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;

{

CvSparseMatIterator it1;

CvSparseNode* node1;

int depth = CV_MAT_DEPTH(m1->type);

if( m1->heap->active_count != m2->heap->active_count ||

m1->dims != m2->dims || CV_MAT_TYPE(m1->type) != CV_MAT_TYPE(m2->type) )

return false;

for( node1 = cvInitSparseMatIterator( m1, &it1 );

node1 != 0; node1 = cvGetNextSparseNode( &it1 ))

{

uchar* v1 = (uchar*)CV_NODE_VAL(m1,node1);

uchar* v2 = cvPtrND( m2, CV_NODE_IDX(m1,node1), 0, 0, &node1->hashval );

if( !v2 )

return false;

if( depth == CV_8U || depth == CV_8S )

{

if( *v1 != *v2 )

return false;

}

else if( depth == CV_16U || depth == CV_16S )

{

if( *(ushort*)v1 != *(ushort*)v2 )

return false;

}

else if( depth == CV_32S )

{

if( *(int*)v1 != *(int*)v2 )

return false;

}

else if( depth == CV_32F )

{

if( fabs(*(float*)v1 - *(float*)v2) > eps*(fabs(*(float*)v2) + 1) )

return false;

}

else if( fabs(*(double*)v1 - *(double*)v2) > eps*(fabs(*(double*)v2) + 1) )

return false;

}

return true;

{

Core_IOTest() { }

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));

multiply(test_mat, test_mat_scale, test_mat);

}

CvSeq* seq = cvCreateSeq(test_mat.type(), (int)sizeof(CvSeq),

(int)test_mat.elemSize(), storage);

cvSeqPushMulti(seq, test_mat.ptr(), test_mat.cols*test_mat.rows);

CvGraph* graph = cvCreateGraph( CV_ORIENTED_GRAPH,

sizeof(CvGraph), sizeof(CvGraphVtx),

sizeof(CvGraphEdge), storage );

int edges[][2] = {{0,1},{1,2},{2,0},{0,3},{3,4},{4,1}};

int i, vcount = 5, ecount = 6;

for( i = 0; i < vcount; i++ )

cvGraphAddVtx(graph);

for( i = 0; i < ecount; i++ )

{

CvGraphEdge* edge;

cvGraphAddEdge(graph, edges[i][0], edges[i][1], 0, &edge);

edge->weight = (float)(i+1);

}

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));

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, (int)(sizeof(arr)/sizeof(arr[0])));

fs << "]" << "}";

cvWriteComment(*fs, "test comment", 0);

fs.writeObj("test_seq", seq);

fs.writeObj("test_graph",graph);

CvGraph* graph2 = (CvGraph*)cvClone(graph);

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;

}

CvMat* m = (CvMat*)fs["test_mat"].readObj();

CvMat _test_mat = test_mat;

double max_diff = 0;

CvMat stub1, _test_stub1;

cvReshape(m, &stub1, 1, 0);

cvReshape(&_test_mat, &_test_stub1, 1, 0);

vector<int> pt;

if( !m || !CV_IS_MAT(m) || m->rows != test_mat.rows || m->cols != test_mat.cols ||

cvtest::cmpEps( cv::cvarrToMat(&stub1), cv::cvarrToMat(&_test_stub1), &max_diff, 0, &pt, true) < 0 )

{

ts->printf( cvtest::TS::LOG, "the read matrix is not correct: (%.20g vs %.20g) at (%d,%d)\n",

cvGetReal2D(&stub1, pt[0], pt[1]), cvGetReal2D(&_test_stub1, pt[0], pt[1]),

pt[0], pt[1] );

ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );

return;

}

if( m && CV_IS_MAT(m))

cvReleaseMat(&m);

CvMatND* m_nd = (CvMatND*)fs["test_mat_nd"].readObj();

CvMatND _test_mat_nd = test_mat_nd;

if( !m_nd || !CV_IS_MATND(m_nd) )

{

ts->printf( cvtest::TS::LOG, "the read nd-matrix is not correct\n" );

ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );

return;

}

CvMat stub, _test_stub;

cvGetMat(m_nd, &stub, 0, 1);

cvGetMat(&_test_mat_nd, &_test_stub, 0, 1);

cvReshape(&stub, &stub1, 1, 0);

cvReshape(&_test_stub, &_test_stub1, 1, 0);

if( !CV_ARE_TYPES_EQ(&stub, &_test_stub) ||

!CV_ARE_SIZES_EQ(&stub, &_test_stub) ||

//cvNorm(&stub, &_test_stub, CV_L2) != 0 )

cvtest::cmpEps( cv::cvarrToMat(&stub1), cv::cvarrToMat(&_test_stub1), &max_diff, 0, &pt, true) < 0 )

{

ts->printf( cvtest::TS::LOG, "readObj method: the read nd matrix is not correct: (%.20g vs %.20g) vs at (%d,%d)\n",

cvGetReal2D(&stub1, pt[0], pt[1]), cvGetReal2D(&_test_stub1, pt[0], pt[1]),

pt[0], pt[1] );

ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );

return;

}

MatND mat_nd2;

fs["test_mat_nd"] >> mat_nd2;

CvMatND m_nd2 = mat_nd2;

cvGetMat(&m_nd2, &stub, 0, 1);

cvReshape(&stub, &stub1, 1, 0);

if( !CV_ARE_TYPES_EQ(&stub, &_test_stub) ||

!CV_ARE_SIZES_EQ(&stub, &_test_stub) ||

//cvNorm(&stub, &_test_stub, CV_L2) != 0 )

cvtest::cmpEps( cv::cvarrToMat(&stub1), cv::cvarrToMat(&_test_stub1), &max_diff, 0, &pt, true) < 0 )

{

ts->printf( cvtest::TS::LOG, "C++ method: the read nd matrix is not correct: (%.20g vs %.20g) vs at (%d,%d)\n",

cvGetReal2D(&stub1, pt[0], pt[1]), cvGetReal2D(&_test_stub1, pt[1], pt[0]),

pt[0], pt[1] );

ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );

return;

}

cvRelease((void**)&m_nd);

Ptr<CvSparseMat> m_s((CvSparseMat*)fs["test_sparse_mat"].readObj());

Ptr<CvSparseMat> _test_sparse_(cvCreateSparseMat(test_sparse_mat));

Ptr<CvSparseMat> _test_sparse((CvSparseMat*)cvClone(_test_sparse_));

SparseMat m_s2;

fs["test_sparse_mat"] >> m_s2;

Ptr<CvSparseMat> _m_s2(cvCreateSparseMat(m_s2));

if( !m_s || !CV_IS_SPARSE_MAT(m_s) ||

!cvTsCheckSparse(m_s, _test_sparse, 0) ||

!cvTsCheckSparse(_m_s2, _test_sparse, 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 += 4;

real_lbp_val |= (int)*it2 << 7;

--it2;

real_lbp_val |= (int)*it2 << 6;

it2--;

real_lbp_val |= (int)*it2 << 5;

it2 -= 1;

real_lbp_val |= (int)*it2 << 4;

it2 += -1;

CV_Assert( it == it2 );

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;

}

CvGraph* graph3 = (CvGraph*)fs["test_graph"].readObj();

if(graph2->active_count != vcount || graph3->active_count != vcount ||

graph2->edges->active_count != ecount || graph3->edges->active_count != ecount)

{

ts->printf( cvtest::TS::LOG, "the cloned or read graph have wrong number of vertices or edges\n" );

ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );

return;

}

for( i = 0; i < ecount; i++ )

{

CvGraphEdge* edge2 = cvFindGraphEdge(graph2, edges[i][0], edges[i][1]);

CvGraphEdge* edge3 = cvFindGraphEdge(graph3, edges[i][0], edges[i][1]);

if( !edge2 || edge2->weight != (float)(i+1) ||

!edge3 || edge3->weight != (float)(i+1) )

{

ts->printf( cvtest::TS::LOG, "the cloned or read graph do not have the edge (%d, %d)\n", edges[i][0], edges[i][1] );

ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );

return;

}

}

fs.release();

if( !mem )

remove(filename.c_str());

}

}

{

int a;

float b;

const String&,

const UserDefinedType &value)

{

fs << "{:" << "a" << value.a << "b" << value.b << "}";

UserDefinedType& value,

const UserDefinedType& default_value

= UserDefinedType()) {

if(node.empty())

{

value = default_value;

}

else

{

node["a"] >> value.a;

node["b"] >> value.b;

}

{

CV_MiscIOTest() {}

~CV_MiscIOTest() {}

void run(int)

{

const char * suffix[3] = {

".yml",

".xml",

".json"

};

for ( size_t i = 0u; i < 3u; 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 );

}

catch(...)

{

ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);

}

}

}

{

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());

}

{

std::string file = cv::tempfile(".xml");

cv::FileStorage f(file, cv::FileStorage::WRITE);

char arr[66];

sprintf(arr, "sprintf is hell %d", 666);

EXPECT_NO_THROW(f << arr);

{

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());

{

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%d", 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%d", i)] >> valuesRead[i]);

ASSERT_STREQ(values[i].c_str(), valuesRead[i].c_str());

}

{

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;

/*

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";

}

{

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_basic_test.yml",

"core_io_base64_basic_test.xml",

"core_io_base64_basic_test.json",

0

};

for (char const ** ptr = filenames; *ptr; ptr++)

{

char const * suffix_name = *ptr;

std::string name = basename + '_' + suffix_name;

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(64, 64, CV_64FC1), _rd_in;

bool no_type_id = true;

{ /* init */

/* a 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 + 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 < 1000; 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);

}

}

{ /* write */

cv::FileStorage fs(name, cv::FileStorage::WRITE_BASE64);

fs << "normal_2d_mat" << _2d_out;

fs << "normal_nd_mat" << _nd_out;

fs << "empty_2d_mat" << _em_out;

fs << "random_mat" << _rd_out;

cvStartWriteStruct( *fs, "rawdata", CV_NODE_SEQ | CV_NODE_FLOW, "binary" );

for (int i = 0; i < 10; i++)

cvWriteRawDataBase64(*fs, rawdata.data() + i * 100, 100, data_t::signature());

cvEndWriteStruct( *fs );

fs.release();

}

{ /* read */

cv::FileStorage fs(name, cv::FileStorage::READ);

/* mat */

fs["empty_2d_mat"] >> _em_in;

fs["normal_2d_mat"] >> _2d_in;

fs["normal_nd_mat"] >> _nd_in;

fs["random_mat"] >> _rd_in;

if ( !fs["empty_2d_mat"]["type_id"].empty() ||

!fs["normal_2d_mat"]["type_id"].empty() ||

!fs["normal_nd_mat"]["type_id"].empty() ||

!fs[ "random_mat"]["type_id"].empty() )

no_type_id = false;

/* raw data */

std::vector<data_t>(1000).swap(rawdata);

cvReadRawData(*fs, fs["rawdata"].node, rawdata.data(), data_t::signature());

fs.release();

}

int errors = 0;

for (int i = 0; i < 1000; 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_TRUE(no_type_id);

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());

EXPECT_EQ(_2d_in.rows , _2d_out.rows);

EXPECT_EQ(_2d_in.cols , _2d_out.cols);

EXPECT_EQ(_2d_in.dims , _2d_out.dims);

EXPECT_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;

}

}

}

EXPECT_EQ(_nd_in.rows , _nd_out.rows);

EXPECT_EQ(_nd_in.cols , _nd_out.cols);

EXPECT_EQ(_nd_in.dims , _nd_out.dims);

EXPECT_EQ(_nd_in.depth(), _nd_out.depth());

EXPECT_EQ(cv::countNonZero(cv::mean(_nd_in != _nd_out)), 0);

EXPECT_EQ(_rd_in.rows , _rd_out.rows);

EXPECT_EQ(_rd_in.cols , _rd_out.cols);

EXPECT_EQ(_rd_in.dims , _rd_out.dims);

EXPECT_EQ(_rd_in.depth(), _rd_out.depth());

EXPECT_EQ(cv::countNonZero(cv::mean(_rd_in != _rd_out)), 0);

remove(name.c_str());

}

{

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",

"core_io_base64_other_test.yml?base64",

"core_io_base64_other_test.xml?base64",

"core_io_base64_other_test.json?base64",

0

};

char const * real_name[] = {

"core_io_base64_other_test.yml",

"core_io_base64_other_test.xml",

"core_io_base64_other_test.json",

"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 (char const ** ptr = filenames; *ptr; ptr++)

{

char const * suffix_name = *ptr;

std::string name = basename + '_' + suffix_name;

EXPECT_NO_THROW(

{

cv::FileStorage fs(name, cv::FileStorage::WRITE_BASE64);

cvStartWriteStruct(*fs, "manydata", CV_NODE_SEQ);

cvStartWriteStruct(*fs, 0, CV_NODE_SEQ | CV_NODE_FLOW);

for (int i = 0; i < 10; i++)

cvWriteRawData(*fs, rawdata.data(), static_cast<int>(rawdata.size()), "i");

cvEndWriteStruct(*fs);

cvWriteString(*fs, 0, str_out.c_str(), 1);

cvEndWriteStruct(*fs);

fs.release();

});

{

cv::FileStorage fs(name, cv::FileStorage::READ);

std::vector<int> data_in(rawdata.size());

fs["manydata"][0].readRaw("i", (uchar *)data_in.data(), data_in.size());

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(name, cv::FileStorage::WRITE);

cvStartWriteStruct(*fs, "manydata", CV_NODE_SEQ);

cvWriteString(*fs, 0, str_out.c_str(), 1);

cvStartWriteStruct(*fs, 0, CV_NODE_SEQ | CV_NODE_FLOW, "binary");

for (int i = 0; i < 10; i++)

cvWriteRawData(*fs, rawdata.data(), static_cast<int>(rawdata.size()), "i");

cvEndWriteStruct(*fs);

cvEndWriteStruct(*fs);

fs.release();

});

{

cv::FileStorage fs(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());

EXPECT_TRUE(fs["manydata"][1].isSeq());

EXPECT_TRUE(std::equal(rawdata.begin(), rawdata.end(), data_in.begin()));

fs.release();

}

remove((basename + '_' + real_name[ptr - filenames]).c_str());

}

{

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 (char const ** ptr = filenames; *ptr; ptr++)

{

char const * suffix_name = *ptr;

std::string name = basename + '_' + suffix_name;

EXPECT_ANY_THROW({

cv::FileStorage fs(name, cv::FileStorage::WRITE);

cvStartWriteStruct(*fs, "rawdata", CV_NODE_SEQ, "binary");

cvStartWriteStruct(*fs, 0, CV_NODE_SEQ | CV_NODE_FLOW);

});

EXPECT_ANY_THROW({

cv::FileStorage fs(name, cv::FileStorage::WRITE);

cvStartWriteStruct(*fs, "rawdata", CV_NODE_SEQ);

cvStartWriteStruct(*fs, 0, CV_NODE_SEQ | CV_NODE_FLOW);

cvWriteRawDataBase64(*fs, name.c_str(), 1, "u");

});

remove(name.c_str());

}

{

const std::string file_name = "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());

{

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"));