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Split cvWriteRawData_Base64 into three functions

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The three new functions:

```cpp
void cvStartWriteRawData_Base64(::CvFileStorage * fs, const char* name,
int len, const char* dt);
void cvWriteRawData_Base64(::CvFileStorage *
fs, const void* _data, int len);
void
cvEndWriteRawData_Base64(::CvFileStorage * fs);
```

Test is also updated. (And it's remarkable that there is a bug in
`cvWriteReadData`.)
This commit is contained in:
MYLS
2016-06-24 22:27:42 +08:00
parent 29921d055d
commit 7c92ee2e6e
3 changed files with 252 additions and 153 deletions
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245
modules/core/test/test_io.cpp
View File

@@ -583,132 +583,133 @@ TEST(Core_InputOutput, filestorage_yml_compatibility)
//EXPECT_ANY_THROW();
}
class CV_Base64IOTest : public cvtest::BaseTest
{
private:
std::string file_name;
public:
CV_Base64IOTest(std::string const & file_name)
: file_name(file_name) {}
~CV_Base64IOTest() {}
protected:
void run(int)
{
try
{
struct data_t
{
uchar u1, u2;
int i1, i2, i3;
double d1, d2;
int i4;
};
std::vector<data_t> rawdata;
cv::Mat _em_out, _em_in;
cv::Mat _2d_out, _2d_in;
cv::Mat _nd_out, _nd_in;
{ /* init */
/* normal mat */
_2d_out = cv::Mat(100, 100, CV_8UC3, cvScalar(1U, 2U, 127U));
for (int i = 0; i < _2d_out.rows; ++i)
for (int j = 0; j < _2d_out.cols; ++j)
_2d_out.at<cv::Vec3b>(i, j)[1] = i % 256;
/* 4d mat */
const int Size[] = {4, 4, 4, 4};
cv::Mat _4d(4, Size, CV_64FC4, cvScalar(0.888, 0.111, 0.666, 0.444));
const cv::Range ranges[] = {
cv::Range(0, 2),
cv::Range(0, 2),
cv::Range(1, 2),
cv::Range(0, 2) };
_nd_out = _4d(ranges);
/* raw data */
for (int i = 0; i < 1000; i++)
rawdata.push_back(data_t{1, 2, 1, 2, 3, 0.1, 0.2, i});
}
{ /* write */
cv::FileStorage fs(file_name, cv::FileStorage::WRITE);
CvMat holder = _2d_out;
cv::cvWriteMat_Base64(*fs, "normal_2d_mat", &holder);
CvMatND holder_nd = _nd_out;
cv::cvWriteMatND_Base64(*fs, "normal_nd_mat", &holder_nd);
holder = _em_out;
cv::cvWriteMat_Base64(*fs, "empty_2d_mat", &holder);
cv::cvStartWriteRawData_Base64(*fs, "rawdata", rawdata.size(), "2u3i2di");
for (int i = 0; i < 10; i++)
cv::cvWriteRawData_Base64(*fs, rawdata.data() + i * 100, 100);
cv::cvEndWriteRawData_Base64(*fs);
fs.release();
}
{ /* read */
cv::FileStorage fs(file_name, cv::FileStorage::READ);
/* mat */
fs["empty_2d_mat"] >> _em_in;
fs["normal_2d_mat"] >> _2d_in;
fs["normal_nd_mat"] >> _nd_in;
/* raw data */
std::vector<data_t>(1000).swap(rawdata);
cvReadRawData(*fs, fs["rawdata"].node, rawdata.data(), "2u3i2di");
fs.release();
}
for (int i = 0; i < 1000; i++) {
// TODO: Solve this bug
//EXPECT_EQ(rawdata[i].u1, 1);
//EXPECT_EQ(rawdata[i].u2, 2);
//EXPECT_EQ(rawdata[i].i1, 1);
//EXPECT_EQ(rawdata[i].i2, 2);
//EXPECT_EQ(rawdata[i].i3, 3);
//EXPECT_EQ(rawdata[i].d1, 0.1);
//EXPECT_EQ(rawdata[i].d2, 0.2);
//EXPECT_EQ(rawdata[i].i4, i);
}
EXPECT_EQ(_em_in.rows , _em_out.rows);
EXPECT_EQ(_em_in.cols , _em_out.cols);
EXPECT_EQ(_em_in.dims , _em_out.dims);
EXPECT_EQ(_em_in.depth(), _em_out.depth());
EXPECT_TRUE(_em_in.empty());
EXPECT_EQ(_2d_in.rows , _2d_in.rows);
EXPECT_EQ(_2d_in.cols , _2d_in.cols);
EXPECT_EQ(_2d_in.dims , _2d_in.dims);
EXPECT_EQ(_2d_in.depth(), _2d_in.depth());
for(int i = 0; i < _2d_in.rows; ++i)
for (int j = 0; j < _2d_in.cols; ++j)
EXPECT_EQ(_2d_in.at<cv::Vec3b>(i, j), _2d_out.at<cv::Vec3b>(i, j));
EXPECT_EQ(_nd_in.rows , _nd_in.rows);
EXPECT_EQ(_nd_in.cols , _nd_in.cols);
EXPECT_EQ(_nd_in.dims , _nd_in.dims);
EXPECT_EQ(_nd_in.depth(), _nd_in.depth());
EXPECT_EQ(cv::countNonZero(cv::mean(_nd_in != _nd_out)), 0);
}
catch(...)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
}
}
};
TEST(Core_InputOutput, filestorage_yml_base64)
{
cv::Mat _em_out, _em_in;
cv::Mat _2d_out, _2d_in;
cv::Mat _nd_out, _nd_in;
{ /* init */
/* normal mat */
_2d_out = cv::Mat(100, 100, CV_8UC3, cvScalar(1U, 2U, 127U));
for (int i = 0; i < _2d_out.rows; ++i)
for (int j = 0; j < _2d_out.cols; ++j)
_2d_out.at<cv::Vec3b>(i, j)[1] = i % 256;
/* 4d mat */
const int Size[] = {4, 4, 4, 4};
cv::Mat _4d(4, Size, CV_64FC4, cvScalar(0.888, 0.111, 0.666, 0.444));
const cv::Range ranges[] = {
cv::Range(0, 2),
cv::Range(0, 2),
cv::Range(1, 2),
cv::Range(0, 2) };
_nd_out = _4d(ranges);
}
{ /* write */
cv::FileStorage fs("test.yml", cv::FileStorage::WRITE);
CvMat holder = _2d_out;
cv::cvWriteMat_Base64(*fs, "normal_2d_mat", &holder);
CvMatND holder_nd = _nd_out;
cv::cvWriteMatND_Base64(*fs, "normal_nd_mat", &holder_nd);
holder = _em_out;
cv::cvWriteMat_Base64(*fs, "empty_2d_mat", &holder);
fs.release();
}
{ /* read */
cv::FileStorage fs("test.yml", cv::FileStorage::READ);
fs["empty_2d_mat"] >> _em_in;
fs["normal_2d_mat"] >> _2d_in;
fs["normal_nd_mat"] >> _nd_in;
fs.release();
}
EXPECT_EQ(_em_in.rows , _em_out.rows);
EXPECT_EQ(_em_in.cols , _em_out.cols);
EXPECT_EQ(_em_in.dims , _em_out.dims);
EXPECT_EQ(_em_in.depth(), _em_out.depth());
EXPECT_TRUE(_em_in.empty());
EXPECT_EQ(_2d_in.rows , _2d_in.rows);
EXPECT_EQ(_2d_in.cols , _2d_in.cols);
EXPECT_EQ(_2d_in.dims , _2d_in.dims);
EXPECT_EQ(_2d_in.depth(), _2d_in.depth());
for(int i = 0; i < _2d_in.rows; ++i)
for (int j = 0; j < _2d_in.cols; ++j)
EXPECT_EQ(_2d_in.at<cv::Vec3b>(i, j), _2d_out.at<cv::Vec3b>(i, j));
EXPECT_EQ(_nd_in.rows , _nd_in.rows);
EXPECT_EQ(_nd_in.cols , _nd_in.cols);
EXPECT_EQ(_nd_in.dims , _nd_in.dims);
EXPECT_EQ(_nd_in.depth(), _nd_in.depth());
EXPECT_EQ(cv::countNonZero(cv::mean(_nd_in != _nd_out)), 0);
CV_Base64IOTest test("base64_test.yml"); test.safe_run();
}
TEST(Core_InputOutput, filestorage_xml_base64)
{
cv::Mat _em_out, _em_in;
cv::Mat _2d_out, _2d_in;
cv::Mat _nd_out, _nd_in;
{ /* init */
/* normal mat */
_2d_out = cv::Mat(100, 100, CV_8UC3, cvScalar(1U, 2U, 127U));
for (int i = 0; i < _2d_out.rows; ++i)
for (int j = 0; j < _2d_out.cols; ++j)
_2d_out.at<cv::Vec3b>(i, j)[1] = i % 256;
/* 4d mat */
const int Size[] = {4, 4, 4, 4};
cv::Mat _4d(4, Size, CV_64FC4, cvScalar(0.888, 0.111, 0.666, 0.444));
const cv::Range ranges[] = {
cv::Range(0, 2),
cv::Range(0, 2),
cv::Range(1, 2),
cv::Range(0, 2) };
_nd_out = _4d(ranges);
}
{ /* write */
cv::FileStorage fs("test.xml", cv::FileStorage::WRITE);
CvMat holder = _2d_out;
cv::cvWriteMat_Base64(*fs, "normal_2d_mat", &holder);
CvMatND holder_nd = _nd_out;
cv::cvWriteMatND_Base64(*fs, "normal_nd_mat", &holder_nd);
holder = _em_out;
cv::cvWriteMat_Base64(*fs, "empty_2d_mat", &holder);
fs.release();
}
{ /* read */
cv::FileStorage fs("test.xml", cv::FileStorage::READ);
fs["empty_2d_mat"] >> _em_in;
fs["normal_2d_mat"] >> _2d_in;
fs["normal_nd_mat"] >> _nd_in;
fs.release();
}
EXPECT_EQ(_em_in.rows , _em_out.rows);
EXPECT_EQ(_em_in.cols , _em_out.cols);
EXPECT_EQ(_em_in.dims , _em_out.dims);
EXPECT_EQ(_em_in.depth(), _em_out.depth());
EXPECT_TRUE(_em_in.empty());
EXPECT_EQ(_2d_in.rows , _2d_in.rows);
EXPECT_EQ(_2d_in.cols , _2d_in.cols);
EXPECT_EQ(_2d_in.dims , _2d_in.dims);
EXPECT_EQ(_2d_in.depth(), _2d_in.depth());
for(int i = 0; i < _2d_in.rows; ++i)
for (int j = 0; j < _2d_in.cols; ++j)
EXPECT_EQ(_2d_in.at<cv::Vec3b>(i, j), _2d_out.at<cv::Vec3b>(i, j));
EXPECT_EQ(_nd_in.rows , _nd_in.rows);
EXPECT_EQ(_nd_in.cols , _nd_in.cols);
EXPECT_EQ(_nd_in.dims , _nd_in.dims);
EXPECT_EQ(_nd_in.depth(), _nd_in.depth());
EXPECT_EQ(cv::countNonZero(cv::sum(_nd_in != _nd_out)), 0);
CV_Base64IOTest test("base64_test.xml"); test.safe_run();
}