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