
]
*
c
[
7
]
-
c
[
1
]
*
c
[
6
])
*
inv_dtrm
;
inverseCovs
[
ci
][
1
][
2
]
=
-
(
c
[
0
]
*
c
[
5
]
-
c
[
2
]
*
c
[
3
])
/
dtrm
;
inverseCovs
[
ci
][
0
][
2
]
=
(
c
[
1
]
*
c
[
5
]
-
c
[
2
]
*
c
[
4
])
*
inv_dtrm
;
inverseCovs
[
ci
][
2
][
2
]
=
(
c
[
0
]
*
c
[
4
]
-
c
[
1
]
*
c
[
3
])
/
dtrm
;
inverseCovs
[
ci
][
1
][
2
]
=
-
(
c
[
0
]
*
c
[
5
]
-
c
[
2
]
*
c
[
3
])
*
inv_dtrm
;
inverseCovs
[
ci
][
2
][
2
]
=
(
c
[
0
]
*
c
[
4
]
-
c
[
1
]
*
c
[
3
])
*
inv_dtrm
;
}
}
}
}
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment