I just made the way the template is declared for the pick_initial_centers()

function a little more flexible.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403427

dlib/svm/kkmeans.h

@@ -295,13 +295,14 @@ namespace dlib
     };
 
     template <
-        typename vector_type, 
+        typename vector_type1, 
+        typename vector_type2, 
         typename kernel_type
         >
     void pick_initial_centers(
         long num_centers, 
-        vector_type& centers, 
-        const vector_type& samples, 
+        vector_type1& centers, 
+        const vector_type2& samples, 
         const kernel_type& k, 
         double percentile = 0.01
     )

dlib/svm/kkmeans_abstract.h

@@ -204,13 +204,14 @@ namespace dlib
 // ----------------------------------------------------------------------------------------
 
     template <
-        typename vector_type, 
+        typename vector_type1, 
+        typename vector_type2, 
         typename kernel_type
         >
     void pick_initial_centers(
         long num_centers, 
-        vector_type& centers, 
-        const vector_type& samples, 
+        vector_type1& centers, 
+        const vector_type2& samples, 
         const kernel_type& k, 
         double percentile = 0.01
     );
@@ -219,7 +220,8 @@ namespace dlib
             - num_centers > 1
             - 0 <= percentile < 1
             - samples.size() > 1
-            - vector_type == something with an interface compatible with std::vector
+            - vector_type1 == something with an interface compatible with std::vector
+            - vector_type2 == something with an interface compatible with std::vector
             - k(samples[0],samples[0]) must be a valid expression that returns a double
         ensures
             - finds num_centers candidate cluster centers in the data in the samples