Repository for OpenCV's extra modules
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
/**
* @file test_hdf5.cpp
* @author Fangjun Kuang <csukuangfj dot at gmail dot com>
* @date December 2017
*
*/
#include<stdio.h> // for remove()
#include "test_precomp.hpp"
#include <vector>
using namespace cv;
struct HDF5_Test : public testing::Test
{
virtual void SetUp()
{
m_filename = "test.h5";
// 0 1 2
// 3 4 5
m_single_channel.create(2, 3, CV_32F);
for (size_t i = 0; i < m_single_channel.total(); i++)
{
((float*)m_single_channel.data)[i] = i;
}
// 0 1 2 3 4 5
// 6 7 8 9 10 11
m_two_channels.create(2, 3, CV_32SC2);
for (size_t i = 0; i < m_two_channels.total()*m_two_channels.channels(); i++)
{
((int*)m_two_channels.data)[i] = (int)i;
}
}
//! Remove the hdf5 file
void reset()
{
remove(m_filename.c_str());
}
String m_filename; //!< filename for testing
Ptr<hdf::HDF5> m_hdf_io; //!< HDF5 file pointer
Mat m_single_channel; //!< single channel matrix for test
Mat m_two_channels; //!< two-channel matrix for test
};
TEST_F(HDF5_Test, create_a_single_group)
{
reset();
String group_name = "parent";
m_hdf_io = hdf::open(m_filename);
m_hdf_io->grcreate(group_name);
EXPECT_EQ(m_hdf_io->hlexists(group_name), true);
EXPECT_EQ(m_hdf_io->hlexists("child"), false);
m_hdf_io->close();
}
TEST_F(HDF5_Test, create_a_child_group)
{
reset();
String parent = "parent";
String child = parent + "/child";
m_hdf_io = hdf::open(m_filename);
m_hdf_io->grcreate(parent);
m_hdf_io->grcreate(child);
EXPECT_EQ(m_hdf_io->hlexists(parent), true);
EXPECT_EQ(m_hdf_io->hlexists(child), true);
m_hdf_io->close();
}
TEST_F(HDF5_Test, create_dataset)
{
reset();
String dataset_single_channel = "/single";
String dataset_two_channels = "/dual";
m_hdf_io = hdf::open(m_filename);
m_hdf_io->dscreate(m_single_channel.rows,
m_single_channel.cols,
m_single_channel.type(),
dataset_single_channel);
m_hdf_io->dscreate(m_two_channels.rows,
m_two_channels.cols,
m_two_channels.type(),
dataset_two_channels);
EXPECT_EQ(m_hdf_io->hlexists(dataset_single_channel), true);
EXPECT_EQ(m_hdf_io->hlexists(dataset_two_channels), true);
std::vector<int> dims;
dims = m_hdf_io->dsgetsize(dataset_single_channel, hdf::HDF5::H5_GETDIMS);
EXPECT_EQ(dims.size(), (size_t)2);
EXPECT_EQ(dims[0], m_single_channel.rows);
EXPECT_EQ(dims[1], m_single_channel.cols);
dims = m_hdf_io->dsgetsize(dataset_two_channels, hdf::HDF5::H5_GETDIMS);
EXPECT_EQ(dims.size(), (size_t)2);
EXPECT_EQ(dims[0], m_two_channels.rows);
EXPECT_EQ(dims[1], m_two_channels.cols);
int type;
type = m_hdf_io->dsgettype(dataset_single_channel);
EXPECT_EQ(type, m_single_channel.type());
type = m_hdf_io->dsgettype(dataset_two_channels);
EXPECT_EQ(type, m_two_channels.type());
m_hdf_io->close();
}
TEST_F(HDF5_Test, write_read_dataset_1)
{
reset();
String dataset_single_channel = "/single";
String dataset_two_channels = "/dual";
m_hdf_io = hdf::open(m_filename);
// since the dataset is under the root group, it is created by dswrite() automatically.
m_hdf_io->dswrite(m_single_channel, dataset_single_channel);
m_hdf_io->dswrite(m_two_channels, dataset_two_channels);
EXPECT_EQ(m_hdf_io->hlexists(dataset_single_channel), true);
EXPECT_EQ(m_hdf_io->hlexists(dataset_two_channels), true);
// read single channel matrix
Mat single;
m_hdf_io->dsread(single, dataset_single_channel);
EXPECT_EQ(single.type(), m_single_channel.type());
EXPECT_EQ(single.size(), m_single_channel.size());
EXPECT_NEAR(norm(single-m_single_channel), 0, 1e-10);
// read dual channel matrix
Mat dual;
m_hdf_io->dsread(dual, dataset_two_channels);
EXPECT_EQ(dual.type(), m_two_channels.type());
EXPECT_EQ(dual.size(), m_two_channels.size());
EXPECT_NEAR(norm(dual-m_two_channels), 0, 1e-10);
m_hdf_io->close();
}
TEST_F(HDF5_Test, write_read_dataset_2)
{
reset();
// create the dataset manually if it is not inside
// the root group
String parent = "/parent";
String dataset_single_channel = parent + "/single";
String dataset_two_channels = parent + "/dual";
m_hdf_io = hdf::open(m_filename);
m_hdf_io->grcreate(parent);
EXPECT_EQ(m_hdf_io->hlexists(parent), true);
m_hdf_io->dscreate(m_single_channel.rows,
m_single_channel.cols,
m_single_channel.type(),
dataset_single_channel);
m_hdf_io->dscreate(m_two_channels.rows,
m_two_channels.cols,
m_two_channels.type(),
dataset_two_channels);
EXPECT_EQ(m_hdf_io->hlexists(dataset_single_channel), true);
EXPECT_EQ(m_hdf_io->hlexists(dataset_two_channels), true);
m_hdf_io->dswrite(m_single_channel, dataset_single_channel);
m_hdf_io->dswrite(m_two_channels, dataset_two_channels);
EXPECT_EQ(m_hdf_io->hlexists(dataset_single_channel), true);
EXPECT_EQ(m_hdf_io->hlexists(dataset_two_channels), true);
// read single channel matrix
Mat single;
m_hdf_io->dsread(single, dataset_single_channel);
EXPECT_EQ(single.type(), m_single_channel.type());
EXPECT_EQ(single.size(), m_single_channel.size());
EXPECT_NEAR(norm(single-m_single_channel), 0, 1e-10);
// read dual channel matrix
Mat dual;
m_hdf_io->dsread(dual, dataset_two_channels);
EXPECT_EQ(dual.type(), m_two_channels.type());
EXPECT_EQ(dual.size(), m_two_channels.size());
EXPECT_NEAR(norm(dual-m_two_channels), 0, 1e-10);
m_hdf_io->close();
}