Tegra optimization for image filtering
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modules/imgproc/perf/perf_filter2d.cpp
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45
modules/imgproc/perf/perf_filter2d.cpp
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@ -0,0 +1,45 @@
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#include "perf_precomp.hpp"
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using namespace std;
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using namespace cv;
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using namespace perf;
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using namespace testing;
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using std::tr1::make_tuple;
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using std::tr1::get;
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CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT_101);
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typedef TestBaseWithParam< tr1::tuple<Size, int, BorderMode> > TestFilter2d;
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PERF_TEST_P( TestFilter2d, Filter2d,
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Combine(
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Values( Size(320, 240), szVGA, sz720p, sz1080p ),
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Values( 3, 5 ),
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ValuesIn( BorderMode::all() )
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)
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)
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{
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Size sz;
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int borderMode, kSize;
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sz = get<0>(GetParam());
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kSize = get<1>(GetParam());
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borderMode = get<2>(GetParam());
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Mat src(sz, CV_8UC4);
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Mat dst(sz, CV_8UC4);
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Mat kernel(kSize, kSize, CV_32FC1);
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randu(kernel, -3, 10);
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float s = fabs( sum(kernel)[0] );
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if(s > 1e-3) kernel /= s;
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declare.in(src, WARMUP_RNG).out(dst).time(20);
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TEST_CYCLE() filter2D(src, dst, CV_8UC4, kernel, Point(1, 1), 0., borderMode);
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SANITY_CHECK(dst);
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}
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@ -3010,6 +3010,11 @@ void cv::filter2D( InputArray _src, OutputArray _dst, int ddepth,
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Mat dst = _dst.getMat();
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anchor = normalizeAnchor(anchor, kernel.size());
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#ifdef HAVE_TEGRA_OPTIMIZATION
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if( tegra::filter2D(src, dst, kernel, anchor, delta, borderType) )
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return;
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#endif
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if( kernel.cols*kernel.rows >= dft_filter_size )
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{
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Mat temp;
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@ -311,6 +311,12 @@ void cv::boxFilter( InputArray _src, OutputArray _dst, int ddepth,
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if( src.cols == 1 )
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ksize.width = 1;
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}
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#ifdef HAVE_TEGRA_OPTIMIZATION
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if ( tegra::boxFilter(src, dst, ksize, anchor, normalize, borderType) )
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return;
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#endif
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Ptr<FilterEngine> f = createBoxFilter( src.type(), dst.type(),
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ksize, anchor, normalize, borderType );
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f->apply( src, dst );
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