Adding FLANN_ prefix to all logging constants

src/cpp/flann/algorithms/autotuned_index.h

@@ -144,7 +144,7 @@ class AutotunedIndex : public NNIndex<Distance>
     /**
      * Index parameters
      */
-    const AutotunedIndexParams& index_params;
+    const AutotunedIndexParams index_params;
 
     Distance distance;
 public:
@@ -161,9 +161,11 @@ public:
     {
     	if (bestIndex!=NULL) {
     		delete bestIndex;
+            bestIndex = NULL;
     	}
     	if (bestParams!=NULL) {
     		delete bestParams;
+            bestParams = NULL;
     	}
     };
 

src/cpp/flann/algorithms/composite_index.h

@@ -102,7 +102,7 @@ class CompositeIndex : public NNIndex<Distance>
 
     const Matrix<ElementType> dataset;
 
-    const IndexParams& index_params;
+    const CompositeIndexParams index_params;
 
     Distance distance;
 

src/cpp/flann/algorithms/kdtree_index.h

@@ -123,7 +123,7 @@ class KDTreeIndex : public NNIndex<Distance>
 	 */
 	const Matrix<ElementType> dataset;
 
-    const IndexParams& index_params;
+    const KDTreeIndexParams index_params;
 
 	size_t size_;
 	size_t veclen_;

src/cpp/flann/algorithms/kdtree_single_index.h

@@ -102,7 +102,7 @@ class KDTreeSingleIndex : public NNIndex<Distance>
 	 */
 	const Matrix<ElementType> dataset;
 
-    const IndexParams& index_params;
+    const KDTreeSingleIndexParams index_params;
 
 	size_t size_;
 	size_t veclen_;

src/cpp/flann/algorithms/kmeans_index.h

@@ -134,7 +134,7 @@ class KMeansIndex : public NNIndex<Distance>
 	 */
     const Matrix<ElementType> dataset;
 
-    const IndexParams& index_params;
+    const KMeansIndexParams index_params;
 
     /**
     * Number of features in the dataset.

src/cpp/flann/algorithms/linear_index.h

@@ -65,7 +65,7 @@ class LinearIndex : public NNIndex<Distance>
 	typedef typename Distance::ResultType DistanceType;
 
 	const Matrix<ElementType> dataset;
-	const LinearIndexParams& index_params;
+	const LinearIndexParams index_params;
 
 	Distance distance;
 

src/cpp/flann/flann.cpp

@@ -100,6 +100,7 @@ flann_index_t __flann_build_index(typename Distance::ElementType* dataset, int r
             *speedup = autotuned_index->getSpeedup();
         }
 
+        delete params;
 		return index;
 	}
 	catch (std::runtime_error& e) {
@@ -620,9 +621,7 @@ int __flann_free_index(flann_index_t index_ptr, FLANNParameters* flann_params)
             throw FLANNException("Invalid index");
         }
         Index<Distance>* index = (Index<Distance>*) index_ptr;
-		const IndexParams* index_params = index->getIndexParameters();
         delete index;
-        delete index_params;
 
         return 0;
 	}

test/flann_simple_test.cpp

@@ -309,7 +309,7 @@ TEST_F(Flann_SIFT100K_Test, KMeansTreeTest)
 
 TEST_F(Flann_SIFT100K_Test, AutotunedTest)
 {
-    flann::log_verbosity(LOG_INFO);
+    flann::log_verbosity(FLANN_LOG_INFO);
 
 	Index<L2<float> > index(data, flann::AutotunedIndexParams(0.8,0.01,0,0.1)); // 80% precision
 	start_timer("Building autotuned index...");