void CV_MinMaxHistTest::init_hist(int test_case_idx, int hist_i)
{
int i, eq = 1;
CvRNG* rng = ts->get_rng();
CV_BaseHistTest::init_hist( test_case_idx, hist_i );
for(;;)
{
for( i = 0; i < cdims; i++ )
{
min_idx0[i] = cvTsRandInt(rng) % dims[i];
max_idx0[i] = cvTsRandInt(rng) % dims[i];
eq &= min_idx0[i] == max_idx0[i];
}
if( !eq || total_size == 1 )
break;
}
min_val0 = (float)(-cvTsRandReal(rng)*10 - FLT_EPSILON);
max_val0 = (float)(cvTsRandReal(rng)*10 + FLT_EPSILON + gen_hist_max_val);
if( total_size == 1 )
min_val0 = max_val0;
cvSetRealND( hist[0]->bins, min_idx0, min_val0 );
cvSetRealND( hist[0]->bins, max_idx0, max_val0 );
}
void CV_MHIBaseTest::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
types[INPUT][0] = CV_8UC1;
types[mhi_i][0] = types[mhi_ref_i][0] = CV_32FC1;
duration = exp(cvTsRandReal(rng)*max_log_duration);
timestamp = duration + cvTsRandReal(rng)*30.-10.;
}
void CV_MHIGradientTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
CV_MHIBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32FC1;
delta1 = exp(cvTsRandReal(rng)*delta_range_log + 1.);
delta2 = exp(cvTsRandReal(rng)*delta_range_log + 1.);
aperture_size = (cvTsRandInt(rng)%3)*2+3;
//duration = exp(cvTsRandReal(rng)*max_log_duration);
//timestamp = duration + cvTsRandReal(rng)*30.-10.;
}
void CV_BaseHistTest::init_hist( int /*test_case_idx*/, int hist_i )
{
if( gen_random_hist )
{
CvRNG* rng = ts->get_rng();
CvArr* h = hist[hist_i]->bins;
if( hist_type == CV_HIST_ARRAY )
{
cvRandArr( rng, h, CV_RAND_UNI,
cvScalarAll(0), cvScalarAll(gen_hist_max_val) );
}
else
{
int i, j, total_size = 1, nz_count;
int idx[CV_MAX_DIM];
for( i = 0; i < cdims; i++ )
total_size *= dims[i];
nz_count = cvTsRandInt(rng) % MAX( total_size/4, 100 );
nz_count = MIN( nz_count, total_size );
// a zero number of non-zero elements should be allowed
for( i = 0; i < nz_count; i++ )
{
for( j = 0; j < cdims; j++ )
idx[j] = cvTsRandInt(rng) % dims[j];
cvSetRealND( h, idx, cvTsRandReal(rng)*gen_hist_max_val );
}
}
}
}
void CV_BaseHistTest::get_hist_params( int /*test_case_idx*/ )
{
CvRNG* rng = ts->get_rng();
int i, max_dim_size, max_ni_dim_size = 31;
double hist_size;
cdims = cvTsRandInt(rng) % max_cdims + 1;
hist_size = exp(cvTsRandReal(rng)*max_log_size*CV_LOG2);
max_dim_size = cvRound(pow(hist_size,1./cdims));
total_size = 1;
uniform = cvTsRandInt(rng) % 2;
hist_type = cvTsRandInt(rng) % 2 ? CV_HIST_SPARSE : CV_HIST_ARRAY;
for( i = 0; i < cdims; i++ )
{
dims[i] = cvTsRandInt(rng) % (max_dim_size + 2) + 2;
if( !uniform )
dims[i] = MIN(dims[i], max_ni_dim_size);
total_size *= dims[i];
}
img_type = cvTsRandInt(rng) % 2 ? CV_32F : CV_8U;
img_size.width = cvRound( exp(cvRandReal(rng) * img_max_log_size*CV_LOG2) );
img_size.height = cvRound( exp(cvRandReal(rng) * img_max_log_size*CV_LOG2) );
low = cvTsMinVal(img_type);
high = cvTsMaxVal(img_type);
range_delta = (cvTsRandInt(rng) % 2)*(high-low)*0.05;
}
int CV_CalcBackProjectTest::prepare_test_case( int test_case_idx )
{
int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
CvRNG* rng = ts->get_rng();
int i, j, n, img_len = img_size.width*img_size.height;
for( i = 0; i < CV_MAX_DIM + 3; i++ )
{
if( i < cdims )
{
int nch = 1; //cvTsRandInt(rng) % 3 + 1;
images[i] = cvCreateImage( img_size,
img_type == CV_8U ? IPL_DEPTH_8U : IPL_DEPTH_32F, nch );
channels[i] = cvTsRandInt(rng) % nch;
cvRandArr( rng, images[i], CV_RAND_UNI,
cvScalarAll(low), cvScalarAll(high) );
}
else if( i == CV_MAX_DIM && cvTsRandInt(rng) % 2 )
{
// create mask
images[i] = cvCreateImage( img_size, IPL_DEPTH_8U, 1 );
// make ~25% pixels in the mask non-zero
cvRandArr( rng, images[i], CV_RAND_UNI,
cvScalarAll(-2), cvScalarAll(2) );
}
else if( i > CV_MAX_DIM )
{
images[i] = cvCreateImage( img_size, images[0]->depth, 1 );
}
}
cvTsCalcHist( images, hist[0], images[CV_MAX_DIM], channels );
// now modify the images a bit to add some zeros go to the backprojection
n = cvTsRandInt(rng) % (img_len/20+1);
for( i = 0; i < cdims; i++ )
{
char* data = images[i]->imageData;
for( j = 0; j < n; j++ )
{
int idx = cvTsRandInt(rng) % img_len;
double val = cvTsRandReal(rng)*(high - low) + low;
if( img_type == CV_8U )
((uchar*)data)[idx] = (uchar)cvRound(val);
else
((float*)data)[idx] = (float)val;
}
}
}
return code;
}
void CV_CannyTest::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
double thresh_range;
CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8U;
aperture_size = cvTsRandInt(rng) % 2 ? 5 : 3;
thresh_range = aperture_size == 3 ? 300 : 1000;
threshold1 = cvTsRandReal(rng)*thresh_range;
threshold2 = cvTsRandReal(rng)*thresh_range*0.3;
if( cvTsRandInt(rng) % 2 )
CV_SWAP( threshold1, threshold2, thresh_range );
use_true_gradient = cvTsRandInt(rng) % 2;
}
void CV_ThreshTest::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
int depth = cvTsRandInt(rng) % 2, cn = cvTsRandInt(rng) % 4 + 1;
CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
depth = depth == 0 ? CV_8U : CV_32F;
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn);
thresh_type = cvTsRandInt(rng) % 5;
if( depth == CV_8U )
{
thresh_val = (float)(cvTsRandReal(rng)*350. - 50.);
max_val = (float)(cvTsRandReal(rng)*350. - 50.);
if( cvTsRandInt(rng)%4 == 0 )
max_val = 255;
}
else
{
thresh_val = (float)(cvTsRandReal(rng)*1000. - 500.);
max_val = (float)(cvTsRandReal(rng)*1000. - 500.);
}
}
void CV_MHIGlobalOrientTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
CV_MHIBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
CvSize size = sizes[INPUT][0];
size.width = MAX( size.width, 8 );
size.height = MAX( size.height, 8 );
sizes[INPUT][0] = sizes[INPUT][1] = sizes[INPUT][2] = size;
types[INPUT][1] = CV_8UC1; // mask
types[INPUT][2] = CV_32FC1; // orientation
min_angle = cvTsRandReal(rng)*359.9;
max_angle = cvTsRandReal(rng)*359.9;
if( min_angle >= max_angle )
{
double t;
CV_SWAP( min_angle, max_angle, t );
}
max_angle += 0.1;
duration = exp(cvTsRandReal(rng)*max_log_duration);
timestamp = duration + cvTsRandReal(rng)*30.-10.;
}
int CV_NormHistTest::prepare_test_case( int test_case_idx )
{
int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
CvRNG* rng = ts->get_rng();
factor = cvTsRandReal(rng)*10 + 0.1;
if( hist_type == CV_HIST_SPARSE &&
((CvSparseMat*)hist[0]->bins)->heap->active_count == 0 )
factor = 0;
}
return code;
}
int CV_ThreshHistTest::prepare_test_case( int test_case_idx )
{
int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
CvRNG* rng = ts->get_rng();
threshold = cvTsRandReal(rng)*gen_hist_max_val;
if( hist_type == CV_HIST_ARRAY )
{
orig_nz_count = total_size;
values = cvCreateMat( 1, total_size, CV_32F );
memcpy( values->data.fl, cvPtr1D( hist[0]->bins, 0 ), total_size*sizeof(float) );
}
else
{
CvSparseMat* sparse = (CvSparseMat*)hist[0]->bins;
CvSparseMatIterator iterator;
CvSparseNode* node;
int i, k;
orig_nz_count = sparse->heap->active_count;
values = cvCreateMat( 1, orig_nz_count+1, CV_32F );
indices = cvCreateMat( 1, (orig_nz_count+1)*cdims, CV_32S );
for( node = cvInitSparseMatIterator( sparse, &iterator ), i = 0;
node != 0; node = cvGetNextSparseNode( &iterator ), i++ )
{
const int* idx = CV_NODE_IDX(sparse,node);
OPENCV_ASSERT( i < orig_nz_count, "CV_ThreshHistTest::prepare_test_case", "Buffer overflow" );
values->data.fl[i] = *(float*)CV_NODE_VAL(sparse,node);
for( k = 0; k < cdims; k++ )
indices->data.i[i*cdims + k] = idx[k];
}
OPENCV_ASSERT( i == orig_nz_count, "Unmatched buffer size",
"CV_ThreshHistTest::prepare_test_case" );
}
}
return code;
}
void CV_POSITTest::run( int start_from )
{
int code = CvTS::OK;
/* fixed parameters output */
/*float rot[3][3]={ 0.49010f, 0.85057f, 0.19063f,
-0.56948f, 0.14671f, 0.80880f,
0.65997f, -0.50495f, 0.55629f };
float trans[3] = { 0.0f, 0.0f, 40.02637f };
*/
/* Some variables */
int i, counter;
CvTermCriteria criteria;
CvPoint3D32f* obj_points;
CvPoint2D32f* img_points;
CvPOSITObject* object;
float angleX, angleY, angleZ;
CvRNG* rng = ts->get_rng();
int progress = 0;
CvMat* true_rotationX = cvCreateMat( 3, 3, CV_32F );
CvMat* true_rotationY = cvCreateMat( 3, 3, CV_32F );
CvMat* true_rotationZ = cvCreateMat( 3, 3, CV_32F );
CvMat* tmp_matrix = cvCreateMat( 3, 3, CV_32F );
CvMat* true_rotation = cvCreateMat( 3, 3, CV_32F );
CvMat* rotation = cvCreateMat( 3, 3, CV_32F );
CvMat* translation = cvCreateMat( 3, 1, CV_32F );
CvMat* true_translation = cvCreateMat( 3, 1, CV_32F );
const float flFocalLength = 760.f;
const float flEpsilon = 0.1f;
/* Initilization */
criteria.type = CV_TERMCRIT_EPS|CV_TERMCRIT_ITER;
criteria.epsilon = flEpsilon;
criteria.max_iter = 10000;
/* Allocating source arrays; */
obj_points = (CvPoint3D32f*)cvAlloc( 8 * sizeof(CvPoint3D32f) );
img_points = (CvPoint2D32f*)cvAlloc( 8 * sizeof(CvPoint2D32f) );
/* Fill points arrays with values */
/* cube model with edge size 10 */
obj_points[0].x = 0; obj_points[0].y = 0; obj_points[0].z = 0;
obj_points[1].x = 10; obj_points[1].y = 0; obj_points[1].z = 0;
obj_points[2].x = 10; obj_points[2].y = 10; obj_points[2].z = 0;
obj_points[3].x = 0; obj_points[3].y = 10; obj_points[3].z = 0;
obj_points[4].x = 0; obj_points[4].y = 0; obj_points[4].z = 10;
obj_points[5].x = 10; obj_points[5].y = 0; obj_points[5].z = 10;
obj_points[6].x = 10; obj_points[6].y = 10; obj_points[6].z = 10;
obj_points[7].x = 0; obj_points[7].y = 10; obj_points[7].z = 10;
/* Loop for test some random object positions */
for( counter = start_from; counter < test_case_count; counter++ )
{
ts->update_context( this, counter, true );
progress = update_progress( progress, counter, test_case_count, 0 );
/* set all rotation matrix to zero */
cvZero( true_rotationX );
cvZero( true_rotationY );
cvZero( true_rotationZ );
/* fill random rotation matrix */
angleX = (float)(cvTsRandReal(rng)*2*CV_PI);
angleY = (float)(cvTsRandReal(rng)*2*CV_PI);
angleZ = (float)(cvTsRandReal(rng)*2*CV_PI);
true_rotationX->data.fl[0 *3+ 0] = 1;
true_rotationX->data.fl[1 *3+ 1] = (float)cos(angleX);
true_rotationX->data.fl[2 *3+ 2] = true_rotationX->data.fl[1 *3+ 1];
true_rotationX->data.fl[1 *3+ 2] = -(float)sin(angleX);
true_rotationX->data.fl[2 *3+ 1] = -true_rotationX->data.fl[1 *3+ 2];
true_rotationY->data.fl[1 *3+ 1] = 1;
true_rotationY->data.fl[0 *3+ 0] = (float)cos(angleY);
true_rotationY->data.fl[2 *3+ 2] = true_rotationY->data.fl[0 *3+ 0];
true_rotationY->data.fl[0 *3+ 2] = -(float)sin(angleY);
true_rotationY->data.fl[2 *3+ 0] = -true_rotationY->data.fl[0 *3+ 2];
true_rotationZ->data.fl[2 *3+ 2] = 1;
true_rotationZ->data.fl[0 *3+ 0] = (float)cos(angleZ);
true_rotationZ->data.fl[1 *3+ 1] = true_rotationZ->data.fl[0 *3+ 0];
true_rotationZ->data.fl[0 *3+ 1] = -(float)sin(angleZ);
true_rotationZ->data.fl[1 *3+ 0] = -true_rotationZ->data.fl[0 *3+ 1];
cvMatMul( true_rotationX, true_rotationY, tmp_matrix);
cvMatMul( tmp_matrix, true_rotationZ, true_rotation);
/* fill translation vector */
true_translation->data.fl[2] = (float)(cvRandReal(rng)*(2*flFocalLength-40) + 40);
true_translation->data.fl[0] = (float)((cvRandReal(rng)*2-1)*true_translation->data.fl[2]);
true_translation->data.fl[1] = (float)((cvRandReal(rng)*2-1)*true_translation->data.fl[2]);
/* calculate perspective projection */
for ( i = 0; i < 8; i++ )
{
float vec[3];
CvMat Vec = cvMat( 3, 1, CV_MAT32F, vec );
CvMat Obj_point = cvMat( 3, 1, CV_MAT32F, &obj_points[i].x );
cvMatMul( true_rotation, &Obj_point, &Vec );
vec[0] += true_translation->data.fl[0];
vec[1] += true_translation->data.fl[1];
vec[2] += true_translation->data.fl[2];
img_points[i].x = flFocalLength * vec[0] / vec[2];
img_points[i].y = flFocalLength * vec[1] / vec[2];
}
/*img_points[0].x = 0 ; img_points[0].y = 0;
img_points[1].x = 80; img_points[1].y = -93;
img_points[2].x = 245;img_points[2].y = -77;
img_points[3].x = 185;img_points[3].y = 32;
img_points[4].x = 32; img_points[4].y = 135;
img_points[5].x = 99; img_points[5].y = 35;
img_points[6].x = 247; img_points[6].y = 62;
img_points[7].x = 195; img_points[7].y = 179;
*/
object = cvCreatePOSITObject( obj_points, 8 );
cvPOSIT( object, img_points, flFocalLength, criteria,
rotation->data.fl, translation->data.fl );
cvReleasePOSITObject( &object );
code = cvTsCmpEps2( ts, rotation, true_rotation, flEpsilon, false, "rotation matrix" );
if( code < 0 )
goto _exit_;
code = cvTsCmpEps2( ts, translation, true_translation, flEpsilon, false, "translation vector" );
if( code < 0 )
goto _exit_;
}
_exit_:
cvFree( &obj_points );
cvFree( &img_points );
cvReleaseMat( &true_rotationX );
cvReleaseMat( &true_rotationY );
cvReleaseMat( &true_rotationZ );
cvReleaseMat( &tmp_matrix );
cvReleaseMat( &true_rotation );
cvReleaseMat( &rotation );
cvReleaseMat( &translation );
cvReleaseMat( &true_translation );
if( code < 0 )
ts->set_failed_test_info( code );
}
int CV_CalcBackProjectPatchTest::prepare_test_case( int test_case_idx )
{
int code = CV_BaseHistTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
CvRNG* rng = ts->get_rng();
int i, j, n, img_len = img_size.width*img_size.height;
patch_size.width = cvTsRandInt(rng) % img_size.width + 1;
patch_size.height = cvTsRandInt(rng) % img_size.height + 1;
patch_size.width = MIN( patch_size.width, 30 );
patch_size.height = MIN( patch_size.height, 30 );
factor = 1.;
method = cvTsRandInt(rng) % CV_CompareHistTest::MAX_METHOD;
for( i = 0; i < CV_MAX_DIM + 2; i++ )
{
if( i < cdims )
{
int nch = 1; //cvTsRandInt(rng) % 3 + 1;
images[i] = cvCreateImage( img_size,
img_type == CV_8U ? IPL_DEPTH_8U : IPL_DEPTH_32F, nch );
channels[i] = cvTsRandInt(rng) % nch;
cvRandArr( rng, images[i], CV_RAND_UNI,
cvScalarAll(low), cvScalarAll(high) );
}
else if( i >= CV_MAX_DIM )
{
images[i] = cvCreateImage(
cvSize(img_size.width - patch_size.width + 1,
img_size.height - patch_size.height + 1),
IPL_DEPTH_32F, 1 );
}
}
cvTsCalcHist( images, hist[0], 0, channels );
cvNormalizeHist( hist[0], factor );
// now modify the images a bit
n = cvTsRandInt(rng) % (img_len/10+1);
for( i = 0; i < cdims; i++ )
{
char* data = images[i]->imageData;
for( j = 0; j < n; j++ )
{
int idx = cvTsRandInt(rng) % img_len;
double val = cvTsRandReal(rng)*(high - low) + low;
if( img_type == CV_8U )
((uchar*)data)[idx] = (uchar)cvRound(val);
else
((float*)data)[idx] = (float)val;
}
}
}
return code;
}
