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Renamed loss_binary_mmod_ to loss_mmod_

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This commit is contained in:
Davis King 2016-09-05 09:54:31 -04:00
parent d54597230b
commit 6cd2042dd0
5 changed files with 23 additions and 23 deletions
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26
dlib/dnn/loss.h
View File

@ -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>;
// ----------------------------------------------------------------------------------------

12
dlib/dnn/loss_abstract.h
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@ -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>;
// ----------------------------------------------------------------------------------------

2
dlib/dnn/validation.h
View File

@ -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(),

4
dlib/dnn/validation_abstract.h
View File

@ -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

2
dlib/image_processing/full_object_detection_abstract.h
View File

@ -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;