Fixed incorrect requires clause on the cross_validate_trainer() and

cross_validate_trainer_threaded() routines.

dlib/svm/svm.h

@@ -420,10 +420,10 @@ namespace dlib
 
         // make sure requires clause is not broken
         DLIB_ASSERT(is_binary_classification_problem(x,y) == true &&
-                    1 < folds && folds <= x.nr(),
+                    1 < folds && folds <= std::min(sum(y>0),sum(y<0)),
             "\tmatrix cross_validate_trainer()"
             << "\n\t invalid inputs were given to this function"
-            << "\n\t x.nr(): " << x.nr() 
+            << "\n\t std::min(sum(y>0),sum(y<0)): " << std::min(sum(y>0),sum(y<0))
             << "\n\t folds:  " << folds 
             << "\n\t is_binary_classification_problem(x,y): " << ((is_binary_classification_problem(x,y))? "true":"false")
             );

dlib/svm/svm_abstract.h

@@ -369,7 +369,8 @@ namespace dlib
     /*!
         requires
             - is_binary_classification_problem(x,y) == true
-            - 1 < folds <= x.nr()
+            - 1 < folds <= std::min(sum(y>0),sum(y<0))
+              (e.g. There must be at least as many examples of each class as there are folds)
             - trainer_type == some kind of binary classification trainer object (e.g. svm_nu_trainer)
         ensures
             - performs k-fold cross validation by using the given trainer to solve the

dlib/svm/svm_threaded.h

@@ -94,11 +94,11 @@ namespace dlib
 
         // make sure requires clause is not broken
         DLIB_ASSERT(is_binary_classification_problem(x,y) == true &&
-                    1 < folds && folds <= x.nr() &&
+                    1 < folds && folds <= std::min(sum(y>0),sum(y<0)) &&
                     num_threads > 0,
             "\tmatrix cross_validate_trainer()"
             << "\n\t invalid inputs were given to this function"
-            << "\n\t x.nr(): " << x.nr() 
+            << "\n\t std::min(sum(y>0),sum(y<0)): " << std::min(sum(y>0),sum(y<0))
             << "\n\t folds:  " << folds 
             << "\n\t num_threads:  " << num_threads 
             << "\n\t is_binary_classification_problem(x,y): " << ((is_binary_classification_problem(x,y))? "true":"false")

dlib/svm/svm_threaded_abstract.h

@@ -28,7 +28,8 @@ namespace dlib
     /*!
         requires
             - is_binary_classification_problem(x,y) == true
-            - 1 < folds <= x.nr()
+            - 1 < folds <= std::min(sum(y>0),sum(y<0))
+              (e.g. There must be at least as many examples of each class as there are folds)
             - trainer_type == some kind of trainer object (e.g. svm_nu_trainer)
             - num_threads > 0
         ensures