Open Source Computer Vision Library https://opencv.org/
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#include "test_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;
PARAM_TEST_CASE(MomentsTest, MatType, bool, bool)
{
int type;
cv::Mat mat;
bool test_contours;
bool binaryImage;
virtual void SetUp()
{
type = GET_PARAM(0);
test_contours = GET_PARAM(1);
cv::Size size(10 * MWIDTH, 10 * MHEIGHT);
mat = randomMat(size, type, 0, 256, false);
binaryImage = GET_PARAM(2);
}
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, 1e-3);
}
};
OCL_TEST_P(MomentsTest, Mat)
{
oclMat src_d(mat);
for(int j = 0; j < LOOP_TIMES; j++)
{
if(test_contours)
{
Mat src = readImage( "cv/shared/pic3.png", IMREAD_GRAYSCALE );
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ASSERT_FALSE(src.empty());
Mat canny_output;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
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Canny( src, 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]);
Compare(m, dm);
}
}
cv::Moments CvMom = cv::moments(mat, binaryImage);
cv::Moments oclMom = cv::ocl::ocl_moments(src_d, binaryImage);
Compare(CvMom, oclMom);
}
}
INSTANTIATE_TEST_CASE_P(OCL_ImgProc, MomentsTest, Combine(
Values(CV_8UC1, CV_16UC1, CV_16SC1, CV_32FC1, CV_64FC1), Values(false, true), Values(false, true)));
#endif // HAVE_OPENCL