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钟尚武
dlib
Commits
ea02f4d4
Commit
ea02f4d4
authored
Apr 28, 2012
by
Davis King
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Added unit tests for the new graph cuts tools.
parent
80e501d8
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CMakeLists.txt
dlib/test/CMakeLists.txt
+1
-0
graph_cuts.cpp
dlib/test/graph_cuts.cpp
+749
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makefile
dlib/test/makefile
+1
-0
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dlib/test/CMakeLists.txt
View file @
ea02f4d4
...
@@ -45,6 +45,7 @@ set (tests
...
@@ -45,6 +45,7 @@ set (tests
find_max_factor_graph_viterbi.cpp
find_max_factor_graph_viterbi.cpp
geometry.cpp
geometry.cpp
graph.cpp
graph.cpp
graph_cuts.cpp
hash.cpp
hash.cpp
hash_map.cpp
hash_map.cpp
hash_set.cpp
hash_set.cpp
...
...
dlib/test/graph_cuts.cpp
0 → 100644
View file @
ea02f4d4
// Copyright (C) 2012 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#include <sstream>
#include <string>
#include <cstdlib>
#include <ctime>
#include <dlib/graph_cuts.h>
#include <dlib/graph_utils.h>
#include <dlib/directed_graph.h>
#include <dlib/rand.h>
#include "tester.h"
namespace
{
using
namespace
test
;
using
namespace
dlib
;
using
namespace
std
;
logger
dlog
(
"test.graph_cuts"
);
// ----------------------------------------------------------------------------------------
class
dense_potts_problem
{
public
:
typedef
double
value_type
;
private
:
matrix
<
value_type
,
0
,
2
>
factors1
;
matrix
<
value_type
>
factors2
;
matrix
<
node_label
,
0
,
1
>
labels
;
public
:
dense_potts_problem
(
unsigned
long
num_nodes
,
dlib
::
rand
&
rnd
)
{
factors1
=
-
7
*
(
randm
(
num_nodes
,
2
,
rnd
)
-
0.5
);
factors2
=
make_symmetric
(
randm
(
num_nodes
,
num_nodes
,
rnd
)
>
0.5
);
labels
.
set_size
(
num_nodes
);
labels
=
FREE_NODE
;
}
unsigned
long
number_of_nodes
(
)
const
{
return
factors1
.
nr
();
}
unsigned
long
number_of_neighbors
(
unsigned
long
// idx
)
const
{
return
number_of_nodes
()
-
1
;
}
unsigned
long
get_neighbor_idx
(
unsigned
long
node_id1
,
unsigned
long
node_id2
)
const
{
if
(
node_id2
<
node_id1
)
return
node_id2
;
else
return
node_id2
-
1
;
}
unsigned
long
get_neighbor
(
unsigned
long
node_id
,
unsigned
long
idx
)
const
{
DLIB_TEST
(
node_id
<
number_of_nodes
());
DLIB_TEST
(
idx
<
number_of_neighbors
(
node_id
));
if
(
idx
<
node_id
)
return
idx
;
else
return
idx
+
1
;
}
void
set_label
(
const
unsigned
long
&
idx
,
node_label
value
)
{
labels
(
idx
)
=
value
;
}
node_label
get_label
(
const
unsigned
long
&
idx
)
const
{
return
labels
(
idx
);
}
value_type
factor_value
(
unsigned
long
idx
,
bool
value
)
const
{
DLIB_TEST
(
idx
<
number_of_nodes
());
if
(
value
)
return
factors1
(
idx
,
0
);
else
return
factors1
(
idx
,
1
);
}
value_type
factor_value_disagreement
(
unsigned
long
idx1
,
unsigned
long
idx2
)
const
{
DLIB_TEST
(
idx1
!=
idx2
);
DLIB_TEST
(
idx1
<
number_of_nodes
());
DLIB_TEST
(
idx2
<
number_of_nodes
());
DLIB_TEST
(
get_neighbor_idx
(
idx1
,
idx2
)
<
number_of_neighbors
(
idx1
));
DLIB_TEST
(
get_neighbor_idx
(
idx2
,
idx1
)
<
number_of_neighbors
(
idx2
));
return
factors2
(
idx1
,
idx2
);
}
};
// ----------------------------------------------------------------------------------------
class
image_potts_problem
{
public
:
typedef
double
value_type
;
const
static
unsigned
long
max_number_of_neighbors
=
4
;
private
:
matrix
<
value_type
,
0
,
2
>
factors1
;
matrix
<
value_type
>
factors2
;
matrix
<
node_label
,
0
,
1
>
labels
;
long
nr
;
long
nc
;
rectangle
rect
,
inner_rect
;
mutable
long
count
;
public
:
image_potts_problem
(
long
nr_
,
long
nc_
,
dlib
::
rand
&
rnd
)
:
nr
(
nr_
),
nc
(
nc_
)
{
rect
=
rectangle
(
0
,
0
,
nc
-
1
,
nr
-
1
);
inner_rect
=
shrink_rect
(
rect
,
1
);
const
unsigned
long
num_nodes
=
nr
*
nc
;
factors1
=
-
7
*
(
randm
(
num_nodes
,
2
,
rnd
));
factors2
=
randm
(
num_nodes
,
4
,
rnd
)
>
0.5
;
//factors1 = 0;
//set_rowm(factors1, range(0, factors1.nr()/2)) = -1;
labels
.
set_size
(
num_nodes
);
labels
=
FREE_NODE
;
count
=
0
;
}
~
image_potts_problem
()
{
dlog
<<
LTRACE
<<
"interface calls: "
<<
count
;
dlog
<<
LTRACE
<<
"labels hash: "
<<
murmur_hash3_128bit
(
&
labels
(
0
),
labels
.
size
()
*
sizeof
(
labels
(
0
)),
0
).
first
;
}
unsigned
long
number_of_nodes
(
)
const
{
return
factors1
.
nr
();
}
unsigned
long
number_of_neighbors
(
unsigned
long
idx
)
const
{
++
count
;
const
point
&
p
=
get_loc
(
idx
);
if
(
inner_rect
.
contains
(
p
))
return
4
;
else
if
(
p
==
rect
.
tl_corner
()
||
p
==
rect
.
bl_corner
()
||
p
==
rect
.
tr_corner
()
||
p
==
rect
.
br_corner
()
)
return
2
;
else
return
3
;
}
unsigned
long
get_neighbor_idx
(
long
node_id1
,
long
node_id2
)
const
{
++
count
;
const
point
&
p
=
get_loc
(
node_id1
);
long
ret
=
0
;
if
(
rect
.
contains
(
p
+
point
(
1
,
0
)))
{
if
(
node_id2
-
node_id1
==
1
)
return
ret
;
++
ret
;
}
if
(
rect
.
contains
(
p
-
point
(
1
,
0
)))
{
if
(
node_id2
-
node_id1
==
-
1
)
return
ret
;
++
ret
;
}
if
(
rect
.
contains
(
p
+
point
(
0
,
1
)))
{
if
(
node_id2
-
node_id1
==
nc
)
return
ret
;
++
ret
;
}
return
ret
;
}
unsigned
long
get_neighbor
(
long
node_id
,
long
idx
)
const
{
++
count
;
const
point
&
p
=
get_loc
(
node_id
);
if
(
rect
.
contains
(
p
+
point
(
1
,
0
)))
{
if
(
idx
==
0
)
return
node_id
+
1
;
--
idx
;
}
if
(
rect
.
contains
(
p
-
point
(
1
,
0
)))
{
if
(
idx
==
0
)
return
node_id
-
1
;
--
idx
;
}
if
(
rect
.
contains
(
p
+
point
(
0
,
1
)))
{
if
(
idx
==
0
)
return
node_id
+
nc
;
--
idx
;
}
return
node_id
-
nc
;
}
void
set_label
(
const
unsigned
long
&
idx
,
node_label
value
)
{
++
count
;
labels
(
idx
)
=
value
;
}
node_label
get_label
(
const
unsigned
long
&
idx
)
const
{
++
count
;
return
labels
(
idx
);
}
value_type
factor_value
(
unsigned
long
idx
,
bool
value
)
const
{
++
count
;
DLIB_TEST
(
idx
<
(
unsigned
long
)
number_of_nodes
());
if
(
value
)
return
factors1
(
idx
,
0
);
else
return
factors1
(
idx
,
1
);
}
value_type
factor_value_disagreement
(
unsigned
long
idx1
,
unsigned
long
idx2
)
const
{
++
count
;
DLIB_TEST
(
idx1
!=
idx2
);
DLIB_TEST
(
idx1
<
(
unsigned
long
)
number_of_nodes
());
DLIB_TEST
(
idx2
<
(
unsigned
long
)
number_of_nodes
());
// make this function symmetric
if
(
idx1
>
idx2
)
swap
(
idx1
,
idx2
);
DLIB_TEST
(
get_neighbor
(
idx1
,
get_neighbor_idx
(
idx1
,
idx2
))
==
idx2
);
DLIB_TEST
(
get_neighbor
(
idx2
,
get_neighbor_idx
(
idx2
,
idx1
))
==
idx1
);
// the neighbor relationship better be symmetric
DLIB_TEST
(
get_neighbor_idx
(
idx1
,
idx2
)
<
number_of_neighbors
(
idx1
));
DLIB_TEST_MSG
(
get_neighbor_idx
(
idx2
,
idx1
)
<
number_of_neighbors
(
idx2
),
"
\n
idx1: "
<<
idx1
<<
"
\n
idx2: "
<<
idx2
<<
"
\n
get_neighbor_idx(idx2,idx1): "
<<
get_neighbor_idx
(
idx2
,
idx1
)
<<
"
\n
number_of_neighbors(idx2): "
<<
number_of_neighbors
(
idx2
)
<<
"
\n
nr: "
<<
nr
<<
"
\n
nc: "
<<
nc
);
return
factors2
(
idx1
,
get_neighbor_idx
(
idx1
,
idx2
));
}
private
:
point
get_loc
(
const
unsigned
long
&
idx
)
const
{
return
point
(
idx
%
nc
,
idx
/
nc
);
}
};
// ----------------------------------------------------------------------------------------
template
<
typename
potts_model
>
void
brute_force_potts_model
(
potts_model
&
g
)
{
potts_model
m
(
g
);
const
unsigned
long
num
=
(
unsigned
long
)
std
::
pow
(
2
,
m
.
number_of_nodes
());
double
best_score
=
-
std
::
numeric_limits
<
double
>::
infinity
();
for
(
unsigned
long
i
=
0
;
i
<
num
;
++
i
)
{
for
(
unsigned
long
j
=
0
;
j
<
m
.
number_of_nodes
();
++
j
)
{
unsigned
long
T
=
(
1
)
<<
j
;
T
=
(
T
&
i
);
if
(
T
!=
0
)
m
.
set_label
(
j
,
SINK_CUT
);
else
m
.
set_label
(
j
,
SOURCE_CUT
);
}
double
score
=
potts_model_score
(
m
);
if
(
score
>
best_score
)
{
best_score
=
score
;
g
=
m
;
}
}
}
// ----------------------------------------------------------------------------------------
template
<
typename
potts_prob
>
void
impl_test_potts_model
(
potts_prob
&
p
)
{
using
namespace
std
;
double
brute_force_score
;
double
graph_cut_score
;
{
potts_prob
temp
(
p
);
brute_force_potts_model
(
temp
);
for
(
unsigned
long
i
=
0
;
i
<
temp
.
number_of_nodes
();
++
i
)
{
dlog
<<
LTRACE
<<
"node "
<<
i
<<
": "
<<
(
int
)
temp
.
get_label
(
i
);
}
brute_force_score
=
potts_model_score
(
temp
);
dlog
<<
LTRACE
<<
"brute force score: "
<<
brute_force_score
;
}
dlog
<<
LTRACE
<<
"******************"
;
{
potts_prob
temp
(
p
);
find_max_factor_graph_potts
(
temp
);
for
(
unsigned
long
i
=
0
;
i
<
temp
.
number_of_nodes
();
++
i
)
{
dlog
<<
LTRACE
<<
"node "
<<
i
<<
": "
<<
(
int
)
temp
.
get_label
(
i
);
}
graph_cut_score
=
potts_model_score
(
temp
);
dlog
<<
LTRACE
<<
"graph cut score: "
<<
graph_cut_score
;
}
DLIB_TEST_MSG
(
graph_cut_score
==
brute_force_score
,
std
::
abs
(
graph_cut_score
-
brute_force_score
));
dlog
<<
LTRACE
<<
"##################"
;
dlog
<<
LTRACE
<<
"##################"
;
dlog
<<
LTRACE
<<
"##################"
;
}
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
// BASIC MIN CUT STUFF
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
template
<
typename
directed_graph
>
void
brute_force_min_cut
(
directed_graph
&
g
,
unsigned
long
source
,
unsigned
long
sink
)
{
typedef
typename
directed_graph
::
edge_type
edge_weight_type
;
const
unsigned
long
num
=
(
unsigned
long
)
std
::
pow
(
2
,
g
.
number_of_nodes
());
std
::
vector
<
node_label
>
best_cut
(
g
.
number_of_nodes
(),
FREE_NODE
);
edge_weight_type
best_score
=
std
::
numeric_limits
<
edge_weight_type
>::
max
();
for
(
unsigned
long
i
=
0
;
i
<
num
;
++
i
)
{
for
(
unsigned
long
j
=
0
;
j
<
g
.
number_of_nodes
();
++
j
)
{
unsigned
long
T
=
(
1
)
<<
j
;
T
=
(
T
&
i
);
if
(
T
!=
0
)
g
.
node
(
j
).
data
=
SINK_CUT
;
else
g
.
node
(
j
).
data
=
SOURCE_CUT
;
}
// ignore cuts that don't label the source or sink node the way we want.
if
(
g
.
node
(
source
).
data
!=
SOURCE_CUT
||
g
.
node
(
sink
).
data
!=
SINK_CUT
)
continue
;
edge_weight_type
score
=
graph_cut_score
(
g
);
if
(
score
<
best_score
)
{
best_score
=
score
;
for
(
unsigned
long
j
=
0
;
j
<
g
.
number_of_nodes
();
++
j
)
best_cut
[
j
]
=
g
.
node
(
j
).
data
;
}
}
for
(
unsigned
long
j
=
0
;
j
<
g
.
number_of_nodes
();
++
j
)
g
.
node
(
j
).
data
=
best_cut
[
j
];
}
// ----------------------------------------------------------------------------------------
template
<
typename
directed_graph
>
void
print_graph
(
const
directed_graph
&
g
)
{
using
namespace
std
;
dlog
<<
LTRACE
<<
"number of nodes: "
<<
g
.
number_of_nodes
();
for
(
unsigned
long
i
=
0
;
i
<
g
.
number_of_nodes
();
++
i
)
{
for
(
unsigned
long
n
=
0
;
n
<
g
.
node
(
i
).
number_of_children
();
++
n
)
dlog
<<
LTRACE
<<
i
<<
" -("
<<
g
.
node
(
i
).
child_edge
(
n
)
<<
")-> "
<<
g
.
node
(
i
).
child
(
n
).
index
();
}
}
template
<
typename
directed_graph
>
void
copy_edge_weights
(
directed_graph
&
dest
,
const
directed_graph
&
src
)
{
for
(
unsigned
long
i
=
0
;
i
<
src
.
number_of_nodes
();
++
i
)
{
for
(
unsigned
long
n
=
0
;
n
<
src
.
node
(
i
).
number_of_children
();
++
n
)
{
dest
.
node
(
i
).
child_edge
(
n
)
=
src
.
node
(
i
).
child_edge
(
n
);
}
}
}
// ----------------------------------------------------------------------------------------
template
<
typename
graph_type
>
void
pick_random_source_and_sink
(
dlib
::
rand
&
rnd
,
const
graph_type
&
g
,
unsigned
long
&
source
,
unsigned
long
&
sink
)
{
source
=
rnd
.
get_random_32bit_number
()
%
g
.
number_of_nodes
();
sink
=
rnd
.
get_random_32bit_number
()
%
g
.
number_of_nodes
();
while
(
sink
==
source
)
sink
=
rnd
.
get_random_32bit_number
()
%
g
.
number_of_nodes
();
}
// ----------------------------------------------------------------------------------------
template
<
typename
dgraph_type
>
void
make_random_graph
(
dlib
::
rand
&
rnd
,
dgraph_type
&
g
,
unsigned
long
&
source
,
unsigned
long
&
sink
)
{
typedef
typename
dgraph_type
::
edge_type
edge_weight_type
;
g
.
clear
();
const
unsigned
int
num_nodes
=
rnd
.
get_random_32bit_number
()
%
7
+
2
;
g
.
set_number_of_nodes
(
num_nodes
);
const
unsigned
int
num_edges
=
static_cast
<
unsigned
int
>
(
num_nodes
*
(
num_nodes
-
1
)
/
2
*
rnd
.
get_random_double
()
+
0.5
);
// add the right number of randomly selected edges
unsigned
int
count
=
0
;
while
(
count
<
num_edges
)
{
unsigned
long
parent
=
rnd
.
get_random_32bit_number
()
%
g
.
number_of_nodes
();
unsigned
long
child
=
rnd
.
get_random_32bit_number
()
%
g
.
number_of_nodes
();
if
(
parent
!=
child
&&
g
.
has_edge
(
parent
,
child
)
==
false
)
{
++
count
;
g
.
add_edge
(
parent
,
child
);
edge
(
g
,
parent
,
child
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
// have to have edges both ways
swap
(
parent
,
child
);
g
.
add_edge
(
parent
,
child
);
edge
(
g
,
parent
,
child
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
}
}
pick_random_source_and_sink
(
rnd
,
g
,
source
,
sink
);
}
// ----------------------------------------------------------------------------------------
template
<
typename
dgraph_type
>
void
make_random_chain_graph
(
dlib
::
rand
&
rnd
,
dgraph_type
&
g
,
unsigned
long
&
source
,
unsigned
long
&
sink
)
{
typedef
typename
dgraph_type
::
edge_type
edge_weight_type
;
g
.
clear
();
const
unsigned
int
num_nodes
=
rnd
.
get_random_32bit_number
()
%
7
+
2
;
g
.
set_number_of_nodes
(
num_nodes
);
for
(
unsigned
long
i
=
1
;
i
<
g
.
number_of_nodes
();
++
i
)
{
g
.
add_edge
(
i
,
i
-
1
);
g
.
add_edge
(
i
-
1
,
i
);
edge
(
g
,
i
,
i
-
1
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
edge
(
g
,
i
-
1
,
i
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
}
pick_random_source_and_sink
(
rnd
,
g
,
source
,
sink
);
}
// ----------------------------------------------------------------------------------------
template
<
typename
dgraph_type
>
void
make_random_grid_graph
(
dlib
::
rand
&
rnd
,
dgraph_type
&
g
,
unsigned
long
&
source
,
unsigned
long
&
sink
)
/*!
ensures
- makes a grid graph like the kind used for potts models.
!*/
{
typedef
typename
dgraph_type
::
edge_type
edge_weight_type
;
g
.
clear
();
const
long
nr
=
rnd
.
get_random_32bit_number
()
%
2
+
2
;
const
long
nc
=
rnd
.
get_random_32bit_number
()
%
2
+
2
;
g
.
set_number_of_nodes
(
nr
*
nc
+
2
);
const
rectangle
rect
(
0
,
0
,
nc
-
1
,
nr
-
1
);
for
(
long
r
=
0
;
r
<
nr
;
++
r
)
{
for
(
long
c
=
0
;
c
<
nc
;
++
c
)
{
const
point
p
(
c
,
r
);
const
unsigned
long
i
=
p
.
y
()
*
nc
+
p
.
x
();
const
point
n2
(
c
-
1
,
r
);
if
(
rect
.
contains
(
n2
))
{
const
unsigned
long
j
=
n2
.
y
()
*
nc
+
n2
.
x
();
g
.
add_edge
(
i
,
j
);
g
.
add_edge
(
j
,
i
);
edge
(
g
,
i
,
j
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
edge
(
g
,
j
,
i
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
}
const
point
n4
(
c
,
r
-
1
);
if
(
rect
.
contains
(
n4
))
{
const
unsigned
long
j
=
n4
.
y
()
*
nc
+
n4
.
x
();
g
.
add_edge
(
i
,
j
);
g
.
add_edge
(
j
,
i
);
edge
(
g
,
i
,
j
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
edge
(
g
,
j
,
i
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
}
}
}
// use the last two nodes as source and sink. Also connect them to all the other nodes.
source
=
g
.
number_of_nodes
()
-
1
;
sink
=
g
.
number_of_nodes
()
-
2
;
for
(
unsigned
long
i
=
0
;
i
<
g
.
number_of_nodes
()
-
2
;
++
i
)
{
g
.
add_edge
(
i
,
source
);
g
.
add_edge
(
source
,
i
);
g
.
add_edge
(
i
,
sink
);
g
.
add_edge
(
sink
,
i
);
edge
(
g
,
i
,
source
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
edge
(
g
,
source
,
i
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
edge
(
g
,
i
,
sink
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
edge
(
g
,
sink
,
i
)
=
static_cast
<
edge_weight_type
>
(
rnd
.
get_random_double
()
*
50
);
}
}
// ----------------------------------------------------------------------------------------
template
<
typename
min_cut
,
typename
dgraph_type
>
void
run_test_on_graphs
(
const
min_cut
&
mc
,
dgraph_type
&
g1
,
dgraph_type
&
g2
,
unsigned
long
source
,
unsigned
long
sink
)
{
typedef
typename
dgraph_type
::
edge_type
edge_weight_type
;
using
namespace
std
;
dlog
<<
LTRACE
<<
"number of nodes: "
<<
g1
.
number_of_nodes
();
dlog
<<
LTRACE
<<
"is graph connected: "
<<
graph_is_connected
(
g1
);
dlog
<<
LTRACE
<<
"has self loops: "
<<
graph_contains_length_one_cycle
(
g1
);
dlog
<<
LTRACE
<<
"SOURCE_CUT: "
<<
source
;
dlog
<<
LTRACE
<<
"SINK_CUT: "
<<
sink
;
mc
(
g1
,
source
,
sink
);
brute_force_min_cut
(
g2
,
source
,
sink
);
print_graph
(
g1
);
// copy the edge weights from g2 back to g1 so we can compute cut scores
copy_edge_weights
(
g1
,
g2
);
DLIB_TEST
(
g1
.
number_of_nodes
()
==
g2
.
number_of_nodes
());
for
(
unsigned
long
i
=
0
;
i
<
g1
.
number_of_nodes
();
++
i
)
{
dlog
<<
LTRACE
<<
"node "
<<
i
<<
": "
<<
(
int
)
g1
.
node
(
i
).
data
<<
", "
<<
(
int
)
g2
.
node
(
i
).
data
;
if
(
g1
.
node
(
i
).
data
!=
g2
.
node
(
i
).
data
)
{
edge_weight_type
cut_score
=
graph_cut_score
(
g1
);
edge_weight_type
brute_force_score
=
graph_cut_score
(
g2
);
dlog
<<
LTRACE
<<
"graph cut score: "
<<
cut_score
;
dlog
<<
LTRACE
<<
"brute force score: "
<<
brute_force_score
;
if
(
brute_force_score
!=
cut_score
)
print_graph
(
g1
);
DLIB_TEST_MSG
(
brute_force_score
==
cut_score
,
std
::
abs
(
brute_force_score
-
cut_score
));
}
}
}
// ----------------------------------------------------------------------------------------
template
<
typename
min_cut
,
typename
edge_weight_type
>
void
test_graph_cuts
(
dlib
::
rand
&
rnd
)
{
typedef
typename
dlib
::
directed_graph
<
node_label
,
edge_weight_type
>::
kernel_1a_c
dgraph_type
;
// we will create two identical graphs.
dgraph_type
g1
,
g2
;
min_cut
mc
;
unsigned
long
source
,
sink
;
dlib
::
rand
rnd_copy
(
rnd
);
make_random_graph
(
rnd
,
g1
,
source
,
sink
);
make_random_graph
(
rnd_copy
,
g2
,
source
,
sink
);
run_test_on_graphs
(
mc
,
g1
,
g2
,
source
,
sink
);
rnd_copy
=
rnd
;
make_random_grid_graph
(
rnd
,
g1
,
source
,
sink
);
make_random_grid_graph
(
rnd_copy
,
g2
,
source
,
sink
);
run_test_on_graphs
(
mc
,
g1
,
g2
,
source
,
sink
);
rnd_copy
=
rnd
;
make_random_chain_graph
(
rnd
,
g1
,
source
,
sink
);
make_random_chain_graph
(
rnd_copy
,
g2
,
source
,
sink
);
run_test_on_graphs
(
mc
,
g1
,
g2
,
source
,
sink
);
}
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
class
graph_cuts_tester
:
public
tester
{
public
:
graph_cuts_tester
(
)
:
tester
(
"test_graph_cuts"
,
"Runs tests on the graph cuts tools."
)
{}
dlib
::
rand
rnd
;
void
perform_test
(
)
{
for
(
int
i
=
0
;
i
<
1000
;
++
i
)
{
print_spinner
();
dlog
<<
LTRACE
<<
"test_grpah_cuts<short> iter: "
<<
i
;
test_graph_cuts
<
min_cut
,
short
>
(
rnd
);
print_spinner
();
dlog
<<
LTRACE
<<
"test_grpah_cuts<double> iter: "
<<
i
;
test_graph_cuts
<
min_cut
,
double
>
(
rnd
);
}
for
(
int
k
=
0
;
k
<
300
;
++
k
)
{
dlog
<<
LTRACE
<<
"image_potts_problem iter "
<<
k
;
print_spinner
();
image_potts_problem
p
(
3
,
3
,
rnd
);
impl_test_potts_model
(
p
);
}
for
(
int
k
=
0
;
k
<
300
;
++
k
)
{
dlog
<<
LTRACE
<<
"dense_potts_problem iter "
<<
k
;
print_spinner
();
dense_potts_problem
p
(
6
,
rnd
);
impl_test_potts_model
(
p
);
}
}
}
a
;
}
dlib/test/makefile
View file @
ea02f4d4
...
@@ -60,6 +60,7 @@ SRC += find_max_factor_graph_nmplp.cpp
...
@@ -60,6 +60,7 @@ SRC += find_max_factor_graph_nmplp.cpp
SRC
+=
find_max_factor_graph_viterbi.cpp
SRC
+=
find_max_factor_graph_viterbi.cpp
SRC
+=
geometry.cpp
SRC
+=
geometry.cpp
SRC
+=
graph.cpp
SRC
+=
graph.cpp
SRC
+=
graph_cuts.cpp
SRC
+=
hash.cpp
SRC
+=
hash.cpp
SRC
+=
hash_map.cpp
SRC
+=
hash_map.cpp
SRC
+=
hash_set.cpp
SRC
+=
hash_set.cpp
...
...
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