implemented mean shift segmentation with elimination of small segments, added tests
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103
tests/gpu/src/mssegmentation.cpp
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103
tests/gpu/src/mssegmentation.cpp
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//M*/
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#include <opencv2/opencv.hpp>
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#include <opencv2/gpu/gpu.hpp>
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#include <iostream>
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#include <string>
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#include <iosfwd>
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#include "gputest.hpp"
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using namespace cv;
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using namespace cv::gpu;
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using namespace std;
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struct CV_GpuMeanShiftSegmentationTest : public CvTest {
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CV_GpuMeanShiftSegmentationTest() : CvTest( "GPU-MeanShiftSegmentation", "MeanShiftSegmentation" ) {}
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void run(int)
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{
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try
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{
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Mat img_rgb = imread(string(ts->get_data_path()) + "meanshift/cones.png");
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if (img_rgb.empty())
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{
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ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
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return;
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}
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Mat img;
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cvtColor(img_rgb, img, CV_BGR2BGRA);
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for (int minsize = 0; minsize < 2000; minsize = (minsize + 1) * 2)
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{
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stringstream path;
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path << ts->get_data_path() << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize << ".png";
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Mat dst;
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meanShiftSegmentation((GpuMat)img, dst, 10, 10, minsize);
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Mat dst_rgb;
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cvtColor(dst, dst_rgb, CV_BGRA2BGR);
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//imwrite(path.str(), dst_rgb);
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Mat dst_ref = imread(path.str());
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if (dst_ref.empty())
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{
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ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
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return;
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}
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if (abs(cv::norm(dst_rgb - dst_ref, NORM_INF)) > 1e-3)
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{
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ts->printf(CvTS::LOG, "\ndiffers from image *minsize%d.png\n", minsize);
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ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);
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return;
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}
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}
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}
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catch (const cv::Exception& e)
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{
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if (!check_and_treat_gpu_exception(e, ts))
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throw;
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return;
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}
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ts->set_failed_test_info(CvTS::OK);
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}
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} ms_segm_test;
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