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钟尚武
dlib
Commits
6cd2042d
Commit
6cd2042d
authored
Sep 05, 2016
by
Davis King
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Plain Diff
Renamed loss_binary_mmod_ to loss_mmod_
parent
d5459723
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5 changed files
with
23 additions
and
23 deletions
+23
-23
loss.h
dlib/dnn/loss.h
+13
-13
loss_abstract.h
dlib/dnn/loss_abstract.h
+6
-6
validation.h
dlib/dnn/validation.h
+1
-1
validation_abstract.h
dlib/dnn/validation_abstract.h
+2
-2
full_object_detection_abstract.h
dlib/image_processing/full_object_detection_abstract.h
+1
-1
No files found.
dlib/dnn/loss.h
View file @
6cd2042d
...
...
@@ -443,7 +443,7 @@ namespace dlib
// ----------------------------------------------------------------------------------------
class
loss_
binary_
mmod_
class
loss_mmod_
{
struct
intermediate_detection
{
...
...
@@ -470,9 +470,9 @@ namespace dlib
typedef
std
::
vector
<
mmod_rect
>
label_type
;
loss_
binary_
mmod_
()
{}
loss_mmod_
()
{}
loss_
binary_
mmod_
(
mmod_options
options_
)
:
options
(
options_
)
{}
loss_mmod_
(
mmod_options
options_
)
:
options
(
options_
)
{}
const
mmod_options
&
get_options
(
)
const
{
return
options
;
}
...
...
@@ -671,32 +671,32 @@ namespace dlib
}
friend
void
serialize
(
const
loss_
binary_
mmod_
&
item
,
std
::
ostream
&
out
)
friend
void
serialize
(
const
loss_mmod_
&
item
,
std
::
ostream
&
out
)
{
serialize
(
"loss_
binary_
mmod_"
,
out
);
serialize
(
"loss_mmod_"
,
out
);
serialize
(
item
.
options
,
out
);
}
friend
void
deserialize
(
loss_
binary_
mmod_
&
item
,
std
::
istream
&
in
)
friend
void
deserialize
(
loss_mmod_
&
item
,
std
::
istream
&
in
)
{
std
::
string
version
;
deserialize
(
version
,
in
);
if
(
version
!=
"loss_
binary_
mmod_"
)
throw
serialization_error
(
"Unexpected version found while deserializing dlib::loss_
binary_
mmod_."
);
if
(
version
!=
"loss_mmod_"
)
throw
serialization_error
(
"Unexpected version found while deserializing dlib::loss_mmod_."
);
deserialize
(
item
.
options
,
in
);
}
friend
std
::
ostream
&
operator
<<
(
std
::
ostream
&
out
,
const
loss_
binary_
mmod_
&
)
friend
std
::
ostream
&
operator
<<
(
std
::
ostream
&
out
,
const
loss_mmod_
&
)
{
// TODO, add options fields
out
<<
"loss_
binary_
mmod"
;
out
<<
"loss_mmod"
;
return
out
;
}
friend
void
to_xml
(
const
loss_
binary_
mmod_
&
/*item*/
,
std
::
ostream
&
out
)
friend
void
to_xml
(
const
loss_mmod_
&
/*item*/
,
std
::
ostream
&
out
)
{
// TODO, add options fields
out
<<
"<loss_
binary_
mmod/>"
;
out
<<
"<loss_mmod/>"
;
}
private
:
...
...
@@ -857,7 +857,7 @@ namespace dlib
};
template
<
typename
SUBNET
>
using
loss_
binary_mmod
=
add_loss_layer
<
loss_binary
_mmod_
,
SUBNET
>
;
using
loss_
mmod
=
add_loss_layer
<
loss
_mmod_
,
SUBNET
>
;
// ----------------------------------------------------------------------------------------
...
...
dlib/dnn/loss_abstract.h
View file @
6cd2042d
...
...
@@ -359,7 +359,7 @@ namespace dlib
{
/*!
WHAT THIS OBJECT REPRESENTS
This object contains all the parameters that control the behavior of loss_
binary_
mmod_.
This object contains all the parameters that control the behavior of loss_mmod_.
!*/
public
:
...
...
@@ -419,7 +419,7 @@ namespace dlib
// ----------------------------------------------------------------------------------------
class
loss_
binary_
mmod_
class
loss_mmod_
{
/*!
WHAT THIS OBJECT REPRESENTS
...
...
@@ -438,21 +438,21 @@ namespace dlib
- image_space_to_tensor_space()
A reference implementation of them and their definitions can be found in
the input_rgb_image_pyramid object, which is the recommended input layer to
be used with loss_
binary_
mmod_.
be used with loss_mmod_.
!*/
public
:
typedef
std
::
vector
<
mmod_rect
>
label_type
;
loss_
binary_
mmod_
(
loss_mmod_
(
);
/*!
ensures
- #get_options() == mmod_options()
!*/
loss_
binary_
mmod_
(
loss_mmod_
(
mmod_options
options_
);
/*!
...
...
@@ -517,7 +517,7 @@ namespace dlib
};
template
<
typename
SUBNET
>
using
loss_
binary_mmod
=
add_loss_layer
<
loss_binary
_mmod_
,
SUBNET
>
;
using
loss_
mmod
=
add_loss_layer
<
loss
_mmod_
,
SUBNET
>
;
// ----------------------------------------------------------------------------------------
...
...
dlib/dnn/validation.h
View file @
6cd2042d
...
...
@@ -15,7 +15,7 @@ namespace dlib
typename
image_array_type
>
const
matrix
<
double
,
1
,
3
>
test_object_detection_function
(
loss_
binary_
mmod
<
SUBNET
>&
detector
,
loss_mmod
<
SUBNET
>&
detector
,
const
image_array_type
&
images
,
const
std
::
vector
<
std
::
vector
<
mmod_rect
>>&
truth_dets
,
const
test_box_overlap
&
overlap_tester
=
test_box_overlap
(),
...
...
dlib/dnn/validation_abstract.h
View file @
6cd2042d
...
...
@@ -14,7 +14,7 @@ namespace dlib
typename
image_array_type
>
const
matrix
<
double
,
1
,
3
>
test_object_detection_function
(
loss_
binary_
mmod
<
SUBNET
>&
detector
,
loss_mmod
<
SUBNET
>&
detector
,
const
image_array_type
&
images
,
const
std
::
vector
<
std
::
vector
<
mmod_rect
>>&
truth_dets
,
const
test_box_overlap
&
overlap_tester
=
test_box_overlap
(),
...
...
@@ -27,7 +27,7 @@ namespace dlib
and it must contain objects which can be accepted by detector().
ensures
- This function is just like the test_object_detection_function() for
object_detector's except it runs on CNNs that use loss_
binary_
mmod.
object_detector's except it runs on CNNs that use loss_mmod.
- Tests the given detector against the supplied object detection problem and
returns the precision, recall, and average precision. Note that the task is
to predict, for each images[i], the set of object locations given by
...
...
dlib/image_processing/full_object_detection_abstract.h
View file @
6cd2042d
...
...
@@ -145,7 +145,7 @@ namespace dlib
/*!
WHAT THIS OBJECT REPRESENTS
This is a simple struct that is used to give training data and receive detections
from the Max-Margin Object Detection loss layer loss_
binary_
mmod_ object.
from the Max-Margin Object Detection loss layer loss_mmod_ object.
!*/
mmod_rect
()
=
default
;
...
...
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