test_hdf5.cpp 9.94 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11
// 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 "test_precomp.hpp"

12
namespace opencv_test { namespace {
13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59

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);

60 61 62
    // It should fail since it creates a group with an existing name
    EXPECT_ANY_THROW(m_hdf_io->grcreate(group_name));

63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148
    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());
149
    EXPECT_LE(cvtest::norm(single, m_single_channel, NORM_L2), 1e-10);
150 151 152 153 154 155

    // 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());
156
    EXPECT_LE(cvtest::norm(dual, m_two_channels, NORM_L2), 1e-10);
157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200

    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());
201
    EXPECT_LE(cvtest::norm(single, m_single_channel, NORM_L2), 1e-10);
202 203 204 205 206 207

    // 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());
208
    EXPECT_LE(cvtest::norm(dual, m_two_channels, NORM_L2), 1e-10);
209 210 211

    m_hdf_io->close();
}
212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345

TEST_F(HDF5_Test, test_attribute)
{
    reset();

    String attr_name = "test attribute name";
    int attr_value = 0x12345678;

    m_hdf_io = hdf::open(m_filename);
    EXPECT_EQ(m_hdf_io->atexists(attr_name), false);

    m_hdf_io->atwrite(attr_value, attr_name);
    EXPECT_ANY_THROW(m_hdf_io->atwrite(attr_value, attr_name)); // error! it already exists

    EXPECT_EQ(m_hdf_io->atexists(attr_name), true);

    int expected_attr_value;
    m_hdf_io->atread(&expected_attr_value, attr_name);
    EXPECT_EQ(attr_value, expected_attr_value);

    m_hdf_io->atdelete(attr_name);
    EXPECT_ANY_THROW(m_hdf_io->atdelete(attr_name)); // error! Delete non-existed attribute

    EXPECT_EQ(m_hdf_io->atexists(attr_name), false);

    m_hdf_io->close();
}

TEST_F(HDF5_Test, test_attribute_int)
{
    reset();

    String attr_name = "test int";
    int attr_value = 0x12345678;

    m_hdf_io = hdf::open(m_filename);

    m_hdf_io->atwrite(attr_value, attr_name);

    int expected_attr_value;
    m_hdf_io->atread(&expected_attr_value, attr_name);
    EXPECT_EQ(attr_value, expected_attr_value);

    m_hdf_io->close();
}

TEST_F(HDF5_Test, test_attribute_double)
{
    reset();

    String attr_name = "test double";
    double attr_value = 123.456789;

    m_hdf_io = hdf::open(m_filename);

    m_hdf_io->atwrite(attr_value, attr_name);

    double expected_attr_value;
    m_hdf_io->atread(&expected_attr_value, attr_name);
    EXPECT_NEAR(attr_value, expected_attr_value, 1e-9);

    m_hdf_io->close();
}

TEST_F(HDF5_Test, test_attribute_String)
{
    reset();

    String attr_name = "test-String";
    String attr_value = "----_______----Hello HDF5----_______----\n";

    m_hdf_io = hdf::open(m_filename);

    m_hdf_io->atwrite(attr_value, attr_name);

    String expected_attr_value;
    m_hdf_io->atread(&expected_attr_value, attr_name);
    EXPECT_EQ(attr_value.compare(expected_attr_value), 0);

    m_hdf_io->close();
}

TEST_F(HDF5_Test, test_attribute_InutArray_OutputArray_2d)
{
    reset();

    String attr_name = "test-InputArray-OutputArray-2d";
    cv::Mat attr_value;

    std::vector<int> depth_vec;
    depth_vec.push_back(CV_8U); depth_vec.push_back(CV_8S);
    depth_vec.push_back(CV_16U); depth_vec.push_back(CV_16S);
    depth_vec.push_back(CV_32S); depth_vec.push_back(CV_32F);
    depth_vec.push_back(CV_64F);

    std::vector<int> channel_vec;
    channel_vec.push_back(1); channel_vec.push_back(2);
    channel_vec.push_back(3); channel_vec.push_back(4);
    channel_vec.push_back(5); channel_vec.push_back(6);
    channel_vec.push_back(7); channel_vec.push_back(8);
    channel_vec.push_back(9); channel_vec.push_back(10);

    std::vector<std::vector<int> > dim_vec;
    std::vector<int> dim_2d;
    dim_2d.push_back(2); dim_2d.push_back(3);
    dim_vec.push_back(dim_2d);

    std::vector<int> dim_3d;
    dim_3d.push_back(2);
    dim_3d.push_back(3);
    dim_3d.push_back(4);
    dim_vec.push_back(dim_3d);

    std::vector<int> dim_4d;
    dim_4d.push_back(2); dim_4d.push_back(3);
    dim_4d.push_back(4); dim_4d.push_back(5);
    dim_vec.push_back(dim_4d);

    Mat expected_attr_value;

    m_hdf_io = hdf::open(m_filename);
    for (size_t i = 0; i < depth_vec.size(); i++)
    for (size_t j = 0; j < channel_vec.size(); j++)
    for (size_t k = 0; k < dim_vec.size(); k++)
    {
        if (m_hdf_io->atexists(attr_name))
            m_hdf_io->atdelete(attr_name);

        attr_value.create(dim_vec[k], CV_MAKETYPE(depth_vec[i], channel_vec[j]));
        randu(attr_value, 0, 255);

        m_hdf_io->atwrite(attr_value, attr_name);
        m_hdf_io->atread(expected_attr_value, attr_name);

346 347
        double diff = cvtest::norm(attr_value, expected_attr_value, NORM_L2);
        EXPECT_LE(diff, 1e-6);
348

349
        EXPECT_EQ(attr_value.size, expected_attr_value.size);
350 351 352 353 354
        EXPECT_EQ(attr_value.type(), expected_attr_value.type());
    }

    m_hdf_io->close();
}
355 356

}} // namespace