/external/opencv3/modules/flann/include/opencv2/flann/ |
H A D | all_indices.h | 52 static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) argument 59 nnIndex = new LinearIndex<Distance>(dataset, params, distance); 62 nnIndex = new KDTreeSingleIndex<Distance>(dataset, params, distance); 65 nnIndex = new KDTreeIndex<Distance>(dataset, params, distance); 68 nnIndex = new KMeansIndex<Distance>(dataset, params, distance); 71 nnIndex = new CompositeIndex<Distance>(dataset, params, distance); 74 nnIndex = new AutotunedIndex<Distance>(dataset, params, distance); 77 nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); 80 nnIndex = new LshIndex<Distance>(dataset, params, distance); 93 static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, cons argument 122 create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) argument 146 create_index_by_type(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) argument [all...] |
H A D | ground_truth.h | 42 void find_nearest(const Matrix<typename Distance::ElementType>& dataset, typename Distance::ElementType* query, int* matches, int nn, argument 51 dists[0] = distance(dataset[0], query, dataset.cols); 55 for (size_t i=1; i<dataset.rows; ++i) { 56 DistanceType tmp = distance(dataset[i], query, dataset.cols); 83 void compute_ground_truth(const Matrix<typename Distance::ElementType>& dataset, const Matrix<typename Distance::ElementType>& testset, Matrix<int>& matches, argument 87 find_nearest<Distance>(dataset, testset[i], matches[i], (int)matches.cols, skip, d);
|
H A D | hdf5.h | 76 void save_to_file(const cvflann::Matrix<T>& dataset, const String& filename, const String& name) argument 93 hsize_t dimsf[2]; // dataset dimensions 94 dimsf[0] = dataset.rows; 95 dimsf[1] = dataset.cols; 114 CHECK_ERROR(dataset_id,"Error creating or opening dataset in file."); 116 status = H5Dwrite(dataset_id, get_hdf5_type<T>(), memspace_id, space_id, H5P_DEFAULT, dataset.data ); 117 CHECK_ERROR(status, "Error writing to dataset"); 128 void load_from_file(cvflann::Matrix<T>& dataset, const String& filename, const String& name) argument 140 CHECK_ERROR(dataset_id,"Error opening dataset in file."); 147 dataset 169 load_from_file(cvflann::Matrix<T>& dataset, const String& filename, const String& name) argument [all...] |
H A D | flann_base.hpp | 73 NNIndex<Distance>* load_saved_index(const Matrix<typename Distance::ElementType>& dataset, const cv::String& filename, Distance distance) argument 85 if ((size_t(header.rows) != dataset.rows)||(size_t(header.cols) != dataset.cols)) { 86 throw FLANNException("The index saved belongs to a different dataset"); 91 NNIndex<Distance>* nnIndex = create_index_by_type<Distance>(dataset, params, distance);
|
H A D | lsh_table.h | 193 * @param dataset the values to store 195 void add(Matrix<ElementType> dataset) argument 198 buckets_space_.rehash((buckets_space_.size() + dataset.rows) * 1.2); 201 for (unsigned int i = 0; i < dataset.rows; ++i) add(i, dataset[i]);
|
H A D | hierarchical_clustering_index.h | 103 * vecs = the dataset of points 104 * indices = indices in the dataset 127 DistanceType sq = distance(dataset[centers[index]], dataset[centers[j]], dataset.cols); 145 * vecs = the dataset of points 146 * indices = indices in the dataset 164 DistanceType dist = distance(dataset[centers[0]],dataset[dsindices[j]],dataset 789 const Matrix<ElementType> dataset; member in class:cvflann::HierarchicalClusteringIndex [all...] |
H A D | kmeans_index.h | 102 * vecs = the dataset of points 103 * indices = indices in the dataset 144 * vecs = the dataset of points 145 * indices = indices in the dataset 195 * vecs = the dataset of points 196 * indices = indices in the dataset 281 , dataset(_dataset) 301 DistanceType sq_dist = distance(dataset[indices[i]], dcenters[0], veclen); 304 DistanceType new_sq_dist = distance(dataset[indices[i]], dcenters[j], veclen); 326 const Matrix<ElementType>& dataset; member in class:cvflann::KMeansIndex::KMeansDistanceComputer [all...] |
/external/opencv3/modules/flann/include/opencv2/ |
H A D | flann.hpp | 114 /** @brief Constructs a nearest neighbor search index for a given dataset. 182 (randomized kd-trees, hierarchical kmeans, linear) and parameters for the dataset provided. : 251 GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance) argument 253 CV_Assert(dataset.type() == CvType<ElementType>::type()); 254 CV_Assert(dataset.isContinuous()); 255 ::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols); 405 Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params) argument 409 CV_Assert(dataset [all...] |
/external/robolectric/v3/runtime/ |
H A D | android-all-5.0.0_r2-robolectric-1.jar | META-INF/ META-INF/MANIFEST.MF com/ com/google/ com/google/android/ com/google/android/collect/ ... |
H A D | android-all-5.1.1_r9-robolectric-1.jar | META-INF/ META-INF/MANIFEST.MF com/ com/google/ com/google/android/ com/google/android/collect/ ... |