opencv/tests/gpu/src/mssegmentation.cpp

108 lines
4.3 KiB
C++

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#include <iostream>
#include <string>
#include <iosfwd>
#include "gputest.hpp"
using namespace cv;
using namespace cv::gpu;
using namespace std;
struct CV_GpuMeanShiftSegmentationTest : public CvTest {
CV_GpuMeanShiftSegmentationTest() : CvTest( "GPU-MeanShiftSegmentation", "MeanShiftSegmentation" ) {}
void run(int)
{
try
{
Mat img_rgb = imread(string(ts->get_data_path()) + "meanshift/cones.png");
if (img_rgb.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
Mat img;
cvtColor(img_rgb, img, CV_BGR2BGRA);
int major, minor;
cv::gpu::getComputeCapability(cv::gpu::getDevice(), major, minor);
for (int minsize = 0; minsize < 2000; minsize = (minsize + 1) * 4)
{
stringstream path;
path << ts->get_data_path() << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
if (TargetArchs::hasEqualOrGreater(2, 0) && major >= 2)
path << ".png";
else
path << "_CC1X.png";
Mat dst;
meanShiftSegmentation((GpuMat)img, dst, 10, 10, minsize);
Mat dst_rgb;
cvtColor(dst, dst_rgb, CV_BGRA2BGR);
//imwrite(path.str(), dst_rgb);
Mat dst_ref = imread(path.str());
if (dst_ref.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
if (abs(cv::norm(dst_rgb - dst_ref, NORM_INF)) > 1e-3)
{
ts->printf(CvTS::LOG, "\ndiffers from image *minsize%d.png\n", minsize);
ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);
return;
}
}
}
catch (const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(CvTS::OK);
}
} ms_segm_test;