Added max runtime option to object detector trainer API in python.

tools/python/src/object_detection.cpp

@@ -177,6 +177,8 @@ process take significantly longer, so be patient when using it."
             process take significantly longer, so be patient when using it.
             !*/
                                                )
+        .def_readwrite("max_runtime_seconds", &type::max_runtime_seconds,
+            "Don't let the solver run for longer than this many seconds.")
         .def_readwrite("C", &type::C,
 "C is the usual SVM C regularization parameter.  So it is passed to \n\
 structural_object_detection_trainer::set_c().  Larger values of C \n\
@@ -407,13 +409,23 @@ ensures \n\
 bunch of other simple_object_detectors.  It essentially packs them together \n\
 so that when you run the detector it's like calling run_multiple().  Except \n\
 in this case the non-max suppression is applied to them all as a group.  So \n\
-unlike run_multiple(), each detector competes in the non-max suppression." 
+unlike run_multiple(), each detector competes in the non-max suppression. \n\
+ \n\
+Also, the non-max suppression settings used for this whole thing are \n\
+the settings used by detectors[0].  So if you have a preference,  \n\
+put the detector that uses the type of non-max suppression you like first \n\
+in the list." 
             /*!
                 This version of the constructor builds a simple_object_detector from a
                 bunch of other simple_object_detectors.  It essentially packs them together
                 so that when you run the detector it's like calling run_multiple().  Except
                 in this case the non-max suppression is applied to them all as a group.  So
                 unlike run_multiple(), each detector competes in the non-max suppression.
+
+                Also, the non-max suppression settings used for this whole thing are
+                the settings used by detectors[0].  So if you have a preference, 
+                put the detector that uses the type of non-max suppression you like first
+                in the list.
             !*/
             )
         .def(py::init(&load_object_from_file<type>),

tools/python/src/simple_object_detector.h

@@ -36,6 +36,7 @@ namespace dlib
             epsilon = 0.01;
             upsample_limit = 2;
             nuclear_norm_regularization_strength = 0;
+            max_runtime_seconds = 86400*365*100; // 100 years
         }
 
         bool be_verbose;
@@ -46,7 +47,7 @@ namespace dlib
         double epsilon;
         unsigned long upsample_limit;
         double nuclear_norm_regularization_strength;
-
+        double max_runtime_seconds;
     };
 
     inline std::string print_simple_object_detector_training_options(const simple_object_detector_training_options& o)
@@ -59,6 +60,7 @@ namespace dlib
             << "detection_window_size=" << o.detection_window_size << ", "
             << "C=" << o.C << ", "
             << "epsilon=" << o.epsilon << ", "
+            << "max_runtime_seconds=" << o.max_runtime_seconds << ", "
             << "upsample_limit=" << o.upsample_limit << ", "
             << "nuclear_norm_regularization_strength=" << o.nuclear_norm_regularization_strength 
             << ")";
@@ -162,6 +164,8 @@ namespace dlib
             throw error("Invalid C value given to train_simple_object_detector(), C must be > 0.");
         if (options.epsilon <= 0)
             throw error("Invalid epsilon value given to train_simple_object_detector(), epsilon must be > 0.");
+        if (options.max_runtime_seconds <= 0)
+            throw error("Invalid max_runtime_seconds value given to train_simple_object_detector(), max_runtime_seconds must be > 0.");
 
         if (options.nuclear_norm_regularization_strength < 0)
             throw error("Invalid nuclear_norm_regularization_strength value given to train_simple_object_detector(), it must be must be >= 0.");
@@ -184,6 +188,7 @@ namespace dlib
         trainer.set_num_threads(options.num_threads);  
         trainer.set_c(options.C);
         trainer.set_epsilon(options.epsilon);
+        trainer.set_max_runtime(std::chrono::milliseconds((int64_t)std::round(options.max_runtime_seconds*1000)));
         if (options.be_verbose)
         {
             std::cout << "Training with C: " << options.C << std::endl;