This source file includes following definitions.
- PARAM_TEST_CASE
- OCL_TEST_P
- OCL_TEST_P
- PARAM_TEST_CASE
- OCL_TEST_P
#include "../test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
struct Vec2fComparator
{
bool operator()(const Vec2f& a, const Vec2f b) const
{
if(a[0] != b[0]) return a[0] < b[0];
else return a[1] < b[1];
}
};
PARAM_TEST_CASE(HoughLines, double, double, int)
{
double rhoStep, thetaStep;
int threshold;
Size src_size;
Mat src, dst;
UMat usrc, udst;
virtual void SetUp()
{
rhoStep = GET_PARAM(0);
thetaStep = GET_PARAM(1);
threshold = GET_PARAM(2);
}
virtual void generateTestData()
{
src_size = randomSize(500, 1920);
src.create(src_size, CV_8UC1);
src.setTo(Scalar::all(0));
line(src, Point(0, 100), Point(100, 100), Scalar::all(255), 1);
line(src, Point(0, 200), Point(100, 200), Scalar::all(255), 1);
line(src, Point(0, 400), Point(100, 400), Scalar::all(255), 1);
line(src, Point(100, 0), Point(100, 200), Scalar::all(255), 1);
line(src, Point(200, 0), Point(200, 200), Scalar::all(255), 1);
line(src, Point(400, 0), Point(400, 200), Scalar::all(255), 1);
src.copyTo(usrc);
}
virtual void readRealTestData()
{
Mat img = readImage("shared/pic5.png", IMREAD_GRAYSCALE);
Canny(img, src, 100, 150, 3);
src.copyTo(usrc);
}
virtual void Near(double eps = 0.)
{
EXPECT_EQ(dst.size(), udst.size());
if (dst.total() > 0)
{
Mat lines_cpu, lines_gpu;
dst.copyTo(lines_cpu);
udst.copyTo(lines_gpu);
std::sort(lines_cpu.begin<Vec2f>(), lines_cpu.end<Vec2f>(), Vec2fComparator());
std::sort(lines_gpu.begin<Vec2f>(), lines_gpu.end<Vec2f>(), Vec2fComparator());
EXPECT_LE(TestUtils::checkNorm2(lines_cpu, lines_gpu), eps);
}
}
};
OCL_TEST_P(HoughLines, RealImage)
{
readRealTestData();
OCL_OFF(cv::HoughLines(src, dst, rhoStep, thetaStep, threshold));
OCL_ON(cv::HoughLines(usrc, udst, rhoStep, thetaStep, threshold));
Near(1e-5);
}
OCL_TEST_P(HoughLines, GeneratedImage)
{
for (int j = 0; j < test_loop_times; j++)
{
generateTestData();
OCL_OFF(cv::HoughLines(src, dst, rhoStep, thetaStep, threshold));
OCL_ON(cv::HoughLines(usrc, udst, rhoStep, thetaStep, threshold));
Near(1e-5);
}
}
PARAM_TEST_CASE(HoughLinesP, int, double, double)
{
double rhoStep, thetaStep, minLineLength, maxGap;
int threshold;
Size src_size;
Mat src, dst;
UMat usrc, udst;
virtual void SetUp()
{
rhoStep = 1.0;
thetaStep = CV_PI / 180;
threshold = GET_PARAM(0);
minLineLength = GET_PARAM(1);
maxGap = GET_PARAM(2);
}
virtual void readRealTestData()
{
Mat img = readImage("shared/pic5.png", IMREAD_GRAYSCALE);
Canny(img, src, 50, 200, 3);
src.copyTo(usrc);
}
virtual void Near(double eps = 0.)
{
Mat lines_gpu = udst.getMat(ACCESS_READ);
if (dst.total() > 0 && lines_gpu.total() > 0)
{
Mat result_cpu(src.size(), CV_8UC1, Scalar::all(0));
Mat result_gpu(src.size(), CV_8UC1, Scalar::all(0));
MatConstIterator_<Vec4i> it = dst.begin<Vec4i>(), end = dst.end<Vec4i>();
for ( ; it != end; it++)
{
Vec4i p = *it;
line(result_cpu, Point(p[0], p[1]), Point(p[2], p[3]), Scalar(255));
}
it = lines_gpu.begin<Vec4i>(), end = lines_gpu.end<Vec4i>();
for ( ; it != end; it++)
{
Vec4i p = *it;
line(result_gpu, Point(p[0], p[1]), Point(p[2], p[3]), Scalar(255));
}
EXPECT_MAT_SIMILAR(result_cpu, result_gpu, eps);
}
}
};
OCL_TEST_P(HoughLinesP, RealImage)
{
readRealTestData();
OCL_OFF(cv::HoughLinesP(src, dst, rhoStep, thetaStep, threshold, minLineLength, maxGap));
OCL_ON(cv::HoughLinesP(usrc, udst, rhoStep, thetaStep, threshold, minLineLength, maxGap));
Near(0.25);
}
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, HoughLines, Combine(Values(1, 0.5),
Values(CV_PI / 180.0, CV_PI / 360.0),
Values(80, 150)));
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, HoughLinesP, Combine(Values(100, 150),
Values(50, 100),
Values(5, 10)));
} }