mirror of https://github.com/davisking/dlib.git
Renamed loss_binary_mmod_ to loss_mmod_
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d54597230b
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@ -443,7 +443,7 @@ namespace dlib
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// ----------------------------------------------------------------------------------------
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// ----------------------------------------------------------------------------------------
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class loss_binary_mmod_
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class loss_mmod_
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{
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{
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struct intermediate_detection
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struct intermediate_detection
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{
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{
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@ -470,9 +470,9 @@ namespace dlib
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typedef std::vector<mmod_rect> label_type;
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typedef std::vector<mmod_rect> label_type;
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loss_binary_mmod_() {}
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loss_mmod_() {}
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loss_binary_mmod_(mmod_options options_) : options(options_) {}
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loss_mmod_(mmod_options options_) : options(options_) {}
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const mmod_options& get_options (
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const mmod_options& get_options (
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) const { return options; }
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) const { return options; }
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@ -671,32 +671,32 @@ namespace dlib
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}
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}
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friend void serialize(const loss_binary_mmod_& item, std::ostream& out)
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friend void serialize(const loss_mmod_& item, std::ostream& out)
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{
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{
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serialize("loss_binary_mmod_", out);
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serialize("loss_mmod_", out);
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serialize(item.options, out);
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serialize(item.options, out);
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}
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}
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friend void deserialize(loss_binary_mmod_& item, std::istream& in)
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friend void deserialize(loss_mmod_& item, std::istream& in)
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{
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{
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std::string version;
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std::string version;
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deserialize(version, in);
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deserialize(version, in);
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if (version != "loss_binary_mmod_")
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if (version != "loss_mmod_")
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throw serialization_error("Unexpected version found while deserializing dlib::loss_binary_mmod_.");
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throw serialization_error("Unexpected version found while deserializing dlib::loss_mmod_.");
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deserialize(item.options, in);
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deserialize(item.options, in);
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}
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}
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friend std::ostream& operator<<(std::ostream& out, const loss_binary_mmod_& )
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friend std::ostream& operator<<(std::ostream& out, const loss_mmod_& )
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{
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{
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// TODO, add options fields
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// TODO, add options fields
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out << "loss_binary_mmod";
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out << "loss_mmod";
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return out;
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return out;
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}
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}
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friend void to_xml(const loss_binary_mmod_& /*item*/, std::ostream& out)
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friend void to_xml(const loss_mmod_& /*item*/, std::ostream& out)
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{
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{
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// TODO, add options fields
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// TODO, add options fields
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out << "<loss_binary_mmod/>";
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out << "<loss_mmod/>";
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}
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}
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private:
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private:
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@ -857,7 +857,7 @@ namespace dlib
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};
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};
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template <typename SUBNET>
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template <typename SUBNET>
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using loss_binary_mmod = add_loss_layer<loss_binary_mmod_, SUBNET>;
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using loss_mmod = add_loss_layer<loss_mmod_, SUBNET>;
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// ----------------------------------------------------------------------------------------
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// ----------------------------------------------------------------------------------------
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@ -359,7 +359,7 @@ namespace dlib
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{
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{
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/*!
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/*!
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WHAT THIS OBJECT REPRESENTS
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WHAT THIS OBJECT REPRESENTS
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This object contains all the parameters that control the behavior of loss_binary_mmod_.
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This object contains all the parameters that control the behavior of loss_mmod_.
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!*/
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!*/
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public:
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public:
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@ -419,7 +419,7 @@ namespace dlib
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// ----------------------------------------------------------------------------------------
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// ----------------------------------------------------------------------------------------
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class loss_binary_mmod_
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class loss_mmod_
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{
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{
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/*!
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/*!
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WHAT THIS OBJECT REPRESENTS
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WHAT THIS OBJECT REPRESENTS
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@ -438,21 +438,21 @@ namespace dlib
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- image_space_to_tensor_space()
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- image_space_to_tensor_space()
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A reference implementation of them and their definitions can be found in
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A reference implementation of them and their definitions can be found in
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the input_rgb_image_pyramid object, which is the recommended input layer to
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the input_rgb_image_pyramid object, which is the recommended input layer to
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be used with loss_binary_mmod_.
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be used with loss_mmod_.
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!*/
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!*/
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public:
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public:
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typedef std::vector<mmod_rect> label_type;
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typedef std::vector<mmod_rect> label_type;
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loss_binary_mmod_(
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loss_mmod_(
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);
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);
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/*!
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/*!
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ensures
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ensures
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- #get_options() == mmod_options()
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- #get_options() == mmod_options()
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!*/
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!*/
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loss_binary_mmod_(
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loss_mmod_(
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mmod_options options_
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mmod_options options_
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);
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);
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/*!
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/*!
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@ -517,7 +517,7 @@ namespace dlib
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};
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};
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template <typename SUBNET>
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template <typename SUBNET>
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using loss_binary_mmod = add_loss_layer<loss_binary_mmod_, SUBNET>;
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using loss_mmod = add_loss_layer<loss_mmod_, SUBNET>;
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// ----------------------------------------------------------------------------------------
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// ----------------------------------------------------------------------------------------
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@ -15,7 +15,7 @@ namespace dlib
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typename image_array_type
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typename image_array_type
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>
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>
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const matrix<double,1,3> test_object_detection_function (
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const matrix<double,1,3> test_object_detection_function (
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loss_binary_mmod<SUBNET>& detector,
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loss_mmod<SUBNET>& detector,
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const image_array_type& images,
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const image_array_type& images,
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const std::vector<std::vector<mmod_rect>>& truth_dets,
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const std::vector<std::vector<mmod_rect>>& truth_dets,
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const test_box_overlap& overlap_tester = test_box_overlap(),
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const test_box_overlap& overlap_tester = test_box_overlap(),
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@ -14,7 +14,7 @@ namespace dlib
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typename image_array_type
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typename image_array_type
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>
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>
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const matrix<double,1,3> test_object_detection_function (
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const matrix<double,1,3> test_object_detection_function (
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loss_binary_mmod<SUBNET>& detector,
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loss_mmod<SUBNET>& detector,
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const image_array_type& images,
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const image_array_type& images,
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const std::vector<std::vector<mmod_rect>>& truth_dets,
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const std::vector<std::vector<mmod_rect>>& truth_dets,
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const test_box_overlap& overlap_tester = test_box_overlap(),
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const test_box_overlap& overlap_tester = test_box_overlap(),
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@ -27,7 +27,7 @@ namespace dlib
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and it must contain objects which can be accepted by detector().
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and it must contain objects which can be accepted by detector().
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ensures
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ensures
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- This function is just like the test_object_detection_function() for
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- This function is just like the test_object_detection_function() for
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object_detector's except it runs on CNNs that use loss_binary_mmod.
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object_detector's except it runs on CNNs that use loss_mmod.
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- Tests the given detector against the supplied object detection problem and
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- Tests the given detector against the supplied object detection problem and
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returns the precision, recall, and average precision. Note that the task is
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returns the precision, recall, and average precision. Note that the task is
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to predict, for each images[i], the set of object locations given by
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to predict, for each images[i], the set of object locations given by
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@ -145,7 +145,7 @@ namespace dlib
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/*!
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/*!
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WHAT THIS OBJECT REPRESENTS
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WHAT THIS OBJECT REPRESENTS
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This is a simple struct that is used to give training data and receive detections
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This is a simple struct that is used to give training data and receive detections
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from the Max-Margin Object Detection loss layer loss_binary_mmod_ object.
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from the Max-Margin Object Detection loss layer loss_mmod_ object.
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!*/
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!*/
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mmod_rect() = default;
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mmod_rect() = default;
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