Made python svm struct interface work with sparse vectors

tools/python/src/svm_struct.cpp

@@ -13,10 +13,15 @@ using namespace dlib;
 using namespace std;
 using namespace boost::python;
 
-class svm_struct_dense : public structural_svm_problem<matrix<double,0,1> >
+template <typename psi_type>
+class svm_struct_prob : public structural_svm_problem<matrix<double,0,1>, psi_type>
 {
+    typedef structural_svm_problem<matrix<double,0,1>, psi_type> base;
+    typedef typename base::feature_vector_type feature_vector_type;
+    typedef typename base::matrix_type matrix_type;
+    typedef typename base::scalar_type scalar_type;
 public:
-    svm_struct_dense (
+    svm_struct_prob (
         object& problem_,
         long num_dimensions_,
         long num_samples_
@@ -71,16 +76,8 @@ private:
 
 // ----------------------------------------------------------------------------------------
 
-/*
-class svm_struct_sparse : public structural_svm_problem<matrix<double,0,1>, 
-                                    std::vector<std::pair<unsigned long,double> >
-{
-};
-*/
-
-// ----------------------------------------------------------------------------------------
-
-matrix<double,0,1> solve_structural_svm_problem(
+template <typename psi_type>
+matrix<double,0,1> solve_structural_svm_problem_impl(
     object problem
 )
 {
@@ -101,6 +98,8 @@ matrix<double,0,1> solve_structural_svm_problem(
     const long num_samples = extract<long>(problem.attr("num_samples"));
     const long num_dimensions = extract<long>(problem.attr("num_dimensions"));
 
+    pyassert(num_samples > 0, "You can't train a Structural-SVM if you don't have any training samples.");
+
     if (be_verbose)
     {
         cout << "C:              " << C << endl;
@@ -113,8 +112,7 @@ matrix<double,0,1> solve_structural_svm_problem(
         cout << endl;
     }
 
-
-    svm_struct_dense prob(problem, num_dimensions, num_samples);
+    svm_struct_prob<psi_type> prob(problem, num_dimensions, num_samples);
     prob.set_c(C);
     prob.set_epsilon(eps);
     prob.set_max_cache_size(max_cache_size);
@@ -132,6 +130,20 @@ matrix<double,0,1> solve_structural_svm_problem(
 
 // ----------------------------------------------------------------------------------------
 
+matrix<double,0,1> solve_structural_svm_problem(
+    object problem
+)
+{
+    // Check if the python code is using sparse or dense vectors to represent PSI()
+    extract<matrix<double,0,1> > isdense(problem.attr("get_truth_joint_feature_vector")(0));
+    if (isdense.check())
+        return solve_structural_svm_problem_impl<matrix<double,0,1> >(problem);
+    else
+        return solve_structural_svm_problem_impl<std::vector<std::pair<unsigned long,double> > >(problem);
+}
+
+// ----------------------------------------------------------------------------------------
+
 void bind_svm_struct()
 {
     using boost::python::arg;