Open Source Computer Vision Library https://opencv.org/
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#include "precomp.hpp"
#include <iomanip>
#include "opencv2/imgproc/imgproc_c.h"
#ifdef HAVE_OPENCL
using namespace cv;
using namespace cv::ocl;
using namespace cvtest;
using namespace testing;
using namespace std;
extern string workdir;
PARAM_TEST_CASE(MomentsTestBase, MatType, bool)
{
int type;
cv::Mat mat1;
bool test_contours;
virtual void SetUp()
{
type = GET_PARAM(0);
test_contours = GET_PARAM(1);
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size size(10*MWIDTH, 10*MHEIGHT);
mat1 = randomMat(rng, size, type, 5, 16, false);
}
void Compare(Moments& cpu, Moments& gpu)
{
Mat gpu_dst, cpu_dst;
HuMoments(cpu, cpu_dst);
HuMoments(gpu, gpu_dst);
EXPECT_MAT_NEAR(gpu_dst,cpu_dst, .5, "");
}
};
struct ocl_Moments : MomentsTestBase {};
TEST_P(ocl_Moments, Mat)
{
bool binaryImage = 0;
SetUp();
for(int j = 0; j < LOOP_TIMES; j++)
{
if(test_contours)
{
Mat src = imread( workdir + "../cpp/pic3.png", 1 );
Mat src_gray, canny_output;
cvtColor( src, src_gray, CV_BGR2GRAY );
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
Canny( src_gray, canny_output, 100, 200, 3 );
findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
for( size_t i = 0; i < contours.size(); i++ )
{
Moments m = moments( contours[i], false );
Moments dm = ocl::ocl_moments( contours[i], false );
Compare(m, dm);
}
}
cv::_InputArray _array(mat1);
cv::Moments CvMom = cv::moments(_array, binaryImage);
cv::Moments oclMom = cv::ocl::ocl_moments(_array, binaryImage);
Compare(CvMom, oclMom);
}
}
INSTANTIATE_TEST_CASE_P(Moments, ocl_Moments, Combine(
Values(CV_8UC1, CV_16UC1, CV_16SC1, CV_64FC1), Values(true,false)));
#endif // HAVE_OPENCL