This source file includes following definitions.
- get_test_array_types_and_sizes
- get_success_error_level
- run_func
- prepare_to_validation
- run_func
- prepare_to_validation
- run_func
- prepare_to_validation
- run_func
- prepare_to_validation
- TEST
- TEST
- TEST
- TEST
#include "test_precomp.hpp"
#include "opencv2/imgproc/imgproc_c.h"
using namespace cv;
using namespace std;
class CV_AccumBaseTest : public cvtest::ArrayTest
{
public:
CV_AccumBaseTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
double get_success_error_level( int test_case_idx, int i, int j );
double alpha;
};
CV_AccumBaseTest::CV_AccumBaseTest()
{
test_array[INPUT].push_back(NULL);
test_array[INPUT_OUTPUT].push_back(NULL);
test_array[REF_INPUT_OUTPUT].push_back(NULL);
test_array[MASK].push_back(NULL);
optional_mask = true;
element_wise_relative_error = false;
}
void CV_AccumBaseTest::get_test_array_types_and_sizes( int test_case_idx,
vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
int depth = cvtest::randInt(rng) % 3, cn = cvtest::randInt(rng) & 1 ? 3 : 1;
int accdepth = std::max((int)(cvtest::randInt(rng) % 2 + 1), depth);
int i, input_count = (int)test_array[INPUT].size();
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
depth = depth == 0 ? CV_8U : depth == 1 ? CV_32F : CV_64F;
accdepth = accdepth == 1 ? CV_32F : CV_64F;
accdepth = MAX(accdepth, depth);
for( i = 0; i < input_count; i++ )
types[INPUT][i] = CV_MAKETYPE(depth,cn);
types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(accdepth,cn);
alpha = cvtest::randReal(rng);
}
double CV_AccumBaseTest::get_success_error_level( int , int , int )
{
return test_mat[INPUT_OUTPUT][0].depth() < CV_64F ||
test_mat[INPUT][0].depth() == CV_32F ? FLT_EPSILON*100 : DBL_EPSILON*1000;
}
class CV_AccTest : public CV_AccumBaseTest
{
public:
CV_AccTest() { }
protected:
void run_func();
void prepare_to_validation( int );
};
void CV_AccTest::run_func(void)
{
cvAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
void CV_AccTest::prepare_to_validation( int )
{
const Mat& src = test_mat[INPUT][0];
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
Mat temp;
cvtest::add( src, 1, dst, 1, cvScalarAll(0.), temp, dst.type() );
cvtest::copy( temp, dst, mask );
}
class CV_SquareAccTest : public CV_AccumBaseTest
{
public:
CV_SquareAccTest();
protected:
void run_func();
void prepare_to_validation( int );
};
CV_SquareAccTest::CV_SquareAccTest()
{
}
void CV_SquareAccTest::run_func()
{
cvSquareAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
void CV_SquareAccTest::prepare_to_validation( int )
{
const Mat& src = test_mat[INPUT][0];
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
Mat temp;
cvtest::convert( src, temp, dst.type() );
cvtest::multiply( temp, temp, temp, 1 );
cvtest::add( temp, 1, dst, 1, cvScalarAll(0.), temp, dst.depth() );
cvtest::copy( temp, dst, mask );
}
class CV_MultiplyAccTest : public CV_AccumBaseTest
{
public:
CV_MultiplyAccTest();
protected:
void run_func();
void prepare_to_validation( int );
};
CV_MultiplyAccTest::CV_MultiplyAccTest()
{
test_array[INPUT].push_back(NULL);
}
void CV_MultiplyAccTest::run_func()
{
cvMultiplyAcc( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
void CV_MultiplyAccTest::prepare_to_validation( int )
{
const Mat& src1 = test_mat[INPUT][0];
const Mat& src2 = test_mat[INPUT][1];
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
Mat temp1, temp2;
cvtest::convert( src1, temp1, dst.type() );
cvtest::convert( src2, temp2, dst.type() );
cvtest::multiply( temp1, temp2, temp1, 1 );
cvtest::add( temp1, 1, dst, 1, cvScalarAll(0.), temp1, dst.depth() );
cvtest::copy( temp1, dst, mask );
}
class CV_RunningAvgTest : public CV_AccumBaseTest
{
public:
CV_RunningAvgTest();
protected:
void run_func();
void prepare_to_validation( int );
};
CV_RunningAvgTest::CV_RunningAvgTest()
{
}
void CV_RunningAvgTest::run_func()
{
cvRunningAvg( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
alpha, test_array[MASK][0] );
}
void CV_RunningAvgTest::prepare_to_validation( int )
{
const Mat& src = test_mat[INPUT][0];
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
Mat temp;
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
double a[1], b[1];
int accdepth = test_mat[INPUT_OUTPUT][0].depth();
CvMat A = cvMat(1,1,accdepth,a), B = cvMat(1,1,accdepth,b);
cvSetReal1D( &A, 0, alpha);
cvSetReal1D( &B, 0, 1 - cvGetReal1D(&A, 0));
cvtest::convert( src, temp, dst.type() );
cvtest::add( src, cvGetReal1D(&A, 0), dst, cvGetReal1D(&B, 0), cvScalarAll(0.), temp, temp.depth() );
cvtest::copy( temp, dst, mask );
}
TEST(Video_Acc, accuracy) { CV_AccTest test; test.safe_run(); }
TEST(Video_AccSquared, accuracy) { CV_SquareAccTest test; test.safe_run(); }
TEST(Video_AccProduct, accuracy) { CV_MultiplyAccTest test; test.safe_run(); }
TEST(Video_RunningAvg, accuracy) { CV_RunningAvgTest test; test.safe_run(); }