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#include <gtest/gtest.h>
#include <time.h>
#include <flann/flann.h>
#include <flann/io/hdf5.h>
#include <flann/nn/ground_truth.h>
using namespace flann;
template<typename T>
float compute_precision(const flann::Matrix<T>& match, const flann::Matrix<T>& indices)
{
int count = 0;
assert(match.rows == indices.rows);
size_t nn = std::min(match.cols, indices.cols);
for (size_t i=0; i<match.rows; ++i) {
for (size_t j=0;j<nn;++j) {
for (size_t k=0;k<nn;++k) {
if (match[i][j]==indices[i][k]) {
count ++;
}
}
}
}
return float(count)/(nn*match.rows);
}
class FLANNTestFixture : public ::testing::Test {
protected:
timespec ts_;
void start_timer(const std::string& message = "")
{
if (!message.empty()) {
printf("%s", message.c_str());
fflush(stdout);
}
clock_gettime(CLOCK_REALTIME, &ts_);
}
double stop_timer()
{
timespec ts2;
clock_gettime(CLOCK_REALTIME, &ts2);
return double((ts2.tv_sec-ts_.tv_sec)+(ts2.tv_nsec-ts_.tv_nsec)/1e9);
}
};
/* Test Fixture which loads the cloud.h5 cloud as data and query matrix */
class FlannTest : public FLANNTestFixture {
protected:
flann::Matrix<float> data_;
flann::Matrix<float> query_;
flann::Matrix<size_t> match_;
flann::Matrix<float> dists_;
flann::Matrix<size_t> indices_;
int knn_;
void SetUp()
{
knn_ = 5;
printf("Reading test data...");
fflush(stdout);
flann::load_from_file(data_, "cloud.h5","dataset");
flann::load_from_file(query_,"cloud.h5","query");
flann::load_from_file(match_,"cloud.h5","match");
dists_ = flann::Matrix<float>(new float[query_.rows*knn_], query_.rows, knn_);
indices_ = flann::Matrix<size_t>(new size_t[query_.rows*knn_], query_.rows, knn_);
printf("done\n");
}
void TearDown()
{
delete[] data_.ptr();
delete[] query_.ptr();
delete[] match_.ptr();
delete[] dists_.ptr();
delete[] indices_.ptr();
}
};
TEST_F(FlannTest, HandlesSingleCoreSearch)
{
flann::Index<L2_Simple<float> > index(data_, flann::KDTreeSingleIndexParams(50, false));
start_timer("Building kd-tree index...");
index.buildIndex();
printf("done (%g seconds)\n", stop_timer());
int checks = -1;
float eps = 0.0f;
bool sorted = true;
int cores = 1;
start_timer("Searching KNN...");
SearchParams params(checks,eps,sorted);
params.cores = cores;
index.knnSearch(query_, indices_, dists_, knn_, params);
printf("done (%g seconds)\n", stop_timer());
float precision = compute_precision(match_, indices_);
EXPECT_GE(precision, 0.99);
printf("Precision: %g\n", precision);
}
TEST_F(FlannTest, HandlesMultiCoreSearch)
{
flann::Index<L2_Simple<float> > index(data_, flann::KDTreeSingleIndexParams(50, false));
start_timer("Building kd-tree index...");
index.buildIndex();
printf("done (%g seconds)\n", stop_timer());
int checks = -1;
float eps = 0.0f;
bool sorted = true;
int cores = 2;
start_timer("Searching KNN...");
SearchParams params(checks,eps,sorted);
params.cores = cores;
index.knnSearch(query_, indices_, dists_, knn_, params);
printf("done (%g seconds)\n", stop_timer());
float precision = compute_precision(match_, indices_);
EXPECT_GE(precision, 0.99);
printf("Precision: %g\n", precision);
}
/* Test Fixture which loads the cloud.h5 cloud as data and query matrix and holds two dists
and indices matrices for comparing single and multi core KNN search */
class FlannCompareKnnTest : public FLANNTestFixture {
protected:
flann::Matrix<float> data_;
flann::Matrix<float> query_;
flann::Matrix<float> dists_single_;
flann::Matrix<size_t> indices_single_;
flann::Matrix<float> dists_multi_;
flann::Matrix<size_t> indices_multi_;
int knn_;
void SetUp()
{
knn_ = 5;
printf("Reading test data...");
fflush(stdout);
flann::load_from_file(data_, "cloud.h5","dataset");
flann::load_from_file(query_,"cloud.h5","query");
dists_single_ = flann::Matrix<float>(new float[query_.rows*knn_], query_.rows, knn_);
indices_single_ = flann::Matrix<size_t>(new size_t[query_.rows*knn_], query_.rows, knn_);
dists_multi_ = flann::Matrix<float>(new float[query_.rows*knn_], query_.rows, knn_);
indices_multi_ = flann::Matrix<size_t>(new size_t[query_.rows*knn_], query_.rows, knn_);
printf("done\n");
}
void TearDown()
{
delete[] data_.ptr();
delete[] query_.ptr();
delete[] dists_single_.ptr();
delete[] indices_single_.ptr();
delete[] dists_multi_.ptr();
delete[] indices_multi_.ptr();
}
};
TEST_F(FlannCompareKnnTest, CompareMultiSingleCoreKnnSearch)
{
flann::Index<L2_Simple<float> > index(data_, flann::KDTreeSingleIndexParams(50, false));
start_timer("Building kd-tree index...");
index.buildIndex();
printf("done (%g seconds)\n", stop_timer());
SearchParams params;
params.checks = -1;
params.eps = 0.0f;
params.sorted = true;
start_timer("Searching KNN (single core)...");
params.cores = 1;
int single_neighbor_count = index.knnSearch(query_, indices_single_, dists_single_, knn_, params);
printf("done (%g seconds)\n", stop_timer());
start_timer("Searching KNN (multi core)...");
params.cores = 0;
int multi_neighbor_count = index.knnSearch(query_, indices_multi_, dists_multi_, knn_, params);
printf("done (%g seconds)\n", stop_timer());
EXPECT_EQ(single_neighbor_count, multi_neighbor_count);
printf("Checking results...\n");
float precision = compute_precision(indices_single_, indices_multi_);
EXPECT_GE(precision, 0.99);
printf("Precision: %g\n", precision);
}
/* Test Fixture which loads the cloud.h5 cloud as data and query matrix and holds two dists
and indices matrices for comparing single and multi core radius search */
class FlannCompareRadiusTest : public FLANNTestFixture {
protected:
flann::Matrix<float> data_;
flann::Matrix<float> query_;
flann::Matrix<float> dists_single_;
flann::Matrix<int> indices_single_;
flann::Matrix<float> dists_multi_;
flann::Matrix<int> indices_multi_;
float radius_;
void SetUp()
{
radius_ = 0.1f;
printf("Reading test data...");
fflush(stdout);
flann::load_from_file(data_, "cloud.h5","dataset");
flann::load_from_file(query_,"cloud.h5","query");
int reserve_size = data_.rows / 1000;
dists_single_ = flann::Matrix<float>(new float[query_.rows*reserve_size], query_.rows, reserve_size);
indices_single_ = flann::Matrix<int>(new int[query_.rows*reserve_size], query_.rows, reserve_size);
dists_multi_ = flann::Matrix<float>(new float[query_.rows*reserve_size], query_.rows, reserve_size);
indices_multi_ = flann::Matrix<int>(new int[query_.rows*reserve_size], query_.rows, reserve_size);
printf("done\n");
}
void TearDown()
{
delete[] data_.ptr();
delete[] query_.ptr();
delete[] dists_single_.ptr();
delete[] indices_single_.ptr();
delete[] dists_multi_.ptr();
delete[] indices_multi_.ptr();
}
void runTest(const flann::Index<L2_Simple<float> >& index, SearchParams params)
{
start_timer("Searching Radius (single core)...");
params.cores = 1;
int single_neighbor_count = index.radiusSearch(query_, indices_single_, dists_single_, radius_, params);
printf("done (%g seconds)\n", stop_timer());
start_timer("Searching Radius (multi core)...");
params.cores = 0;
int multi_neighbor_count = index.radiusSearch(query_, indices_multi_, dists_multi_, radius_, params);
printf("done (%g seconds)\n", stop_timer());
EXPECT_EQ(single_neighbor_count, multi_neighbor_count);
printf("Checking results...\n");
float precision = compute_precision(indices_single_, indices_multi_);
EXPECT_GE(precision, 0.99);
printf("Precision: %g\n", precision);
}
};
TEST_F(FlannCompareRadiusTest, CompareMultiSingleCoreRadiusSearchSorted)
{
flann::Index<L2_Simple<float> > index(data_, flann::KDTreeSingleIndexParams(50, false));
start_timer("Building kd-tree index...");
index.buildIndex();
printf("done (%g seconds)\n", stop_timer());
SearchParams params;
params.checks = -1;
params.eps = 0.0f;
params.sorted = true;
runTest(index, params);
}
TEST_F(FlannCompareRadiusTest, CompareMultiSingleCoreRadiusSearchUnsorted)
{
flann::Index<L2_Simple<float> > index(data_, flann::KDTreeSingleIndexParams(50, false));
start_timer("Building kd-tree index...");
index.buildIndex();
printf("done (%g seconds)\n", stop_timer());
SearchParams params;
params.checks = -1;
params.eps = 0.0f;
params.sorted = false;
runTest(index, params);
}
int main(int argc, char** argv)
{
testing::InitGoogleTest(&argc, argv);
return RUN_ALL_TESTS();
}
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