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#include <gtest/gtest.h>
#include <time.h>
#include <flann/flann.h>
#include <flann/io/hdf5.h>
#include "flann_tests.h"
using namespace flann;
class HierarchicalIndex_Brief100K : public FLANNTestFixture
{
protected:
typedef flann::Hamming<unsigned char> Distance;
typedef Distance::ElementType ElementType;
typedef Distance::ResultType DistanceType;
flann::Matrix<unsigned char> data;
flann::Matrix<unsigned char> query;
flann::Matrix<size_t> gt_indices;
flann::Matrix<DistanceType> dists;
flann::Matrix<DistanceType> gt_dists;
flann::Matrix<size_t> indices;
unsigned int k_nn_;
void SetUp()
{
k_nn_ = 3;
printf("Reading test data...");
fflush(stdout);
flann::load_from_file(data, "brief100K.h5", "dataset");
flann::load_from_file(query, "brief100K.h5", "query");
printf("done\n");
flann::Index<Distance> index(data, flann::LinearIndexParams());
index.buildIndex();
start_timer("Searching KNN for ground truth...");
gt_indices = flann::Matrix<size_t>(new size_t[query.rows * k_nn_], query.rows, k_nn_);
gt_dists = flann::Matrix<DistanceType>(new DistanceType[query.rows * k_nn_], query.rows, k_nn_);
index.knnSearch(query, gt_indices, gt_dists, k_nn_, flann::SearchParams(-1));
printf("done (%g seconds)\n", stop_timer());
dists = flann::Matrix<DistanceType>(new DistanceType[query.rows * k_nn_], query.rows, k_nn_);
indices = flann::Matrix<size_t>(new size_t[query.rows * k_nn_], query.rows, k_nn_);
}
void TearDown()
{
delete[] data.ptr();
delete[] query.ptr();
delete[] dists.ptr();
delete[] indices.ptr();
delete[] gt_indices.ptr();
delete[] gt_dists.ptr();
}
};
TEST_F(HierarchicalIndex_Brief100K, TestSearch)
{
TestSearch<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.9, gt_indices, gt_dists);
}
TEST_F(HierarchicalIndex_Brief100K, TestSearch2)
{
TestSearch2<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.9, gt_indices, gt_dists);
}
TEST_F(HierarchicalIndex_Brief100K, TestAddIncremental)
{
TestAddIncremental<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.87, gt_indices, gt_dists);
}
TEST_F(HierarchicalIndex_Brief100K, TestAddIncremental2)
{
TestAddIncremental2<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.87, gt_indices, gt_dists);
}
TEST_F(HierarchicalIndex_Brief100K, TestRemove)
{
TestRemove<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000));
}
TEST_F(HierarchicalIndex_Brief100K, TestSave)
{
TestSave<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.87, gt_indices, gt_dists);
}
TEST_F(HierarchicalIndex_Brief100K, TestCopy)
{
TestCopy<Distance>(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.87, gt_indices, gt_dists);
}
TEST_F(HierarchicalIndex_Brief100K, TestCopy2)
{
TestCopy2<flann::HierarchicalClusteringIndex<Distance> >(data, flann::HierarchicalClusteringIndexParams(),
query, indices, dists, k_nn_, flann::SearchParams(2000), 0.87, gt_indices, gt_dists);
}
int main(int argc, char** argv)
{
testing::InitGoogleTest(&argc, argv);
return RUN_ALL_TESTS();
}
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