Nicer way of instantiating indexes based on runtime values

src/cpp/flann/algorithms/all_indices.h

@@ -72,7 +72,7 @@ struct index_creator
             nnIndex = new KDTreeCuda3dIndex<Distance>(dataset, params, distance);
             break;
 		#endif
-			
+
         case FLANN_INDEX_KMEANS:
             nnIndex = new KMeansIndex<Distance>(dataset, params, distance);
             break;
@@ -151,12 +151,133 @@ struct index_creator<FalseType,FalseType,Distance>
     }
 };
 
+
+
+/**
+ * enable_if sfinae helper
+ */
+template<bool, typename T = void> struct enable_if{};
+template<typename T> struct enable_if<true,T> { typedef T type; };
+
+/**
+ * disable_if sfinae helper
+ */
+template<bool, typename T> struct disable_if{ typedef T type; };
+template<typename T> struct disable_if<true,T> { };
+
+/**
+ * Check if two type are the same
+ */
+template <typename T, typename U>
+struct same_type
+{
+    enum {value = false};
+};
+
+template<typename T>
+struct same_type<T,T>
+{
+    enum {value = true};
+};
+
+
+/**
+ * Checks if an index and a distance can be used together
+ */
+template<template <typename> class Index, typename Distance, typename ElementType>
+struct valid_combination
+{
+
+#define HAS_MEMBER(member) \
+    template<typename T> \
+    struct member { \
+        typedef char No; \
+        typedef long Yes; \
+        template<typename C> static Yes test( typename C::member* ); \
+        template<typename C> static No test( ... ); \
+        enum { value = sizeof (test<T>(0))==sizeof(Yes) }; \
+    };
+
+	HAS_MEMBER(needs_kdtree_distance)
+	HAS_MEMBER(needs_vector_space_distance)
+	HAS_MEMBER(is_kdtree_distance)
+	HAS_MEMBER(is_vector_space_distance)
+
+    static const bool value = same_type<ElementType,typename Distance::ElementType>::value &&
+    				(!needs_kdtree_distance<Index<Distance> >::value || is_kdtree_distance<Distance>::value) &&
+    				(!needs_vector_space_distance<Index<Distance> >::value || is_vector_space_distance<Distance>::value);
+
+};
+
+
+/*********************************************************
+ * Create index
+ **********************************************************/
+template <template<typename> class Index, typename Distance, typename T>
+NNIndex<Distance>* create_index_(flann::Matrix<T> data, const flann::IndexParams& params, const Distance& distance,
+		typename enable_if<valid_combination<Index,Distance,T>::value,void>::type* = 0)
+{
+    return new Index<Distance>(data, params);
+}
+
+template <template<typename> class Index, typename Distance, typename T>
+NNIndex<Distance>* create_index_(flann::Matrix<T> data, const flann::IndexParams& params, const Distance& distance,
+		typename disable_if<valid_combination<Index,Distance,T>::value,void>::type* = 0)
+{
+    return NULL;
+}
+
+
 template<typename Distance>
 NNIndex<Distance>* create_index_by_type(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance)
 {
-    return index_creator<typename Distance::is_kdtree_distance,
-                         typename Distance::is_vector_space_distance,
-                         Distance>::create(dataset, params,distance);
+	typedef typename Distance::ElementType ElementType;
+	flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm");
+
+    NNIndex<Distance>* nnIndex;
+    switch (index_type) {
+    case FLANN_INDEX_LINEAR:
+        nnIndex = create_index_<LinearIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    case FLANN_INDEX_KDTREE_SINGLE:
+        nnIndex = create_index_<KDTreeSingleIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    case FLANN_INDEX_KDTREE:
+        nnIndex = create_index_<KDTreeIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+		//! #define this symbol before including flann.h to enable GPU search algorithms. But you have
+		//! to link libflann_cuda then!
+	#ifdef FLANN_USE_CUDA
+	case FLANN_INDEX_KDTREE_CUDA:
+        nnIndex = create_index_<KDTreeCuda3dIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+	#endif
+
+    case FLANN_INDEX_KMEANS:
+        nnIndex = create_index_<KMeansIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    case FLANN_INDEX_COMPOSITE:
+        nnIndex = create_index_<CompositeIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    case FLANN_INDEX_AUTOTUNED:
+        nnIndex = create_index_<AutotunedIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    case FLANN_INDEX_HIERARCHICAL:
+        nnIndex = create_index_<HierarchicalClusteringIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    case FLANN_INDEX_LSH:
+        nnIndex = create_index_<LshIndex,Distance,ElementType>(dataset, params, distance);
+        break;
+    default:
+        throw FLANNException("Unknown index type");
+    }
+
+    if (nnIndex==NULL) {
+    	throw FLANNException("Invalid index/distance combination");
+    }
+    return nnIndex;
+
+
 }
 
 }

src/cpp/flann/algorithms/autotuned_index.h

@@ -73,6 +73,8 @@ public:
     typedef typename Distance::ElementType ElementType;
     typedef typename Distance::ResultType DistanceType;
 
+    typedef bool needs_kdtree_distance;
+
     AutotunedIndex(const Matrix<ElementType>& inputData, const IndexParams& params = AutotunedIndexParams(), Distance d = Distance()) :
         dataset_(inputData), distance_(d)
     {

src/cpp/flann/algorithms/dist.h

@@ -97,8 +97,7 @@ class FalseType
 template<class T>
 struct L2_Simple
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -130,8 +129,7 @@ struct L2_Simple
 template<class T>
 struct L2
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -195,8 +193,7 @@ struct L2
 template<class T>
 struct L1
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -252,8 +249,7 @@ struct L1
 template<class T>
 struct MinkowskiDistance
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -316,8 +312,7 @@ struct MinkowskiDistance
 template<class T>
 struct MaxDistance
 {
-    typedef FalseType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_vector_space_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -373,9 +368,6 @@ struct MaxDistance
  */
 struct HammingLUT
 {
-    typedef FalseType is_kdtree_distance;
-    typedef FalseType is_vector_space_distance;
-
     typedef unsigned char ElementType;
     typedef int ResultType;
 
@@ -473,12 +465,8 @@ struct HammingLUT
  * That code was taken from brief.cpp in OpenCV
  */
 template<class T>
-struct Hamming
+struct HammingPopcnt
 {
-    typedef FalseType is_kdtree_distance;
-    typedef FalseType is_vector_space_distance;
-
-
     typedef T ElementType;
     typedef int ResultType;
 
@@ -535,11 +523,8 @@ struct Hamming
 };
 
 template<typename T>
-struct Hamming2
+struct Hamming
 {
-    typedef FalseType is_kdtree_distance;
-    typedef FalseType is_vector_space_distance;
-
     typedef T ElementType;
     typedef unsigned int ResultType;
 
@@ -594,8 +579,7 @@ struct Hamming2
 template<class T>
 struct HistIntersectionDistance
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -649,8 +633,7 @@ struct HistIntersectionDistance
 template<class T>
 struct HellingerDistance
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -697,8 +680,7 @@ struct HellingerDistance
 template<class T>
 struct ChiSquareDistance
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;
@@ -751,8 +733,7 @@ struct ChiSquareDistance
 template<class T>
 struct KL_Divergence
 {
-    typedef TrueType is_kdtree_distance;
-    typedef TrueType is_vector_space_distance;
+    typedef bool is_kdtree_distance;
 
     typedef T ElementType;
     typedef typename Accumulator<T>::Type ResultType;

src/cpp/flann/algorithms/kdtree_index.h

@@ -73,6 +73,7 @@ public:
     typedef typename Distance::ElementType ElementType;
     typedef typename Distance::ResultType DistanceType;
 
+    typedef bool needs_kdtree_distance;
 
     /**
      * KDTree constructor

src/cpp/flann/algorithms/kmeans_index.h

@@ -84,6 +84,7 @@ public:
     typedef typename Distance::ElementType ElementType;
     typedef typename Distance::ResultType DistanceType;
 
+    typedef bool needs_vector_space_distance;
 
 
     typedef void (KMeansIndex::* centersAlgFunction)(int, int*, int, int*, int&);

src/cpp/flann/defines.h

@@ -86,7 +86,7 @@ enum flann_algorithm_t
     FLANN_INDEX_KDTREE_SINGLE = 4,
     FLANN_INDEX_HIERARCHICAL = 5,
     FLANN_INDEX_LSH = 6,
-		FLANN_INDEX_KDTREE_CUDA = 7,
+    FLANN_INDEX_KDTREE_CUDA = 7,
     FLANN_INDEX_SAVED = 254,
     FLANN_INDEX_AUTOTUNED = 255,
 
@@ -137,6 +137,9 @@ enum flann_distance_t
     FLANN_DIST_CS         = 7,
     FLANN_DIST_KULLBACK_LEIBLER  = 8,
     FLANN_DIST_KL                = 8,
+    FLANN_DIST_HAMMING         	= 9,
+    FLANN_DIST_HAMMING_LUT		= 10,
+    FLANN_DIST_HAMMING_POPCNT   = 11,
 
     // deprecated constants, should use the FLANN_DIST_* ones instead
     EUCLIDEAN = 1,

src/cpp/flann/util/any.h

@@ -22,8 +22,9 @@ namespace cdiggins
 namespace anyimpl
 {
 
-struct bad_any_cast
+struct bad_any_cast : public std::runtime_error
 {
+	bad_any_cast() : std::runtime_error("Cannot convert 'any' value") { }
 };
 
 struct empty_any
@@ -146,7 +147,7 @@ base_any_policy* get_policy()
 
 class any
 {
-	typedef any any_t;
+	typedef any any_t; // workaround for the NVCC compiler under windows
 private:
     // fields
     anyimpl::base_any_policy* policy;

src/cpp/flann/util/result_set.h

@@ -256,7 +256,7 @@ public:
             {
                 // Check for duplicate indices
                 size_t j = i - 1;
-                while ((j >= 0) && (dist_index_[j].dist_ == dist)) {
+                while (dist_index_[j].dist_ == dist) {
                     if (dist_index_[j].index_ == index) {
                         return;
                     }