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opencv/modules/core/test/test_io.cpp
Kumataro b14ea19466
Merge pull request #25351 from Kumataro:fix25073_format_g 
core: persistence: output reals as human-friendly expression. #25351

Close #25073
Related https://github.com/opencv/opencv/pull/25087

This patch is need to merge same time with https://github.com/opencv/opencv_contrib/pull/3714

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-10 15:17:15 +03:00

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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.
#include "test_precomp.hpp"
#include <fstream>
namespace opencv_test { namespace {
static SparseMat cvTsGetRandomSparseMat(int dims, const int* sz, int type,
int nzcount, double a, double b, RNG& rng)
{
SparseMat m(dims, sz, type);
int i, j;
CV_Assert(CV_MAT_CN(type) == 1);
for( i = 0; i < nzcount; i++ )
{
int idx[CV_MAX_DIM];
for( j = 0; j < dims; j++ )
idx[j] = cvtest::randInt(rng) % sz[j];
double val = cvtest::randReal(rng)*(b - a) + a;
uchar* ptr = m.ptr(idx, true, 0);
if( type == CV_8U )
*(uchar*)ptr = saturate_cast<uchar>(val);
else if( type == CV_8S )
*(schar*)ptr = saturate_cast<schar>(val);
else if( type == CV_16U )
*(ushort*)ptr = saturate_cast<ushort>(val);
else if( type == CV_16S )
*(short*)ptr = saturate_cast<short>(val);
else if( type == CV_32S )
*(int*)ptr = saturate_cast<int>(val);
else if( type == CV_32F )
*(float*)ptr = saturate_cast<float>(val);
else
*(double*)ptr = saturate_cast<double>(val);
}
return m;
}
static bool cvTsCheckSparse(const cv::SparseMat& m1, const cv::SparseMat& m2, double eps)
{
cv::SparseMatConstIterator it1, it1_end = m1.end();
int depth = m1.depth();
if( m1.nzcount() != m2.nzcount() ||
m1.dims() != m2.dims() || m1.type() != m2.type() )
return false;
for( it1 = m1.begin(); it1 != it1_end; ++it1 )
{
const cv::SparseMat::Node* node1 = it1.node();
const uchar* v2 = m2.find<uchar>(node1->idx, (size_t*)&node1->hashval);
if( !v2 )
return false;
if( depth == CV_8U || depth == CV_8S )
{
if( m1.value<uchar>(node1) != *v2 )
return false;
}
else if( depth == CV_16U || depth == CV_16S )
{
if( m1.value<ushort>(node1) != *(ushort*)v2 )
return false;
}
else if( depth == CV_32S )
{
if( m1.value<int>(node1) != *(int*)v2 )
return false;
}
else if( depth == CV_32F )
{
if( fabs(m1.value<float>(node1) - *(float*)v2) > eps*(fabs(*(float*)v2) + 1) )
return false;
}
else if( fabs(m1.value<double>(node1) - *(double*)v2) > eps*(fabs(*(double*)v2) + 1) )
return false;
}
return true;
}
class Core_IOTest : public cvtest::BaseTest
{
public:
Core_IOTest() { }
protected:
void run(int)
{
double ranges[][2] = {{0, 256}, {-128, 128}, {0, 65536}, {-32768, 32768},
{-1000000, 1000000}, {-10, 10}, {-10, 10}};
RNG& rng = ts->get_rng();
RNG rng0;
int progress = 0;
MemStorage storage(cvCreateMemStorage(0));
const char * suffixs[3] = {".yml", ".xml", ".json" };
test_case_count = 6;
for( int idx = 0; idx < test_case_count; idx++ )
{
ts->update_context( this, idx, false );
progress = update_progress( progress, idx, test_case_count, 0 );
cvClearMemStorage(storage);
bool mem = (idx % test_case_count) >= (test_case_count >> 1);
string filename = tempfile(suffixs[idx % (test_case_count >> 1)]);
FileStorage fs(filename, FileStorage::WRITE + (mem ? FileStorage::MEMORY : 0));
int test_int = (int)cvtest::randInt(rng);
double test_real = (cvtest::randInt(rng)%2?1:-1)*exp(cvtest::randReal(rng)*18-9);
string test_string = "vw wv23424rt\"&amp;&lt;&gt;&amp;&apos;@#$@$%$%&%IJUKYILFD@#$@%$&*&() ";
int depth = cvtest::randInt(rng) % (CV_64F+1);
int cn = cvtest::randInt(rng) % 4 + 1;
Mat test_mat(cvtest::randInt(rng)%30+1, cvtest::randInt(rng)%30+1, CV_MAKETYPE(depth, cn));
rng0.fill(test_mat, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
if( depth >= CV_32F )
{
exp(test_mat, test_mat);
Mat test_mat_scale(test_mat.size(), test_mat.type());
rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1));
cv::multiply(test_mat, test_mat_scale, test_mat);
}
depth = cvtest::randInt(rng) % (CV_64F+1);
cn = cvtest::randInt(rng) % 4 + 1;
int sz[] = {
static_cast<int>(cvtest::randInt(rng)%10+1),
static_cast<int>(cvtest::randInt(rng)%10+1),
static_cast<int>(cvtest::randInt(rng)%10+1),
};
MatND test_mat_nd(3, sz, CV_MAKETYPE(depth, cn));
rng0.fill(test_mat_nd, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
if( depth >= CV_32F )
{
exp(test_mat_nd, test_mat_nd);
MatND test_mat_scale(test_mat_nd.dims, test_mat_nd.size, test_mat_nd.type());
rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1));
cv::multiply(test_mat_nd, test_mat_scale, test_mat_nd);
}
int ssz[] = {
static_cast<int>(cvtest::randInt(rng)%10+1),
static_cast<int>(cvtest::randInt(rng)%10+1),
static_cast<int>(cvtest::randInt(rng)%10+1),
static_cast<int>(cvtest::randInt(rng)%10+1),
};
SparseMat test_sparse_mat = cvTsGetRandomSparseMat(4, ssz, cvtest::randInt(rng)%(CV_64F+1),
cvtest::randInt(rng) % 10000, 0, 100, rng);
fs << "test_int" << test_int << "test_real" << test_real << "test_string" << test_string;
fs << "test_mat" << test_mat;
fs << "test_mat_nd" << test_mat_nd;
fs << "test_sparse_mat" << test_sparse_mat;
fs << "test_list" << "[" << 0.0000000000001 << 2 << CV_PI << -3435345 << "2-502 2-029 3egegeg" <<
"{:" << "month" << 12 << "day" << 31 << "year" << 1969 << "}" << "]";
fs << "test_map" << "{" << "x" << 1 << "y" << 2 << "width" << 100 << "height" << 200 << "lbp" << "[:";
const uchar arr[] = {0, 1, 1, 0, 1, 1, 0, 1};
fs.writeRaw("u", arr, sizeof(arr));
fs << "]" << "}";
fs.writeComment("test comment", false);
string content = fs.releaseAndGetString();
if(!fs.open(mem ? content : filename, FileStorage::READ + (mem ? FileStorage::MEMORY : 0)))
{
ts->printf( cvtest::TS::LOG, "filename %s can not be read\n", !mem ? filename.c_str() : content.c_str());
ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA );
return;
}
int real_int = (int)fs["test_int"];
double real_real = (double)fs["test_real"];
String real_string = (String)fs["test_string"];
if( real_int != test_int ||
fabs(real_real - test_real) > DBL_EPSILON*(fabs(test_real)+1) ||
real_string != test_string )
{
ts->printf( cvtest::TS::LOG, "the read scalars are not correct\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
Mat m;
fs["test_mat"] >> m;
double max_diff = 0;
Mat stub1 = m.reshape(1, 0);
Mat test_stub1 = test_mat.reshape(1, 0);
vector<int> pt;
if( m.empty() || m.rows != test_mat.rows || m.cols != test_mat.cols ||
cvtest::cmpEps( stub1, test_stub1, &max_diff, 0, &pt, true) < 0 )
{
ts->printf( cvtest::TS::LOG, "the read matrix is not correct at (%d, %d)\n",
pt[0], pt[1] );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
m.release();
Mat m_nd;
fs["test_mat_nd"] >> m_nd;
if( m_nd.empty() )
{
ts->printf( cvtest::TS::LOG, "the read nd-matrix is not correct\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
stub1 = m_nd.reshape(1, 0);
test_stub1 = test_mat_nd.reshape(1, 0);
if( stub1.type() != test_stub1.type() ||
stub1.size != test_stub1.size ||
cvtest::cmpEps( stub1, test_stub1, &max_diff, 0, &pt, true) < 0 )
{
ts->printf( cvtest::TS::LOG, "readObj method: the read nd matrix is not correct at (%d,%d)\n",
pt[0], pt[1] );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
m_nd.release();
SparseMat m_s;
fs["test_sparse_mat"] >> m_s;
if( m_s.nzcount() == 0 || !cvTsCheckSparse(m_s, test_sparse_mat, 0))
{
ts->printf( cvtest::TS::LOG, "the read sparse matrix is not correct\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
FileNode tl = fs["test_list"];
if( tl.type() != FileNode::SEQ || tl.size() != 6 ||
fabs((double)tl[0] - 0.0000000000001) >= DBL_EPSILON ||
(int)tl[1] != 2 ||
fabs((double)tl[2] - CV_PI) >= DBL_EPSILON ||
(int)tl[3] != -3435345 ||
(String)tl[4] != "2-502 2-029 3egegeg" ||
tl[5].type() != FileNode::MAP || tl[5].size() != 3 ||
(int)tl[5]["month"] != 12 ||
(int)tl[5]["day"] != 31 ||
(int)tl[5]["year"] != 1969 )
{
ts->printf( cvtest::TS::LOG, "the test list is incorrect\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
FileNode tm = fs["test_map"];
FileNode tm_lbp = tm["lbp"];
int real_x = (int)tm["x"];
int real_y = (int)tm["y"];
int real_width = (int)tm["width"];
int real_height = (int)tm["height"];
int real_lbp_val = 0;
FileNodeIterator it;
it = tm_lbp.begin();
real_lbp_val |= (int)*it << 0;
++it;
real_lbp_val |= (int)*it << 1;
it++;
real_lbp_val |= (int)*it << 2;
it += 1;
real_lbp_val |= (int)*it << 3;
FileNodeIterator it2(it);
it2++;
real_lbp_val |= (int)*it2 << 4;
++it2;
real_lbp_val |= (int)*it2 << 5;
it2 += 1;
real_lbp_val |= (int)*it2 << 6;
it2++;
real_lbp_val |= (int)*it2 << 7;
++it2;
CV_Assert( it2 == tm_lbp.end() );
if( tm.type() != FileNode::MAP || tm.size() != 5 ||
real_x != 1 ||
real_y != 2 ||
real_width != 100 ||
real_height != 200 ||
tm_lbp.type() != FileNode::SEQ ||
tm_lbp.size() != 8 ||
real_lbp_val != 0xb6 )
{
ts->printf( cvtest::TS::LOG, "the test map is incorrect\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
fs.release();
if( !mem )
remove(filename.c_str());
}
}
};
TEST(Core_InputOutput, write_read_consistency) { Core_IOTest test; test.safe_run(); }
struct UserDefinedType
{
int a;
float b;
};
static inline bool operator==(const UserDefinedType &x,
const UserDefinedType &y) {
return (x.a == y.a) && (x.b == y.b);
}
static inline void write(FileStorage &fs,
const String&,
const UserDefinedType &value)
{
fs << "{:" << "a" << value.a << "b" << value.b << "}";
}
static inline void read(const FileNode& node,
UserDefinedType& value,
const UserDefinedType& default_value
= UserDefinedType()) {
if(node.empty())
{
value = default_value;
}
else
{
node["a"] >> value.a;
node["b"] >> value.b;
}
}
class CV_MiscIOTest : public cvtest::BaseTest
{
public:
CV_MiscIOTest() {}
~CV_MiscIOTest() {}
protected:
void run(int)
{
const char * suffix[] = {
".yml",
".xml",
".json"
};
int ncases = (int)(sizeof(suffix)/sizeof(suffix[0]));
for ( int i = 0; i < ncases; i++ )
{
try
{
string fname = cv::tempfile(suffix[i]);
vector<int> mi, mi2, mi3, mi4;
vector<Mat> mv, mv2, mv3, mv4;
vector<UserDefinedType> vudt, vudt2, vudt3, vudt4;
Mat m(10, 9, CV_32F);
Mat empty;
UserDefinedType udt = { 8, 3.3f };
randu(m, 0, 1);
mi3.push_back(5);
mv3.push_back(m);
vudt3.push_back(udt);
Point_<float> p1(1.1f, 2.2f), op1;
Point3i p2(3, 4, 5), op2;
Size s1(6, 7), os1;
Complex<int> c1(9, 10), oc1;
Rect r1(11, 12, 13, 14), or1;
Vec<int, 5> v1(15, 16, 17, 18, 19), ov1;
Scalar sc1(20.0, 21.1, 22.2, 23.3), osc1;
Range g1(7, 8), og1;
FileStorage fs(fname, FileStorage::WRITE);
fs << "mi" << mi;
fs << "mv" << mv;
fs << "mi3" << mi3;
fs << "mv3" << mv3;
fs << "vudt" << vudt;
fs << "vudt3" << vudt3;
fs << "empty" << empty;
fs << "p1" << p1;
fs << "p2" << p2;
fs << "s1" << s1;
fs << "c1" << c1;
fs << "r1" << r1;
fs << "v1" << v1;
fs << "sc1" << sc1;
fs << "g1" << g1;
fs.release();
fs.open(fname, FileStorage::READ);
fs["mi"] >> mi2;
fs["mv"] >> mv2;
fs["mi3"] >> mi4;
fs["mv3"] >> mv4;
fs["vudt"] >> vudt2;
fs["vudt3"] >> vudt4;
fs["empty"] >> empty;
fs["p1"] >> op1;
fs["p2"] >> op2;
fs["s1"] >> os1;
fs["c1"] >> oc1;
fs["r1"] >> or1;
fs["v1"] >> ov1;
fs["sc1"] >> osc1;
fs["g1"] >> og1;
CV_Assert( mi2.empty() );
CV_Assert( mv2.empty() );
CV_Assert( cvtest::norm(Mat(mi3), Mat(mi4), CV_C) == 0 );
CV_Assert( mv4.size() == 1 );
double n = cvtest::norm(mv3[0], mv4[0], CV_C);
CV_Assert( vudt2.empty() );
CV_Assert( vudt3 == vudt4 );
CV_Assert( n == 0 );
CV_Assert( op1 == p1 );
CV_Assert( op2 == p2 );
CV_Assert( os1 == s1 );
CV_Assert( oc1 == c1 );
CV_Assert( or1 == r1 );
CV_Assert( ov1 == v1 );
CV_Assert( osc1 == sc1 );
CV_Assert( og1 == g1 );
fs.release();
remove(fname.c_str());
}
catch(...)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
}
}
}
};
TEST(Core_InputOutput, misc) { CV_MiscIOTest test; test.safe_run(); }
#if 0 // 4+ GB of data, 40+ GB of estimated result size, it is very slow
BIGDATA_TEST(Core_InputOutput, huge)
{
RNG& rng = theRNG();
int N = 1000, M = 1200000;
std::cout << "Allocating..." << std::endl;
Mat mat(M, N, CV_32F);
std::cout << "Initializing..." << std::endl;
rng.fill(mat, RNG::UNIFORM, 0, 1);
std::cout << "Writing..." << std::endl;
{
FileStorage fs(cv::tempfile(".xml"), FileStorage::WRITE);
fs << "mat" << mat;
fs.release();
}
}
#endif
TEST(Core_globbing, accuracy)
{
std::string patternLena = cvtest::TS::ptr()->get_data_path() + "lena*.*";
std::string patternLenaPng = cvtest::TS::ptr()->get_data_path() + "lena.png";
std::vector<String> lenas, pngLenas;
cv::glob(patternLena, lenas, true);
cv::glob(patternLenaPng, pngLenas, true);
ASSERT_GT(lenas.size(), pngLenas.size());
for (size_t i = 0; i < pngLenas.size(); ++i)
{
ASSERT_NE(std::find(lenas.begin(), lenas.end(), pngLenas[i]), lenas.end());
}
}
TEST(Core_InputOutput, FileStorage)
{
std::string file = cv::tempfile(".xml");
cv::FileStorage f(file, cv::FileStorage::WRITE);
char arr[66];
snprintf(arr, sizeof(arr), "snprintf is hell %d", 666);
EXPECT_NO_THROW(f << arr);
remove(file.c_str());
}
TEST(Core_InputOutput, FileStorageKey)
{
cv::FileStorage f("dummy.yml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
EXPECT_NO_THROW(f << "key1" << "value1");
EXPECT_NO_THROW(f << "_key2" << "value2");
EXPECT_NO_THROW(f << "key_3" << "value3");
const std::string expected = "%YAML:1.0\n---\nkey1: value1\n_key2: value2\nkey_3: value3\n";
ASSERT_STREQ(f.releaseAndGetString().c_str(), expected.c_str());
}
TEST(Core_InputOutput, FileStorageSpaces)
{
cv::FileStorage f("dummy.yml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
const int valueCount = 5;
std::string values[5] = { "", " ", " ", " a", " some string" };
for (size_t i = 0; i < valueCount; i++) {
EXPECT_NO_THROW(f << cv::format("key%zu", i) << values[i]);
}
cv::FileStorage f2(f.releaseAndGetString(), cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::string valuesRead[valueCount];
for (size_t i = 0; i < valueCount; i++) {
EXPECT_NO_THROW(f2[cv::format("key%zu", i)] >> valuesRead[i]);
ASSERT_STREQ(values[i].c_str(), valuesRead[i].c_str());
}
std::string fileName = cv::tempfile(".xml");
cv::FileStorage g1(fileName, cv::FileStorage::WRITE);
for (size_t i = 0; i < 2; i++) {
EXPECT_NO_THROW(g1 << cv::format("key%zu", i) << values[i]);
}
g1.release();
cv::FileStorage g2(fileName, cv::FileStorage::APPEND);
for (size_t i = 2; i < valueCount; i++) {
EXPECT_NO_THROW(g2 << cv::format("key%zu", i) << values[i]);
}
g2.release();
cv::FileStorage g3(fileName, cv::FileStorage::READ);
std::string valuesReadAppend[valueCount];
for (size_t i = 0; i < valueCount; i++) {
EXPECT_NO_THROW(g3[cv::format("key%zu", i)] >> valuesReadAppend[i]);
ASSERT_STREQ(values[i].c_str(), valuesReadAppend[i].c_str());
}
g3.release();
EXPECT_EQ(0, remove(fileName.c_str()));
}
struct data_t
{
typedef uchar u;
typedef char b;
typedef ushort w;
typedef short s;
typedef int i;
typedef float f;
typedef double d;
/*0x00*/ u u1 ;u u2 ; i i1 ;
/*0x08*/ i i2 ;i i3 ;
/*0x10*/ d d1 ;
/*0x18*/ d d2 ;
/*0x20*/ i i4 ;i required_alignment_field_for_linux32;
/*
* OpenCV persistence.cpp stuff expects: sizeof(data_t) = alignSize(36, sizeof(largest type = double)) = 40
* Some compilers on some archs returns sizeof(data_t) = 36 due struct packaging UB
*/
static inline const char * signature() {
if (sizeof(data_t) != 40)
{
printf("sizeof(data_t)=%d, u1=%p u2=%p i1=%p i2=%p i3=%p d1=%p d2=%p i4=%p\n", (int)sizeof(data_t),
&(((data_t*)0)->u1),
&(((data_t*)0)->u2),
&(((data_t*)0)->i1),
&(((data_t*)0)->i2),
&(((data_t*)0)->i3),
&(((data_t*)0)->d1),
&(((data_t*)0)->d2),
&(((data_t*)0)->i4)
);
}
CV_Assert(sizeof(data_t) == 40);
CV_Assert((size_t)&(((data_t*)0)->u1) == 0x0);
CV_Assert((size_t)&(((data_t*)0)->u2) == 0x1);
CV_Assert((size_t)&(((data_t*)0)->i1) == 0x4);
CV_Assert((size_t)&(((data_t*)0)->i2) == 0x8);
CV_Assert((size_t)&(((data_t*)0)->i3) == 0xc);
CV_Assert((size_t)&(((data_t*)0)->d1) == 0x10);
CV_Assert((size_t)&(((data_t*)0)->d2) == 0x18);
CV_Assert((size_t)&(((data_t*)0)->i4) == 0x20);
return "2u3i2di";
}
};
static void test_filestorage_basic(int write_flags, const char* suffix_name, bool testReadWrite, bool useMemory = false)
{
const bool generateTestData = false; // enable to regenerate reference in opencv_extra
const ::testing::TestInfo* const test_info = ::testing::UnitTest::GetInstance()->current_test_info();
CV_Assert(test_info);
std::string name = (std::string(test_info->test_case_name()) + "--" + test_info->name() + suffix_name);
std::string name_34 = string(cvtest::TS::ptr()->get_data_path()) + "io/3_4/" + name;
if (!testReadWrite || generateTestData)
name = string(cvtest::TS::ptr()->get_data_path()) + "io/" + name;
else
name = cv::tempfile(name.c_str());
{
const size_t rawdata_N = 40;
std::vector<data_t> rawdata;
cv::Mat _em_out, _em_in;
cv::Mat _2d_out, _2d_in;
cv::Mat _nd_out, _nd_in;
cv::Mat _rd_out(8, 16, CV_64FC1), _rd_in;
{ /* init */
/* a normal mat */
_2d_out = cv::Mat(10, 20, 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 + j) % 256;
/* a 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);
/* a random mat */
cv::randu(_rd_out, cv::Scalar(0.0), cv::Scalar(1.0));
/* raw data */
for (int i = 0; i < (int)rawdata_N; i++) {
data_t tmp;
tmp.u1 = 1;
tmp.u2 = 2;
tmp.i1 = 1;
tmp.i2 = 2;
tmp.i3 = 3;
tmp.d1 = 0.1;
tmp.d2 = 0.2;
tmp.i4 = i;
rawdata.push_back(tmp);
}
}
if (testReadWrite || useMemory || generateTestData)
{
cv::FileStorage fs(name, write_flags + (useMemory ? cv::FileStorage::MEMORY : 0));
fs << "normal_2d_mat" << _2d_out;
fs << "normal_nd_mat" << _nd_out;
fs << "empty_2d_mat" << _em_out;
fs << "random_mat" << _rd_out;
fs << "rawdata" << "[:";
for (int i = 0; i < (int)rawdata_N/10; i++)
fs.writeRaw(data_t::signature(), (const uchar*)&rawdata[i * 10], sizeof(data_t) * 10);
fs << "]";
size_t sz = 0;
if (useMemory)
{
name = fs.releaseAndGetString();
sz = name.size();
}
else
{
fs.release();
std::ifstream f(name.c_str(), std::ios::in|std::ios::binary);
f.seekg(0, std::fstream::end);
sz = (size_t)f.tellg();
f.seekg(0, std::ios::beg);
std::vector<char> test_data(sz);
f.read(&test_data[0], sz);
f.close();
std::ifstream reference(name_34.c_str(), std::ios::in|std::ios::binary);
ASSERT_TRUE(reference.is_open());
reference.seekg(0, std::fstream::end);
size_t ref_sz = (size_t)reference.tellg();
reference.seekg(0, std::ios::beg);
std::vector<char> reference_data(ref_sz);
reference.read(&reference_data[0], ref_sz);
reference.close();
EXPECT_EQ(reference_data, test_data);
}
std::cout << "Storage size: " << sz << std::endl;
EXPECT_LE(sz, (size_t)6000);
}
{ /* read */
cv::FileStorage fs(name, cv::FileStorage::READ + (useMemory ? cv::FileStorage::MEMORY : 0));
/* mat */
fs["empty_2d_mat"] >> _em_in;
fs["normal_2d_mat"] >> _2d_in;
fs["normal_nd_mat"] >> _nd_in;
fs["random_mat"] >> _rd_in;
/* raw data */
std::vector<data_t>(rawdata_N).swap(rawdata);
fs["rawdata"].readRaw(data_t::signature(), (uchar*)&rawdata[0], rawdata.size() * sizeof(data_t));
fs.release();
}
int errors = 0;
for (int i = 0; i < (int)rawdata_N; i++)
{
EXPECT_EQ((int)rawdata[i].u1, 1);
EXPECT_EQ((int)rawdata[i].u2, 2);
EXPECT_EQ((int)rawdata[i].i1, 1);
EXPECT_EQ((int)rawdata[i].i2, 2);
EXPECT_EQ((int)rawdata[i].i3, 3);
EXPECT_EQ(rawdata[i].d1, 0.1);
EXPECT_EQ(rawdata[i].d2, 0.2);
EXPECT_EQ((int)rawdata[i].i4, i);
if (::testing::Test::HasNonfatalFailure())
{
printf("i = %d\n", i);
errors++;
}
if (errors >= 3)
break;
}
EXPECT_EQ(_em_in.rows , _em_out.rows);
EXPECT_EQ(_em_in.cols , _em_out.cols);
EXPECT_EQ(_em_in.depth(), _em_out.depth());
EXPECT_TRUE(_em_in.empty());
ASSERT_EQ(_2d_in.rows , _2d_out.rows);
ASSERT_EQ(_2d_in.cols , _2d_out.cols);
ASSERT_EQ(_2d_in.dims , _2d_out.dims);
ASSERT_EQ(_2d_in.depth(), _2d_out.depth());
errors = 0;
for(int i = 0; i < _2d_out.rows; ++i)
{
for (int j = 0; j < _2d_out.cols; ++j)
{
EXPECT_EQ(_2d_in.at<cv::Vec3b>(i, j), _2d_out.at<cv::Vec3b>(i, j));
if (::testing::Test::HasNonfatalFailure())
{
printf("i = %d, j = %d\n", i, j);
errors++;
}
if (errors >= 3)
{
i = _2d_out.rows;
break;
}
}
}
ASSERT_EQ(_nd_in.rows , _nd_out.rows);
ASSERT_EQ(_nd_in.cols , _nd_out.cols);
ASSERT_EQ(_nd_in.dims , _nd_out.dims);
ASSERT_EQ(_nd_in.depth(), _nd_out.depth());
EXPECT_EQ(0, cv::norm(_nd_in, _nd_out, NORM_INF));
ASSERT_EQ(_rd_in.rows , _rd_out.rows);
ASSERT_EQ(_rd_in.cols , _rd_out.cols);
ASSERT_EQ(_rd_in.dims , _rd_out.dims);
ASSERT_EQ(_rd_in.depth(), _rd_out.depth());
EXPECT_EQ(0, cv::norm(_rd_in, _rd_out, NORM_INF));
if (testReadWrite && !useMemory && !generateTestData)
{
EXPECT_EQ(0, remove(name.c_str()));
}
}
}
TEST(Core_InputOutput, filestorage_base64_basic_read_XML)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".xml", false);
}
TEST(Core_InputOutput, filestorage_base64_basic_read_YAML)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".yml", false);
}
TEST(Core_InputOutput, filestorage_base64_basic_read_JSON)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".json", false);
}
TEST(Core_InputOutput, filestorage_base64_basic_rw_XML)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".xml", true);
}
TEST(Core_InputOutput, filestorage_base64_basic_rw_YAML)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".yml", true);
}
TEST(Core_InputOutput, filestorage_base64_basic_rw_JSON)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".json", true);
}
TEST(Core_InputOutput, filestorage_base64_basic_memory_XML)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".xml", true, true);
}
TEST(Core_InputOutput, filestorage_base64_basic_memory_YAML)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".yml", true, true);
}
TEST(Core_InputOutput, filestorage_base64_basic_memory_JSON)
{
test_filestorage_basic(cv::FileStorage::WRITE_BASE64, ".json", true, true);
}
// issue #21851
TEST(Core_InputOutput, filestorage_heap_overflow)
{
const ::testing::TestInfo* const test_info = ::testing::UnitTest::GetInstance()->current_test_info();
CV_Assert(test_info);
std::string name = cv::tempfile();
const char data[] = {0x00, 0x2f, 0x4a, 0x4a, 0x50, 0x4a, 0x4a };
std::ofstream file;
file.open(name, std::ios_base::binary);
assert(file.is_open());
file.write(data, sizeof(data));
file.close();
// This just shouldn't segfault, otherwise it's fine
EXPECT_ANY_THROW(FileStorage(name, FileStorage::READ));
EXPECT_EQ(0, remove(name.c_str()));
}
TEST(Core_InputOutput, filestorage_base64_valid_call)
{
const ::testing::TestInfo* const test_info = ::testing::UnitTest::GetInstance()->current_test_info();
std::string basename = (test_info == 0)
? "filestorage_base64_valid_call"
: (std::string(test_info->test_case_name()) + "--" + test_info->name());
char const * filenames[] = {
"core_io_base64_other_test.yml",
"core_io_base64_other_test.xml",
"core_io_base64_other_test.json",
0
};
std::vector<int> rawdata(10, static_cast<int>(0x00010203));
cv::String str_out = "test_string";
for (int n = 0; n < 6; n++)
{
const int idx = n / 2;
const std::string mode_suffix = (n % 2 == 0) ? "" : "?base64";
std::string suffix_name = basename + "_" + filenames[idx];
std::string file_name = cv::tempfile(suffix_name.c_str());
std::string mode_file_name = file_name + mode_suffix;
SCOPED_TRACE(mode_file_name);
EXPECT_NO_THROW(
{
cv::FileStorage fs(mode_file_name, cv::FileStorage::WRITE_BASE64);
fs << "manydata" << "[";
fs << "[:";
for (int i = 0; i < 10; i++)
fs.writeRaw( "i", rawdata.data(), rawdata.size()*sizeof(rawdata[0]));
fs << "]";
fs << str_out;
fs << "]";
fs.release();
});
{
cv::FileStorage fs(file_name, cv::FileStorage::READ);
std::vector<int> data_in(rawdata.size());
fs["manydata"][0].readRaw("i", (uchar *)data_in.data(), data_in.size() * sizeof(data_in[0]));
EXPECT_TRUE(fs["manydata"][0].isSeq());
EXPECT_TRUE(std::equal(rawdata.begin(), rawdata.end(), data_in.begin()));
cv::String str_in;
fs["manydata"][1] >> str_in;
EXPECT_TRUE(fs["manydata"][1].isString());
EXPECT_EQ(str_in, str_out);
fs.release();
}
EXPECT_NO_THROW(
{
cv::FileStorage fs(mode_file_name, cv::FileStorage::WRITE);
fs << "manydata" << "[";
fs << str_out;
fs << "[";
for (int i = 0; i < 10; i++)
fs.writeRaw("i", rawdata.data(), rawdata.size()*sizeof(rawdata[0]));
fs << "]";
fs << "]";
fs.release();
});
{
cv::FileStorage fs(file_name, cv::FileStorage::READ);
cv::String str_in;
fs["manydata"][0] >> str_in;
EXPECT_TRUE(fs["manydata"][0].isString());
EXPECT_EQ(str_in, str_out);
std::vector<int> data_in(rawdata.size());
fs["manydata"][1].readRaw("i", (uchar *)data_in.data(), data_in.size() * sizeof(data_in[0]));
EXPECT_TRUE(fs["manydata"][1].isSeq());
EXPECT_TRUE(std::equal(rawdata.begin(), rawdata.end(), data_in.begin()));
fs.release();
}
EXPECT_EQ(0, remove(file_name.c_str()));
}
}
TEST(Core_InputOutput, filestorage_base64_invalid_call)
{
const ::testing::TestInfo* const test_info = ::testing::UnitTest::GetInstance()->current_test_info();
std::string basename = (test_info == 0)
? "filestorage_base64_invalid_call"
: (std::string(test_info->test_case_name()) + "--" + test_info->name());
char const * filenames[] = {
"core_io_base64_other_test.yml",
"core_io_base64_other_test.xml",
"core_io_base64_other_test.json",
0
};
for (int idx = 0; idx < 3; ++idx)
{
const string base_suffix = basename + '_' + filenames[idx];
std::string name = cv::tempfile(base_suffix.c_str());
EXPECT_NO_THROW({
cv::FileStorage fs(name, cv::FileStorage::WRITE);
fs << "rawdata" << "[";
fs << "[:";
});
EXPECT_NO_THROW({
cv::FileStorage fs(name, cv::FileStorage::WRITE);
fs << "rawdata" << "[";
fs << "[:";
fs.writeRaw("u", name.c_str(), 1);
});
remove(name.c_str());
}
}
TEST(Core_InputOutput, filestorage_yml_vec2i)
{
const std::string file_name = cv::tempfile("vec2i.yml");
cv::Vec2i vec(2, 1), ovec;
/* write */
{
cv::FileStorage fs(file_name, cv::FileStorage::WRITE);
fs << "prms0" << "{" << "vec0" << vec << "}";
fs.release();
}
/* read */
{
cv::FileStorage fs(file_name, cv::FileStorage::READ);
fs["prms0"]["vec0"] >> ovec;
fs.release();
}
EXPECT_EQ(vec(0), ovec(0));
EXPECT_EQ(vec(1), ovec(1));
remove(file_name.c_str());
}
TEST(Core_InputOutput, filestorage_json_comment)
{
String mem_str =
"{ /* comment */\n"
" \"key\": \"value\"\n"
" /************\n"
" * multiline comment\n"
" ************/\n"
" // 233\n"
" // \n"
"}\n"
;
String str;
EXPECT_NO_THROW(
{
cv::FileStorage fs(mem_str, cv::FileStorage::READ | cv::FileStorage::MEMORY);
fs["key"] >> str;
fs.release();
});
EXPECT_EQ(str, String("value"));
}
TEST(Core_InputOutput, filestorage_utf8_bom)
{
EXPECT_NO_THROW(
{
String content ="\xEF\xBB\xBF<?xml version=\"1.0\"?>\n<opencv_storage>\n</opencv_storage>\n";
cv::FileStorage fs(content, cv::FileStorage::READ | cv::FileStorage::MEMORY);
fs.release();
});
EXPECT_NO_THROW(
{
String content ="\xEF\xBB\xBF%YAML:1.0\n";
cv::FileStorage fs(content, cv::FileStorage::READ | cv::FileStorage::MEMORY);
fs.release();
});
EXPECT_NO_THROW(
{
String content ="\xEF\xBB\xBF{\n}\n";
cv::FileStorage fs(content, cv::FileStorage::READ | cv::FileStorage::MEMORY);
fs.release();
});
}
TEST(Core_InputOutput, filestorage_vec_vec_io)
{
std::vector<std::vector<Mat> > outputMats(3);
for(size_t i = 0; i < outputMats.size(); i++)
{
outputMats[i].resize(i+1);
for(size_t j = 0; j < outputMats[i].size(); j++)
{
outputMats[i][j] = Mat::eye((int)i + 1, (int)i + 1, CV_8U);
}
}
String basename = "vec_vec_io_test.";
std::vector<String> formats;
formats.push_back("xml");
formats.push_back("yml");
formats.push_back("json");
for(size_t i = 0; i < formats.size(); i++)
{
const String basename_plus(basename + formats[i]);
const String fileName = tempfile(basename_plus.c_str());
FileStorage writer(fileName, FileStorage::WRITE);
writer << "vecVecMat" << outputMats;
writer.release();
FileStorage reader(fileName, FileStorage::READ);
std::vector<std::vector<Mat> > testMats;
reader["vecVecMat"] >> testMats;
ASSERT_EQ(testMats.size(), testMats.size());
for(size_t j = 0; j < testMats.size(); j++)
{
ASSERT_EQ(testMats[j].size(), outputMats[j].size());
for(size_t k = 0; k < testMats[j].size(); k++)
{
ASSERT_TRUE(cvtest::norm(outputMats[j][k] - testMats[j][k], NORM_INF) == 0);
}
}
reader.release();
remove(fileName.c_str());
}
}
TEST(Core_InputOutput, filestorage_yaml_advanvced_type_heading)
{
String content = "%YAML:1.0\n cameraMatrix: !<tag:yaml.org,2002:opencv-matrix>\n"
" rows: 1\n"
" cols: 1\n"
" dt: d\n"
" data: [ 1. ]";
cv::FileStorage fs(content, cv::FileStorage::READ | cv::FileStorage::MEMORY);
cv::Mat inputMatrix;
cv::Mat actualMatrix = cv::Mat::eye(1, 1, CV_64F);
fs["cameraMatrix"] >> inputMatrix;
ASSERT_EQ(cv::norm(inputMatrix, actualMatrix, NORM_INF), 0.);
}
TEST(Core_InputOutput, filestorage_matx_io)
{
Matx33d matxTest(1.234, 2, 3, 4, 5, 6, 7, 8, 9.876);
FileStorage writer("", FileStorage::WRITE | FileStorage::MEMORY);
writer << "matxTest" << matxTest;
String content = writer.releaseAndGetString();
FileStorage reader(content, FileStorage::READ | FileStorage::MEMORY);
Matx33d matxTestRead;
reader["matxTest"] >> matxTestRead;
ASSERT_TRUE( cv::norm(matxTest, matxTestRead, NORM_INF) == 0 );
reader.release();
}
TEST(Core_InputOutput, filestorage_matx_io_size_mismatch)
{
Matx32d matxTestWrongSize(1, 2, 3, 4, 5, 6);
FileStorage writer("", FileStorage::WRITE | FileStorage::MEMORY);
writer << "matxTestWrongSize" << matxTestWrongSize;
String content = writer.releaseAndGetString();
FileStorage reader(content, FileStorage::READ | FileStorage::MEMORY);
Matx33d matxTestRead;
try
{
reader["matxTestWrongSize"] >> matxTestRead;
FAIL() << "wrong size matrix read but no exception thrown";
}
catch (const std::exception&)
{
}
reader.release();
}
TEST(Core_InputOutput, filestorage_matx_io_with_mat)
{
Mat normalMat = Mat::eye(3, 3, CV_64F);
FileStorage writer("", FileStorage::WRITE | FileStorage::MEMORY);
writer << "normalMat" << normalMat;
String content = writer.releaseAndGetString();
FileStorage reader(content, FileStorage::READ | FileStorage::MEMORY);
Matx33d matxTestRead;
reader["normalMat"] >> matxTestRead;
ASSERT_TRUE( cv::norm(Mat::eye(3, 3, CV_64F), matxTestRead, NORM_INF) == 0 );
reader.release();
}
TEST(Core_InputOutput, filestorage_keypoints_vec_vec_io)
{
vector<vector<KeyPoint> > kptsVec;
vector<KeyPoint> kpts;
kpts.push_back(KeyPoint(0, 0, 1.1f));
kpts.push_back(KeyPoint(1, 1, 1.1f));
kptsVec.push_back(kpts);
kpts.clear();
kpts.push_back(KeyPoint(0, 0, 1.1f, 10.1f, 34.5f, 10, 11));
kptsVec.push_back(kpts);
FileStorage writer("", FileStorage::WRITE + FileStorage::MEMORY + FileStorage::FORMAT_XML);
writer << "keypoints" << kptsVec;
String content = writer.releaseAndGetString();
FileStorage reader(content, FileStorage::READ + FileStorage::MEMORY);
vector<vector<KeyPoint> > readKptsVec;
reader["keypoints"] >> readKptsVec;
ASSERT_EQ(kptsVec.size(), readKptsVec.size());
for(size_t i = 0; i < kptsVec.size(); i++)
{
ASSERT_EQ(kptsVec[i].size(), readKptsVec[i].size());
for(size_t j = 0; j < kptsVec[i].size(); j++)
{
ASSERT_FLOAT_EQ(kptsVec[i][j].pt.x, readKptsVec[i][j].pt.x);
ASSERT_FLOAT_EQ(kptsVec[i][j].pt.y, readKptsVec[i][j].pt.y);
ASSERT_FLOAT_EQ(kptsVec[i][j].angle, readKptsVec[i][j].angle);
ASSERT_FLOAT_EQ(kptsVec[i][j].size, readKptsVec[i][j].size);
ASSERT_FLOAT_EQ(kptsVec[i][j].response, readKptsVec[i][j].response);
ASSERT_EQ(kptsVec[i][j].octave, readKptsVec[i][j].octave);
ASSERT_EQ(kptsVec[i][j].class_id, readKptsVec[i][j].class_id);
}
}
}
TEST(Core_InputOutput, FileStorage_DMatch)
{
cv::FileStorage fs("dmatch.yml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
cv::DMatch d(1, 2, 3, -1.5f);
EXPECT_NO_THROW(fs << "d" << d);
cv::String fs_result = fs.releaseAndGetString();
EXPECT_STREQ(fs_result.c_str(), "%YAML:1.0\n---\nd: [ 1, 2, 3, -1.5 ]\n");
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
cv::DMatch d_read;
ASSERT_NO_THROW(fs_read["d"] >> d_read);
EXPECT_EQ(d.queryIdx, d_read.queryIdx);
EXPECT_EQ(d.trainIdx, d_read.trainIdx);
EXPECT_EQ(d.imgIdx, d_read.imgIdx);
EXPECT_EQ(d.distance, d_read.distance);
}
TEST(Core_InputOutput, FileStorage_DMatch_vector)
{
cv::FileStorage fs("dmatch.yml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
cv::DMatch d1(1, 2, 3, -1.5f);
cv::DMatch d2(2, 3, 4, 1.5f);
cv::DMatch d3(3, 2, 1, 0.5f);
std::vector<cv::DMatch> dv;
dv.push_back(d1);
dv.push_back(d2);
dv.push_back(d3);
EXPECT_NO_THROW(fs << "dv" << dv);
cv::String fs_result = fs.releaseAndGetString();
EXPECT_STREQ(fs_result.c_str(),
"%YAML:1.0\n"
"---\n"
"dv:\n"
" - [ 1, 2, 3, -1.5 ]\n"
" - [ 2, 3, 4, 1.5 ]\n"
" - [ 3, 2, 1, 0.5 ]\n"
);
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::vector<cv::DMatch> dv_read;
ASSERT_NO_THROW(fs_read["dv"] >> dv_read);
ASSERT_EQ(dv.size(), dv_read.size());
for (size_t i = 0; i < dv.size(); i++)
{
EXPECT_EQ(dv[i].queryIdx, dv_read[i].queryIdx);
EXPECT_EQ(dv[i].trainIdx, dv_read[i].trainIdx);
EXPECT_EQ(dv[i].imgIdx, dv_read[i].imgIdx);
EXPECT_EQ(dv[i].distance, dv_read[i].distance);
}
}
TEST(Core_InputOutput, FileStorage_DMatch_vector_vector)
{
cv::FileStorage fs("dmatch.yml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
cv::DMatch d1(1, 2, 3, -1.5f);
cv::DMatch d2(2, 3, 4, 1.5f);
cv::DMatch d3(3, 2, 1, 0.5f);
std::vector<cv::DMatch> dv1;
dv1.push_back(d1);
dv1.push_back(d2);
dv1.push_back(d3);
std::vector<cv::DMatch> dv2;
dv2.push_back(d3);
dv2.push_back(d1);
std::vector< std::vector<cv::DMatch> > dvv;
dvv.push_back(dv1);
dvv.push_back(dv2);
EXPECT_NO_THROW(fs << "dvv" << dvv);
cv::String fs_result = fs.releaseAndGetString();
#ifndef OPENCV_TRAITS_ENABLE_DEPRECATED
EXPECT_STREQ(fs_result.c_str(),
"%YAML:1.0\n"
"---\n"
"dvv:\n"
" -\n"
" - [ 1, 2, 3, -1.5 ]\n"
" - [ 2, 3, 4, 1.5 ]\n"
" - [ 3, 2, 1, 0.5 ]\n"
" -\n"
" - [ 3, 2, 1, 0.5 ]\n"
" - [ 1, 2, 3, -1.5 ]\n"
);
#endif // OPENCV_TRAITS_ENABLE_DEPRECATED
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::vector< std::vector<cv::DMatch> > dvv_read;
ASSERT_NO_THROW(fs_read["dvv"] >> dvv_read);
ASSERT_EQ(dvv.size(), dvv_read.size());
for (size_t j = 0; j < dvv.size(); j++)
{
const std::vector<cv::DMatch>& dv = dvv[j];
const std::vector<cv::DMatch>& dv_read = dvv_read[j];
ASSERT_EQ(dvv.size(), dvv_read.size());
for (size_t i = 0; i < dv.size(); i++)
{
EXPECT_EQ(dv[i].queryIdx, dv_read[i].queryIdx);
EXPECT_EQ(dv[i].trainIdx, dv_read[i].trainIdx);
EXPECT_EQ(dv[i].imgIdx, dv_read[i].imgIdx);
EXPECT_EQ(dv[i].distance, dv_read[i].distance);
}
}
}
TEST(Core_InputOutput, FileStorage_KeyPoint)
{
cv::FileStorage fs("keypoint.xml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
cv::KeyPoint k(Point2f(1, 2), 16, 0, 100, 1, -1);
EXPECT_NO_THROW(fs << "k" << k);
cv::String fs_result = fs.releaseAndGetString();
EXPECT_STREQ(fs_result.c_str(),
"<?xml version=\"1.0\"?>\n"
"<opencv_storage>\n"
"<k>\n"
" 1. 2. 16. 0. 100. 1 -1</k>\n"
"</opencv_storage>\n"
);
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
cv::KeyPoint k_read;
ASSERT_NO_THROW(fs_read["k"] >> k_read);
EXPECT_EQ(k.pt, k_read.pt);
EXPECT_EQ(k.size, k_read.size);
EXPECT_EQ(k.angle, k_read.angle);
EXPECT_EQ(k.response, k_read.response);
EXPECT_EQ(k.octave, k_read.octave);
EXPECT_EQ(k.class_id, k_read.class_id);
}
TEST(Core_InputOutput, FileStorage_KeyPoint_vector)
{
cv::FileStorage fs("keypoint.xml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
cv::KeyPoint k1(Point2f(1, 2), 16, 0, 100, 1, -1);
cv::KeyPoint k2(Point2f(2, 3), 16, 45, 100, 1, -1);
cv::KeyPoint k3(Point2f(1, 2), 16, 90, 100, 1, -1);
std::vector<cv::KeyPoint> kv;
kv.push_back(k1);
kv.push_back(k2);
kv.push_back(k3);
EXPECT_NO_THROW(fs << "kv" << kv);
cv::String fs_result = fs.releaseAndGetString();
EXPECT_STREQ(fs_result.c_str(),
"<?xml version=\"1.0\"?>\n"
"<opencv_storage>\n"
"<kv>\n"
" <_>\n"
" 1. 2. 16. 0. 100. 1 -1</_>\n"
" <_>\n"
" 2. 3. 16. 45. 100. 1 -1</_>\n"
" <_>\n"
" 1. 2. 16. 90. 100. 1 -1</_></kv>\n"
"</opencv_storage>\n"
);
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::vector<cv::KeyPoint> kv_read;
ASSERT_NO_THROW(fs_read["kv"] >> kv_read);
ASSERT_EQ(kv.size(), kv_read.size());
for (size_t i = 0; i < kv.size(); i++)
{
EXPECT_EQ(kv[i].pt, kv_read[i].pt);
EXPECT_EQ(kv[i].size, kv_read[i].size);
EXPECT_EQ(kv[i].angle, kv_read[i].angle);
EXPECT_EQ(kv[i].response, kv_read[i].response);
EXPECT_EQ(kv[i].octave, kv_read[i].octave);
EXPECT_EQ(kv[i].class_id, kv_read[i].class_id);
}
}
TEST(Core_InputOutput, FileStorage_KeyPoint_vector_vector)
{
cv::FileStorage fs("keypoint.xml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
cv::KeyPoint k1(Point2f(1, 2), 16, 0, 100, 1, -1);
cv::KeyPoint k2(Point2f(2, 3), 16, 45, 100, 1, -1);
cv::KeyPoint k3(Point2f(1, 2), 16, 90, 100, 1, -1);
std::vector<cv::KeyPoint> kv1;
kv1.push_back(k1);
kv1.push_back(k2);
kv1.push_back(k3);
std::vector<cv::KeyPoint> kv2;
kv2.push_back(k3);
kv2.push_back(k1);
std::vector< std::vector<cv::KeyPoint> > kvv;
kvv.push_back(kv1);
kvv.push_back(kv2);
EXPECT_NO_THROW(fs << "kvv" << kvv);
cv::String fs_result = fs.releaseAndGetString();
#ifndef OPENCV_TRAITS_ENABLE_DEPRECATED
EXPECT_STREQ(fs_result.c_str(),
"<?xml version=\"1.0\"?>\n"
"<opencv_storage>\n"
"<kvv>\n"
" <_>\n"
" <_>\n"
" 1. 2. 16. 0. 100. 1 -1</_>\n"
" <_>\n"
" 2. 3. 16. 45. 100. 1 -1</_>\n"
" <_>\n"
" 1. 2. 16. 90. 100. 1 -1</_></_>\n"
" <_>\n"
" <_>\n"
" 1. 2. 16. 90. 100. 1 -1</_>\n"
" <_>\n"
" 1. 2. 16. 0. 100. 1 -1</_></_></kvv>\n"
"</opencv_storage>\n"
);
#endif //OPENCV_TRAITS_ENABLE_DEPRECATED
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::vector< std::vector<cv::KeyPoint> > kvv_read;
ASSERT_NO_THROW(fs_read["kvv"] >> kvv_read);
ASSERT_EQ(kvv.size(), kvv_read.size());
for (size_t j = 0; j < kvv.size(); j++)
{
const std::vector<cv::KeyPoint>& kv = kvv[j];
const std::vector<cv::KeyPoint>& kv_read = kvv_read[j];
ASSERT_EQ(kvv.size(), kvv_read.size());
for (size_t i = 0; i < kv.size(); i++)
{
EXPECT_EQ(kv[i].pt, kv_read[i].pt);
EXPECT_EQ(kv[i].size, kv_read[i].size);
EXPECT_EQ(kv[i].angle, kv_read[i].angle);
EXPECT_EQ(kv[i].response, kv_read[i].response);
EXPECT_EQ(kv[i].octave, kv_read[i].octave);
EXPECT_EQ(kv[i].class_id, kv_read[i].class_id);
}
}
}
#ifdef CV__LEGACY_PERSISTENCE
TEST(Core_InputOutput, FileStorage_LEGACY_DMatch_vector)
{
cv::DMatch d1(1, 2, 3, -1.5f);
cv::DMatch d2(2, 3, 4, 1.5f);
cv::DMatch d3(3, 2, 1, 0.5f);
std::vector<cv::DMatch> dv;
dv.push_back(d1);
dv.push_back(d2);
dv.push_back(d3);
String fs_result =
"<?xml version=\"1.0\"?>\n"
"<opencv_storage>\n"
"<dv>\n"
" 1 2 3 -1.5000000000000000e+00 2 3 4 1.5000000000000000e+00 3 2 1\n"
" 5.0000000000000000e-01</dv>\n"
"</opencv_storage>\n"
;
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::vector<cv::DMatch> dv_read;
ASSERT_NO_THROW(fs_read["dv"] >> dv_read);
ASSERT_EQ(dv.size(), dv_read.size());
for (size_t i = 0; i < dv.size(); i++)
{
EXPECT_EQ(dv[i].queryIdx, dv_read[i].queryIdx);
EXPECT_EQ(dv[i].trainIdx, dv_read[i].trainIdx);
EXPECT_EQ(dv[i].imgIdx, dv_read[i].imgIdx);
EXPECT_EQ(dv[i].distance, dv_read[i].distance);
}
}
TEST(Core_InputOutput, FileStorage_LEGACY_KeyPoint_vector)
{
cv::KeyPoint k1(Point2f(1, 2), 16, 0, 100, 1, -1);
cv::KeyPoint k2(Point2f(2, 3), 16, 45, 100, 1, -1);
cv::KeyPoint k3(Point2f(1, 2), 16, 90, 100, 1, -1);
std::vector<cv::KeyPoint> kv;
kv.push_back(k1);
kv.push_back(k2);
kv.push_back(k3);
cv::String fs_result =
"<?xml version=\"1.0\"?>\n"
"<opencv_storage>\n"
"<kv>\n"
" 1. 2. 16. 0. 100. 1 -1\n"
" 2. 3. 16. 45. 100. 1 -1\n"
" 1. 2. 16. 90. 100. 1 -1</kv>\n"
"</opencv_storage>\n"
;
cv::FileStorage fs_read(fs_result, cv::FileStorage::READ | cv::FileStorage::MEMORY);
std::vector<cv::KeyPoint> kv_read;
ASSERT_NO_THROW(fs_read["kv"] >> kv_read);
ASSERT_EQ(kv.size(), kv_read.size());
for (size_t i = 0; i < kv.size(); i++)
{
EXPECT_EQ(kv[i].pt, kv_read[i].pt);
EXPECT_EQ(kv[i].size, kv_read[i].size);
EXPECT_EQ(kv[i].angle, kv_read[i].angle);
EXPECT_EQ(kv[i].response, kv_read[i].response);
EXPECT_EQ(kv[i].octave, kv_read[i].octave);
EXPECT_EQ(kv[i].class_id, kv_read[i].class_id);
}
}
#endif
TEST(Core_InputOutput, FileStorage_format_xml)
{
FileStorage fs;
fs.open("opencv_storage.xml", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_XML, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_xml_gz)
{
FileStorage fs;
fs.open("opencv_storage.xml.gz", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_XML, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_json)
{
FileStorage fs;
fs.open("opencv_storage.json", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_JSON, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_json_gz)
{
FileStorage fs;
fs.open("opencv_storage.json.gz", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_JSON, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_yaml)
{
FileStorage fs;
fs.open("opencv_storage.yaml", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_YAML, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_yaml_gz)
{
FileStorage fs;
fs.open("opencv_storage.yaml.gz", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_YAML, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_yml)
{
FileStorage fs;
fs.open("opencv_storage.yml", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_YAML, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_format_yml_gz)
{
FileStorage fs;
fs.open("opencv_storage.yml.gz", FileStorage::WRITE | FileStorage::MEMORY);
EXPECT_EQ(FileStorage::FORMAT_YAML, fs.getFormat());
}
TEST(Core_InputOutput, FileStorage_json_named_nodes)
{
std::string test =
"{ "
"\"int_value\": -324,"
"\"map_value\": {"
"\"str_value\": \"mystring\""
"},"
"\"array\": [0.2, 0.1]"
"}";
FileStorage fs(test, FileStorage::READ | FileStorage::MEMORY);
ASSERT_TRUE(fs["int_value"].isNamed());
ASSERT_TRUE(fs["map_value"].isNamed());
ASSERT_TRUE(fs["map_value"]["str_value"].isNamed());
ASSERT_TRUE(fs["array"].isNamed());
ASSERT_FALSE(fs["array"][0].isNamed());
ASSERT_FALSE(fs["array"][1].isNamed());
ASSERT_EQ(fs["int_value"].name(), "int_value");
ASSERT_EQ(fs["map_value"].name(), "map_value");
ASSERT_EQ(fs["map_value"]["str_value"].name(), "str_value");
ASSERT_EQ(fs["array"].name(), "array");
fs.release();
}
TEST(Core_InputOutput, FileStorage_json_bool)
{
std::string test =
"{ "
"\"str_true\": \"true\","
"\"map_value\": {"
"\"int_value\": -33333,\n"
"\"bool_true\": true,"
"\"str_false\": \"false\","
"},"
"\"bool_false\": false, \n"
"\"array\": [0.1, 0.2]"
"}";
FileStorage fs(test, FileStorage::READ | FileStorage::MEMORY);
ASSERT_TRUE(fs["str_true"].isString());
ASSERT_TRUE(fs["map_value"]["bool_true"].isInt());
ASSERT_TRUE(fs["map_value"]["str_false"].isString());
ASSERT_TRUE(fs["bool_false"].isInt());
ASSERT_EQ((std::string)fs["str_true"], "true");
ASSERT_EQ((int)fs["map_value"]["bool_true"], 1);
ASSERT_EQ((std::string)fs["map_value"]["str_false"], "false");
ASSERT_EQ((int)fs["bool_false"], 0);
std::vector<String> keys = fs["map_value"].keys();
ASSERT_EQ((int)keys.size(), 3);
ASSERT_EQ(keys[0], "int_value");
ASSERT_EQ(keys[1], "bool_true");
ASSERT_EQ(keys[2], "str_false");
fs.release();
}
TEST(Core_InputOutput, FileStorage_free_file_after_exception)
{
const std::string fileName = cv::tempfile("FileStorage_free_file_after_exception_test.yml");
const std::string content = "%YAML:1.0\n cameraMatrix;:: !<tag:yaml.org,2002:opencv-matrix>\n";
std::fstream testFile;
testFile.open(fileName.c_str(), std::fstream::out);
if(!testFile.is_open()) FAIL();
testFile << content;
testFile.close();
try
{
FileStorage fs(fileName, FileStorage::READ + FileStorage::FORMAT_YAML);
FAIL();
}
catch (const std::exception&)
{
}
ASSERT_EQ(0, std::remove(fileName.c_str()));
}
TEST(Core_InputOutput, FileStorage_write_to_sequence)
{
const std::vector<std::string> formatExts = { ".yml", ".json", ".xml" };
for (const auto& ext : formatExts)
{
const std::string name = tempfile(ext.c_str());
FileStorage fs(name, FileStorage::WRITE);
std::vector<int> in = { 23, 42 };
fs.startWriteStruct("some_sequence", cv::FileNode::SEQ);
for (int i : in)
fs.write("", i);
fs.endWriteStruct();
fs.release();
FileStorage fsIn(name, FileStorage::READ);
FileNode seq = fsIn["some_sequence"];
FileNodeIterator it = seq.begin(), it_end = seq.end();
std::vector<int> out;
for (; it != it_end; ++it)
out.push_back((int)*it);
EXPECT_EQ(in, out);
EXPECT_EQ(0, remove(name.c_str()));
}
}
TEST(Core_InputOutput, FileStorage_YAML_parse_multiple_documents)
{
const std::string filename = cv::tempfile("FileStorage_YAML_parse_multiple_documents.yml");
FileStorage fs;
fs.open(filename, FileStorage::WRITE);
fs << "a" << 42;
fs.release();
fs.open(filename, FileStorage::APPEND);
fs << "b" << 1988;
fs.release();
fs.open(filename, FileStorage::READ);
EXPECT_EQ(42, (int)fs["a"]);
EXPECT_EQ(1988, (int)fs["b"]);
EXPECT_EQ(42, (int)fs.root(0)["a"]);
EXPECT_TRUE(fs.root(0)["b"].empty());
EXPECT_TRUE(fs.root(1)["a"].empty());
EXPECT_EQ(1988, (int)fs.root(1)["b"]);
fs.release();
ASSERT_EQ(0, std::remove(filename.c_str()));
}
TEST(Core_InputOutput, FileStorage_JSON_VeryLongLines)
{
for( int iter = 0; iter < 2; iter++ )
{
std::string temp_path = cv::tempfile("temp.json");
{
std::ofstream ofs(temp_path);
ofs << "{ ";
int prev_len = 0, start = 0;
for (int i = 0; i < 52500; i++)
{
std::string str = cv::format("\"KEY%d\"", i);
ofs << str;
if(iter == 1 && i - start > prev_len)
{
// build a stairway with increasing text row width
ofs << "\n";
prev_len = i - start;
start = i;
}
str = cv::format(": \"VALUE%d\", ", i);
ofs << str;
}
ofs << "}";
}
{
cv::FileStorage fs(temp_path, cv::FileStorage::READ);
char key[16], val0[16];
std::string val;
for(int i = 0; i < 52500; i += 100)
{
snprintf(key, sizeof(key), "KEY%d", i);
snprintf(val0, sizeof(val0), "VALUE%d", i);
fs[key] >> val;
ASSERT_EQ(val, val0);
}
}
remove(temp_path.c_str());
}
}
TEST(Core_InputOutput, FileStorage_empty_16823)
{
std::string fname = tempfile("test_fs_empty.yml");
{
// create empty file
std::ofstream f(fname.c_str(), std::ios::out);
}
try
{
FileStorage fs(fname, FileStorage::READ);
ADD_FAILURE() << "Exception must be thrown for empty file.";
}
catch (const cv::Exception&)
{
// expected way
// closed files can be checked manually through 'strace'
}
catch (const std::exception& e)
{
ADD_FAILURE() << "Unexpected exception: " << e.what();
}
catch (...)
{
ADD_FAILURE() << "Unexpected unknown C++ exception";
}
EXPECT_EQ(0, remove(fname.c_str()));
}
TEST(Core_InputOutput, FileStorage_open_empty_16823)
{
std::string fname = tempfile("test_fs_open_empty.yml");
{
// create empty file
std::ofstream f(fname.c_str(), std::ios::out);
}
FileStorage fs;
try
{
fs.open(fname, FileStorage::READ);
ADD_FAILURE() << "Exception must be thrown for empty file.";
}
catch (const cv::Exception&)
{
// expected way
// closed files can be checked manually through 'strace'
}
catch (const std::exception& e)
{
ADD_FAILURE() << "Unexpected exception: " << e.what();
}
catch (...)
{
ADD_FAILURE() << "Unexpected unknown C++ exception";
}
EXPECT_EQ(0, remove(fname.c_str()));
}
TEST(Core_InputOutput, FileStorage_copy_constructor_17412)
{
std::string fname = tempfile("test.yml");
FileStorage fs_orig(fname, cv::FileStorage::WRITE);
fs_orig << "string" << "wat";
fs_orig.release();
// no crash anymore
cv::FileStorage fs;
fs = cv::FileStorage(fname, cv::FileStorage::READ);
std::string s;
fs["string"] >> s;
EXPECT_EQ(s, "wat");
EXPECT_EQ(0, remove(fname.c_str()));
}
TEST(Core_InputOutput, FileStorage_copy_constructor_17412_heap)
{
std::string fname = tempfile("test.yml");
FileStorage fs_orig(fname, cv::FileStorage::WRITE);
fs_orig << "string" << "wat";
fs_orig.release();
// no crash anymore
cv::FileStorage fs;
// use heap to allow valgrind detections
{
cv::FileStorage* fs2 = new cv::FileStorage(fname, cv::FileStorage::READ);
fs = *fs2;
delete fs2;
}
std::string s;
fs["string"] >> s;
EXPECT_EQ(s, "wat");
EXPECT_EQ(0, remove(fname.c_str()));
}
static void test_20279(FileStorage& fs)
{
Mat m32fc1(5, 10, CV_32FC1, Scalar::all(0));
for (size_t i = 0; i < m32fc1.total(); i++)
{
float v = (float)i;
m32fc1.at<float>((int)i) = v * 0.5f;
}
Mat m16fc1;
// produces CV_16S output: convertFp16(m32fc1, m16fc1);
m32fc1.convertTo(m16fc1, CV_16FC1);
EXPECT_EQ(CV_16FC1, m16fc1.type()) << typeToString(m16fc1.type());
//std::cout << m16fc1 << std::endl;
Mat m32fc3(4, 3, CV_32FC3, Scalar::all(0));
for (size_t i = 0; i < m32fc3.total(); i++)
{
float v = (float)i;
m32fc3.at<Vec3f>((int)i) = Vec3f(v, v * 0.2f, -v);
}
Mat m16fc3;
m32fc3.convertTo(m16fc3, CV_16FC3);
EXPECT_EQ(CV_16FC3, m16fc3.type()) << typeToString(m16fc3.type());
//std::cout << m16fc3 << std::endl;
fs << "m16fc1" << m16fc1;
fs << "m16fc3" << m16fc3;
string content = fs.releaseAndGetString();
if (cvtest::debugLevel > 0) std::cout << content << std::endl;
FileStorage fs_read(content, FileStorage::READ + FileStorage::MEMORY);
Mat m16fc1_result;
Mat m16fc3_result;
fs_read["m16fc1"] >> m16fc1_result;
ASSERT_FALSE(m16fc1_result.empty());
EXPECT_EQ(CV_16FC1, m16fc1_result.type()) << typeToString(m16fc1_result.type());
EXPECT_LE(cvtest::norm(m16fc1_result, m16fc1, NORM_INF), 1e-2);
fs_read["m16fc3"] >> m16fc3_result;
ASSERT_FALSE(m16fc3_result.empty());
EXPECT_EQ(CV_16FC3, m16fc3_result.type()) << typeToString(m16fc3_result.type());
EXPECT_LE(cvtest::norm(m16fc3_result, m16fc3, NORM_INF), 1e-2);
}
TEST(Core_InputOutput, FileStorage_16F_xml)
{
FileStorage fs("test.xml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
test_20279(fs);
}
TEST(Core_InputOutput, FileStorage_16F_yml)
{
FileStorage fs("test.yml", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
test_20279(fs);
}
TEST(Core_InputOutput, FileStorage_16F_json)
{
FileStorage fs("test.json", cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
test_20279(fs);
}
TEST(Core_InputOutput, FileStorage_invalid_path_regression_21448_YAML)
{
FileStorage fs("invalid_path/test.yaml", cv::FileStorage::WRITE);
EXPECT_FALSE(fs.isOpened());
EXPECT_ANY_THROW(fs.write("K", 1));
fs.release();
}
TEST(Core_InputOutput, FileStorage_invalid_path_regression_21448_XML)
{
FileStorage fs("invalid_path/test.xml", cv::FileStorage::WRITE);
EXPECT_FALSE(fs.isOpened());
EXPECT_ANY_THROW(fs.write("K", 1));
fs.release();
}
TEST(Core_InputOutput, FileStorage_invalid_path_regression_21448_JSON)
{
FileStorage fs("invalid_path/test.json", cv::FileStorage::WRITE);
EXPECT_FALSE(fs.isOpened());
EXPECT_ANY_THROW(fs.write("K", 1));
fs.release();
}
// see https://github.com/opencv/opencv/issues/25073
typedef testing::TestWithParam< std::string > Core_InputOutput_regression_25073;
TEST_P(Core_InputOutput_regression_25073, my_double)
{
cv::String res = "";
double my_double = 0.5;
FileStorage fs( GetParam(), cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
EXPECT_NO_THROW( fs << "my_double" << my_double );
EXPECT_NO_THROW( fs << "my_int" << 5 );
EXPECT_NO_THROW( res = fs.releaseAndGetString() );
EXPECT_NE( res.find("0.5"), String::npos ) << res; // Found "0.5"
EXPECT_EQ( res.find("5.0"), String::npos ) << res; // Not Found "5.000000000000000000e-01"
fs.release();
}
TEST_P(Core_InputOutput_regression_25073, my_float)
{
cv::String res = "";
float my_float = 0.5;
FileStorage fs( GetParam(), cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
EXPECT_NO_THROW( fs << "my_float" << my_float );
EXPECT_NO_THROW( fs << "my_int" << 5 );
EXPECT_NO_THROW( res = fs.releaseAndGetString() );
EXPECT_NE( res.find("0.5"), String::npos ) << res; // Found "0.5"
EXPECT_EQ( res.find("5.0"), String::npos ) << res; // Not Found "5.00000000e-01",
fs.release();
}
TEST_P(Core_InputOutput_regression_25073, my_float16)
{
cv::String res = "";
cv::float16_t my_float16(0.5);
FileStorage fs( GetParam(), cv::FileStorage::WRITE | cv::FileStorage::MEMORY);
EXPECT_NO_THROW( fs << "my_float16" << my_float16 );
EXPECT_NO_THROW( fs << "my_int" << 5 );
EXPECT_NO_THROW( res = fs.releaseAndGetString() );
EXPECT_NE( res.find("0.5"), String::npos ) << res; // Found "0.5".
EXPECT_EQ( res.find("5.0"), String::npos ) << res; // Not Found "5.0000e-01".
fs.release();
}
INSTANTIATE_TEST_CASE_P( /*nothing*/,
Core_InputOutput_regression_25073,
Values("test.json", "test.xml", "test.yml") );
}} // namespace
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